The 10 Most Innovative AI Leaders Transforming the Industry, 2024

1. Issue: 33 | 2024 THE MOST NNOVATIVE LEADERS TRANSFORMING THE INDUSTRY, 2024 IN FOCUS Innovative AI Leaders: Shaping the Future Through Vision and Technology Senior Machine Learning Principal Heping Liu www.ciobusinessworld.com Navigating the Future of AI and Machine Learning in Enterprise Solutions

4. Editor in chief Robert Patrick Contents Managing Editor : Smith Collins Design Visualizer : Jack Thomas Arts & Design Director : Adam Jones Associate Designer : Erick Williams Sales Senior Sales Manager : Scott M Marketing Manager : Andrew T Sales Executive : Mark Davis Technical Victor Anderson SME- SMO Research Analyst : Henry Martinez SEO Executive : Daniel Lee Circulation Manager Alexander Nelson Follow us : www.ciobusinessworld.com

6. Editorial Note The Role of Innovative Leadership in Industry Evolution I n today's rapidly evolving digital landscape, innovation has become the driving force behind industry transformation. As businesses navigate the complexities of a technology- driven world, leadership plays a pivotal role in steering organizations toward sustainable growth, resilience, and competitive differentiation. At the heart of this change are innovative leaders who not only embrace technological advancements but also inspire teams to adapt and thrive in an era of constant disruption. The term "innovation" is often associated with groundbreaking products and disruptive technologies. However, true innovation transcends mere technological prowess. It involves reshaping business models, reimagining customer experiences, and fostering a culture of creativity and collaboration within organizations. Leaders who champion innovation are those

7. who understand that success in the modern world is not solely measured by market share or profit margins, but by the ability to anticipate change, take calculated risks, and transform challenges into opportunities. At CIO Business World, we have the privilege of interacting with some of the brightest minds across industries. Through our engagement with visionary leaders, we've observed how transformative leadership fuels innovation, ensuring organizations not only survive but excel in an increasingly competitive marketplace. These leaders bring a blend of technical expertise, emotional intelligence, and a deep understanding of market dynamics to their roles, enabling them to make bold decisions that shape the future of their industries. A key characteristic of these innovative leaders is their willingness to embrace emerging technologies, such as artificial intelligence, blockchain, and the Internet of Things (IoT). Yet, their true strength lies in their ability to align these technologies with the broader organizational vision. For them, digital transformation is not just about implementing the latest tools but about creating a seamless integration of technology, people, and processes to unlock new levels of efficiency and innovation. Moreover, these leaders are committed to fostering a culture of inclusivity and collaboration within their teams. By empowering employees to think creatively and challenge the status quo, they build a workforce that is agile, adaptable, and ready to tackle the challenges of tomorrow. Innovation, after all, is not confined to the C- suite; it flourishes when it is embraced at every level of the organization. In this feature, we will explore the stories of some of these trailblazing leaders—individuals who are not only transforming their companies but also redefining the industries they operate in. From CEOs at the helm of tech giants to CIOs leading digital revolutions in traditional sectors, these leaders serve as a beacon for what it means to lead with innovation in mind. As the business world continues to evolve, the role of innovative leaders will only become more critical. They are the ones who will steer their organizations through the waves of disruption, ensuring that they remain resilient, relevant, and poised for long-term success. We at CIO Business World are proud to shine a spotlight on these transformative leaders and celebrate their contributions to shaping the future of industry. Their stories are not just about leadership but about the power of innovation to change the world.

8. Contetns COVER STORY 12 Heaping Liu

9. Article Business Pro?ile Innovative AI Leaders: Shaping the Future Through Vision and Technology 28 24 Christophe Foulon CXO CXO Artificial Intelligence: Balancing Cybersecurity Risks and Defenses 20 The 30 evolution and distinction of AGV and AMR concepts in mobile robotics CXO The impact of AI on the enterprise sector with a focus on the Middle East 34

12. COVER STORY Heping Liu Navigating the Future of AI and Machine Learning in Enterprise Solutions 12

13. Senior Machine Learning Principal 13 www.ciobusinessworld.com

14. Long-Term Vision and Goals the Workday system using large language models (LLMs), exemplify Dr. Liu's visionary leadership and his capacity to overcome technical and strategic hurdles. Dr. Liu's long-term vision involves continuing to drive innovation in areas such as forecasting, optimization, machine learning, generative and multimodal AI, and Artificial General Intelligence (AGI). His focus is on creating impactful solutions that have the potential to transform industries. A key aspect of this vision is advocating for and building a data environment that is friendly to generative and conversational AI. Utilizing distributed system design, Dr. Liu aims to develop cutting- edge products and services based on generative and multimodal AI models, while exploring the application of time series foundation models to various types of time series data and optimization models. Workday's Mission and Vision Workday, Inc. is a leading provider of enterprise cloud applications for finance and human resources. Its mission is to deliver innovative cloud-based solutions that empower businesses to thrive in the digital age. By providing user- friendly applications that streamline operations, Workday enables organizations to reach their full potential. Leveraging AI and machine learning, the company seeks to revolutionize how businesses manage human resources, finance, and other critical functions. Workday envisions a future where every organization has access to the tools and resources needed to succeed in a digital-first world. The company aspires to be at the forefront of digital transformation in the enterprise software industry, offering advanced technology that enhances efficiency, collaboration, and growth. Workday's vision is to empower businesses to make data-driven decisions and seamlessly integrate technology into all aspects of their operations, fostering a more connected and productive workforce. Within Workday, Dr. Liu's future goals are centered around intelligent solutions by advancing time series forecasting and optimization models, enhancing distributed systems, and exploring and developing generative and conversational AI applications. By integrating advanced AI and machine learning techniques, he seeks to make Workday's HR and financial data enterprise solutions more intelligent and adaptive. Leveraging generative and conversational AI, Dr. Liu aims to create innovative tools that enhance user generative and conversational experience and provide deeper data insights. He is committed to advocating for a domain-friendly data environment that supports efficient use of generative and conversational AI, ensuring scalability, reliability, security, and performance of AI- driven products and services in the big data environment. Building and Managing Effective Teams A key component of Dr. Liu's leadership philosophy is building and managing motivated and effective teams. He places significant emphasis on fostering an environment where team members are self-driven, disciplined, and aligned with both the technological and cultural aspects of the organization. Clear communication is paramount, ensuring that each team member understands their role and the broader organizational objectives. Dr. Liu believes in granting autonomy to his team, allowing them to explore creative solutions while offering guidance and support as needed. This approach cultivates a culture of collaboration, respect, and continuous learning, where team members are encouraged to take ownership of their projects and grow their skill sets. Workday Culture and Values Workday's culture is centered around the belief that happy employees lead to happy customers. The company fosters a collaborative, inclusive, and innovative work environment. Workday prioritizes employee well-being, diversity, and inclusion, and emphasizes a culture of continuous learning, open communication, and mutual respect. Workday's values encompass several key aspects: employees, customer service, innovation, integrity, fun, and profitability. The company is committed to fostering a supportive environment where employees are encouraged to excel and grow, with a strong emphasis on respect and continuous improvement. Dedicated to delivering exceptional value, Workday prioritizes customer satisfaction and success. The company embraces innovation, learn from outcomes to remain competitive, and deliver long-term value. Honesty and accountability are Hiring the right talent is critical to Dr. Liu's management strategy. Beyond technical skills, he prioritizes cultural fit. Mentoring and professional development are integral to Dr. Liu's approach, enabling team members to thrive and innovate. Recognizing and celebrating achievements further enhances morale and motivation, creating an environment where individuals feel valued and driven to excel. 04 www.ciobusinessworld.com central. Workday also promotes a fun and enjoyable work atmosphere. While profitability is important, the company prioritizes living its values and making sustainable financial decisions. and educating young professionals about AI. His research has resulted in the publication of approximately 20 papers in academic journals, presenting innovative AI, computational intelligence, and deep learning algorithms and models with applications in investment and pricing, revenue management, energy, healthcare, and nano- manufacturing. H adaptability defines longevity, Workday stands out as a beacon of excellence. With a mission to empower organizations to adapt to a changing world, Workday leverages innovative technology to deliver cloud applications for human resources, finance, planning, spend management, and analytics. eping Liu, the Senior Machine Learning Principal at Workday, whose journey from academia to the pinnacle of technological innovation is a testament to resilience, strategic foresight, and an undying passion for artificial intelligence. In the world of enterprise software, where innovation drives success and The Future of AI As the AI landscape continues to evolve, generative AI and large language models are poised to revolutionize various industries by transforming how data is interacted with, processes are automated, and insights are generated. The potential emergence of Artificial General Intelligence (AGI) represents a significant milestone, with AGI systems anticipated to possess broad cognitive abilities across diverse tasks and domains. According to OpenAI, AGI refers to highly autonomous systems that can outperform humans in practically all economically valuable work, encompassing levels of interaction, problem-solving, and innovation that surpass current AI capabilities. In the industry, Dr. Liu has led the development of AI- driven platforms, products, and services across multiple companies. His initiatives include creating time series price forecasting and supply chain optimization models for the food industry, developing a next-generation analytics engine for online advertising, and pioneering big data analytics and clustering modeling for IP intelligence and reputation. These contributions have been utilized in advertisement targeting, transaction fraud prevention, and marketing industries, showcasing Dr. Liu's ability to drive innovation and deliver tangible business value. Journey to Workday Heping Liu's journey as a technology leader is rooted in a rich tapestry of academic and entrepreneurial experiences. Beginning with a master's degree thesis, Dr. Liu explored the potential of neural networks to forecast financial indices and used the Markowitz model for portfolio optimization. This early exposure to the power of computational intelligence laid the groundwork for his pursuit of a Ph.D. in 2004, where his focus was on advancing the field of AI. Transitioning from academia to industry, Dr. Liu embarked on a challenging yet rewarding path through several startup companies, driven by the dream of establishing his own venture and eventually taking it public. At Workday, AI is deeply integrated into the company's platform, driving intelligent predictions and automation. The company is actively preparing for the opportunities presented by advancements in AI, committed to incorporating the latest technologies to enhance its services and maintain a leading edge in innovation. By embracing the potential of generative AI, Workday aims to continue delivering cutting-edge solutions that empower its users and transform industries. In 2018, Dr. Liu founded an AI technology company, leading teams to build a conversational product for the finance and investment industry using Natural Language Understanding (NLU) technologies. The product's major components include a conversational platform based on NLU technologies, a knowledge graph platform utilizing Neo4J and APOC and graph algorithms, a search platform based on ElasticSearch, a big data ETL platform using Spark, Kafka, and Redis, and a web crawling platform to collect real-time finance text and quantitative data. your work.‘ ‘ ‘ ‘ ‘ ‘ ‘ ‘ The entrepreneurial landscape offered Dr. Liu invaluable insights into the nuances of building and leading a company. In Beijing, he founded Unigroup AI Technologies Inc., where he not only managed the company but also spearheaded the development of advanced AI technologies and products. This experience underscored the critical importance of assembling a cohesive team, navigating the complexities inherent to startups, securing funding, and remaining at the forefront of technological trends. These lessons became integral to Dr. Liu's leadership style, characterized by strategic planning and a keen ability to surmount challenges. Transforming the Tech Industry My advice to budding entrepreneurs aspiring to venture into the AI sector is to stay curious, be resilient, and prioritize ethical considerations in At Workday, Dr. Liu has proposed, initiated, and led several key projects, presenting them at the Annual Workday Product & Technology Conferences, known as the Annual Spelunking Conference. These projects and proposals include the Workday Resource Forecasting/Optimization Platform, Forecasting-as-a-Service, a conversational front end for the Workday system using large language models (LLMs), and transforming the Object Management Service (OMS) into an AI-Agent friendly data environment. Dr. Liu's contributions to AI continue to drive innovation and enhance Workday's ability to deliver intelligent, adaptive enterprise solutions. Given the opportunity, Dr. Liu would focus on the early development of generative AI and the integration of function calling with large language models (LLMs). The potential of generative AI spans various applications, enhancing AI's ability to generate high-quality content, design innovative solutions, and assist in creative processes across multiple domains. Integrating function calling with LLMs significantly enhances their usability and effectiveness, allowing LLMs to execute specific tasks, access external databases, and interact with various software systems seamlessly. This integration leads to more intelligent and context-aware AI agents, improving user experience and productivity. Joining Workday Inc. marked a new chapter in Dr. Liu's career, presenting the formidable task of integrating cutting-edge AI solutions within an established enterprise framework. He successfully proposed, initiated, and led several pivotal projects that were showcased at the Annual Workday Product & Technology Conferences, known as the Annual Spelunking Conference. These initiatives, such as the Workday Resource Forecasting/Optimization Platform, Forecasting-as-a- Service and a conversational front end for In addition to his professional work, Dr. Liu dedicates time to mentoring and teaching young professionals, helping them learn the latest advancements in AI. His commitment to education and mentorship underscores his dedication to fostering the next generation of AI leaders, equipping them with the skills and knowledge necessary to navigate and contribute to the dynamic field of artificial intelligence. Impact on AI Dr. Liu has significantly impacted the field of artificial intelligence through his contributions to advancing AI technologies, developing products across various domains, 05 06 www.ciobusinessworld.com www.ciobusinessworld.com 14 The Future of Forecasting and Optimization analysis, model building, and actionable insights. The interaction between users and their data becomes more intelligent, leading to a trend where user needs shift towards business intelligence as users have more freedom to ask complicated analytical questions. Over the next five years, machine learning is poised to play an increasingly central role in forecasting and optimization platforms. Advances in generative models will enable more generalized predictions and optimized decision-making processes, driving efficiency and innovation across industries. A significant trend in forecasting has emerged, with companies leveraging transformer models to build generalized large time series foundation models. Examples include Amazon's Chronos, Salesforce's Moirai, Google's TimesFM, and Datadog's Toto. Both AI agents and conversational interaction require a friendly data environment and smart function calling, which are challenging to build. Continuous improvement of model accuracy is necessary, but understanding domain-specific data remains a significant challenge. To assist AI agents and conversational interaction, labeling and tagging data will become critical to create a more friendly data environment. These large time series pre trained foundation models represent a paradigm shift in forecasting. Traditionally, developing an effective forecasting model required a forecasting expert to tailor a model to a specific dataset. However, with these generalized models, this expertise is no longer a necessity. The models can generalize across various datasets, democratizing prediction modeling by reducing the reliance on specialized forecasting expertise and the need for specific data and computational resources. Workday recognizes these industry trends and opportunities. The company has partnered with Salesforce to develop a new AI employee service agent that will automate time-consuming tasks, provide personalized support, and surface data-driven insights to help employees work smarter and faster. The combination of Salesforce's new Agentforce Platform and Einstein AI with the Workday platform and Workday AI will enable organizations to create and manage agents for various employee service use cases. This AI agent will work with and elevate humans to drive employee and customer success across the business. At Workday, AI is at the core of the platform, powering intelligent predictions and automation like no one else can. AI/ML and Big Data Analytics: The Next Big Trend The next big trend in AI/ML and big data analytics is expected to be in generative and multimodal AI and AGI. These technologies are set to continue evolving, with some models becoming much larger and others, oriented to specific industries or applications, becoming smaller. Equipped with either large or small language models, the application of AI agents is anticipated to become widespread. Advice to Aspiring Entrepreneurs To budding entrepreneurs aspiring to venture into the AI sector, Dr. Liu offers valuable advice: stay curious, be resilient, and prioritize ethical considerations in your work. Understanding your target market, staying attuned to industry trends, and being prepared to pivot when necessary are critical components of success in the dynamic and rapidly evolving field of AI. Continuous learning and adaptation are essential, as the AI landscape is constantly changing and presenting new opportunities and challenges. Furthermore, Dr. Liu emphasizes the importance of ethical considerations in AI development. Strive to develop AI solutions that are fair, transparent, and beneficial to society. By prioritizing ethical considerations, entrepreneurs can ensure that their innovations contribute positively to the world and build trust with users and stakeholders. This approach not only enhances the impact of AI solutions but also aligns with the broader societal goal of harnessing technology for the greater good. Industry leaders, such as ChatGPT 3.5 and subsequent versions, serve as language foundational models, and companies are exploring ways to apply these foundation models to their businesses. AI agents based on these foundation models have demonstrated the potential to connect LLMs with company domain knowledge, providing automated services. AI agents act as cognition amplifiers, anticipating user needs and helping them accomplish tasks. They offer predictive, conversational and generative capabilities along with advanced analytics, providing users with intelligent and context-aware interactions. The internet may evolve into a network of AI agents, with humans focusing more on reviewing and approving the work of AI agents. With the introduction of LLMs, user interaction with data is shifting from customized user web interfaces to conversational approaches. This revolutionizes how users interact with proprietary data, enabling dialogues, report generation, dataset comparison and 07

15. central. Workday also promotes a fun and enjoyable work atmosphere. While profitability is important, the company prioritizes living its values and making sustainable financial decisions. and educating young professionals about AI. His research has resulted in the publication of approximately 20 papers in academic journals, presenting innovative AI, computational intelligence, and deep learning algorithms and models with applications in investment and pricing, revenue management, energy, healthcare, and nano- manufacturing. Long-Term Vision and Goals the Workday system using large language models (LLMs), exemplify Dr. Liu's visionary leadership and his capacity to overcome technical and strategic hurdles. The Future of AI Dr. Liu's long-term vision involves continuing to drive innovation in areas such as forecasting, optimization, machine learning, generative and multimodal AI, and Artificial General Intelligence (AGI). His focus is on creating impactful solutions that have the potential to transform industries. A key aspect of this vision is advocating for and building a data environment that is friendly to generative and conversational AI. Utilizing distributed system design, Dr. Liu aims to develop cutting- edge products and services based on generative and multimodal AI models, while exploring the application of time series foundation models to various types of time series data and optimization models. As the AI landscape continues to evolve, generative AI and large language models are poised to revolutionize various industries by transforming how data is interacted with, processes are automated, and insights are generated. The potential emergence of Artificial General Intelligence (AGI) represents a significant milestone, with AGI systems anticipated to possess broad cognitive abilities across diverse tasks and domains. According to OpenAI, AGI refers to highly autonomous systems that can outperform humans in practically all economically valuable work, encompassing levels of interaction, problem-solving, and innovation that surpass current AI capabilities. Workday's Mission and Vision In the industry, Dr. Liu has led the development of AI- driven platforms, products, and services across multiple companies. His initiatives include creating time series price forecasting and supply chain optimization models for the food industry, developing a next-generation analytics engine for online advertising, and pioneering big data analytics and clustering modeling for IP intelligence and reputation. These contributions have been utilized in advertisement targeting, transaction fraud prevention, and marketing industries, showcasing Dr. Liu's ability to drive innovation and deliver tangible business value. Workday, Inc. is a leading provider of enterprise cloud applications for finance and human resources. Its mission is to deliver innovative cloud-based solutions that empower businesses to thrive in the digital age. By providing user- friendly applications that streamline operations, Workday enables organizations to reach their full potential. Leveraging AI and machine learning, the company seeks to revolutionize how businesses manage human resources, finance, and other critical functions. Workday envisions a future where every organization has access to the tools and resources needed to succeed in a digital-first world. The company aspires to be at the forefront of digital transformation in the enterprise software industry, offering advanced technology that enhances efficiency, collaboration, and growth. Workday's vision is to empower businesses to make data-driven decisions and seamlessly integrate technology into all aspects of their operations, fostering a more connected and productive workforce. Within Workday, Dr. Liu's future goals are centered around intelligent solutions by advancing time series forecasting and optimization models, enhancing distributed systems, and exploring and developing generative and conversational AI applications. By integrating advanced AI and machine learning techniques, he seeks to make Workday's HR and financial data enterprise solutions more intelligent and adaptive. Leveraging generative and conversational AI, Dr. Liu aims to create innovative tools that enhance user generative and conversational experience and provide deeper data insights. He is committed to advocating for a domain-friendly data environment that supports efficient use of generative and conversational AI, ensuring scalability, reliability, security, and performance of AI- driven products and services in the big data environment. At Workday, AI is deeply integrated into the company's platform, driving intelligent predictions and automation. The company is actively preparing for the opportunities presented by advancements in AI, committed to incorporating the latest technologies to enhance its services and maintain a leading edge in innovation. By embracing the potential of generative AI, Workday aims to continue delivering cutting-edge solutions that empower its users and transform industries. In 2018, Dr. Liu founded an AI technology company, leading teams to build a conversational product for the finance and investment industry using Natural Language Understanding (NLU) technologies. The product's major components include a conversational platform based on NLU technologies, a knowledge graph platform utilizing Neo4J and APOC and graph algorithms, a search platform based on ElasticSearch, a big data ETL platform using Spark, Kafka, and Redis, and a web crawling platform to collect real-time finance text and quantitative data. your work.‘ ‘ ‘ ‘ ‘ ‘ ‘ ‘ Transforming the Tech Industry Building and Managing Effective Teams My advice to budding entrepreneurs aspiring to venture into the AI sector is to stay curious, be resilient, and prioritize ethical considerations in At Workday, Dr. Liu has proposed, initiated, and led several key projects, presenting them at the Annual Workday Product & Technology Conferences, known as the Annual Spelunking Conference. These projects and proposals include the Workday Resource Forecasting/Optimization Platform, Forecasting-as-a-Service, a conversational front end for the Workday system using large language models (LLMs), and transforming the Object Management Service (OMS) into an AI-Agent friendly data environment. Dr. Liu's contributions to AI continue to drive innovation and enhance Workday's ability to deliver intelligent, adaptive enterprise solutions. Given the opportunity, Dr. Liu would focus on the early development of generative AI and the integration of function calling with large language models (LLMs). The potential of generative AI spans various applications, enhancing AI's ability to generate high-quality content, design innovative solutions, and assist in creative processes across multiple domains. Integrating function calling with LLMs significantly enhances their usability and effectiveness, allowing LLMs to execute specific tasks, access external databases, and interact with various software systems seamlessly. This integration leads to more intelligent and context-aware AI agents, improving user experience and productivity. A key component of Dr. Liu's leadership philosophy is building and managing motivated and effective teams. He places significant emphasis on fostering an environment where team members are self-driven, disciplined, and aligned with both the technological and cultural aspects of the organization. Clear communication is paramount, ensuring that each team member understands their role and the broader organizational objectives. Dr. Liu believes in granting autonomy to his team, allowing them to explore creative solutions while offering guidance and support as needed. This approach cultivates a culture of collaboration, respect, and continuous learning, where team members are encouraged to take ownership of their projects and grow their skill sets. Workday Culture and Values Workday's culture is centered around the belief that happy employees lead to happy customers. The company fosters a collaborative, inclusive, and innovative work environment. Workday prioritizes employee well-being, diversity, and inclusion, and emphasizes a culture of continuous learning, open communication, and mutual respect. In addition to his professional work, Dr. Liu dedicates time to mentoring and teaching young professionals, helping them learn the latest advancements in AI. His commitment to education and mentorship underscores his dedication to fostering the next generation of AI leaders, equipping them with the skills and knowledge necessary to navigate and contribute to the dynamic field of artificial intelligence. Workday's values encompass several key aspects: employees, customer service, innovation, integrity, fun, and profitability. The company is committed to fostering a supportive environment where employees are encouraged to excel and grow, with a strong emphasis on respect and continuous improvement. Dedicated to delivering exceptional value, Workday prioritizes customer satisfaction and success. The company embraces innovation, learn from outcomes to remain competitive, and deliver long-term value. Honesty and accountability are Impact on AI Hiring the right talent is critical to Dr. Liu's management strategy. Beyond technical skills, he prioritizes cultural fit. Mentoring and professional development are integral to Dr. Liu's approach, enabling team members to thrive and innovate. Recognizing and celebrating achievements further enhances morale and motivation, creating an environment where individuals feel valued and driven to excel. Dr. Liu has significantly impacted the field of artificial intelligence through his contributions to advancing AI technologies, developing products across various domains, 05 06 www.ciobusinessworld.com www.ciobusinessworld.com 15 www.ciobusinessworld.com The Future of Forecasting and Optimization analysis, model building, and actionable insights. The interaction between users and their data becomes more intelligent, leading to a trend where user needs shift towards business intelligence as users have more freedom to ask complicated analytical questions. Over the next five years, machine learning is poised to play an increasingly central role in forecasting and optimization platforms. Advances in generative models will enable more generalized predictions and optimized decision-making processes, driving efficiency and innovation across industries. A significant trend in forecasting has emerged, with companies leveraging transformer models to build generalized large time series foundation models. Examples include Amazon's Chronos, Salesforce's Moirai, Google's TimesFM, and Datadog's Toto. Both AI agents and conversational interaction require a friendly data environment and smart function calling, which are challenging to build. Continuous improvement of model accuracy is necessary, but understanding domain-specific data remains a significant challenge. To assist AI agents and conversational interaction, labeling and tagging data will become critical to create a more friendly data environment. These large time series pre trained foundation models represent a paradigm shift in forecasting. Traditionally, developing an effective forecasting model required a forecasting expert to tailor a model to a specific dataset. However, with these generalized models, this expertise is no longer a necessity. The models can generalize across various datasets, democratizing prediction modeling by reducing the reliance on specialized forecasting expertise and the need for specific data and computational resources. Workday recognizes these industry trends and opportunities. The company has partnered with Salesforce to develop a new AI employee service agent that will automate time-consuming tasks, provide personalized support, and surface data-driven insights to help employees work smarter and faster. The combination of Salesforce's new Agentforce Platform and Einstein AI with the Workday platform and Workday AI will enable organizations to create and manage agents for various employee service use cases. This AI agent will work with and elevate humans to drive employee and customer success across the business. At Workday, AI is at the core of the platform, powering intelligent predictions and automation like no one else can. AI/ML and Big Data Analytics: The Next Big Trend The next big trend in AI/ML and big data analytics is expected to be in generative and multimodal AI and AGI. These technologies are set to continue evolving, with some models becoming much larger and others, oriented to specific industries or applications, becoming smaller. Equipped with either large or small language models, the application of AI agents is anticipated to become widespread. Advice to Aspiring Entrepreneurs To budding entrepreneurs aspiring to venture into the AI sector, Dr. Liu offers valuable advice: stay curious, be resilient, and prioritize ethical considerations in your work. Understanding your target market, staying attuned to industry trends, and being prepared to pivot when necessary are critical components of success in the dynamic and rapidly evolving field of AI. Continuous learning and adaptation are essential, as the AI landscape is constantly changing and presenting new opportunities and challenges. Furthermore, Dr. Liu emphasizes the importance of ethical considerations in AI development. Strive to develop AI solutions that are fair, transparent, and beneficial to society. By prioritizing ethical considerations, entrepreneurs can ensure that their innovations contribute positively to the world and build trust with users and stakeholders. This approach not only enhances the impact of AI solutions but also aligns with the broader societal goal of harnessing technology for the greater good. Industry leaders, such as ChatGPT 3.5 and subsequent versions, serve as language foundational models, and companies are exploring ways to apply these foundation models to their businesses. AI agents based on these foundation models have demonstrated the potential to connect LLMs with company domain knowledge, providing automated services. AI agents act as cognition amplifiers, anticipating user needs and helping them accomplish tasks. They offer predictive, conversational and generative capabilities along with advanced analytics, providing users with intelligent and context-aware interactions. The internet may evolve into a network of AI agents, with humans focusing more on reviewing and approving the work of AI agents. With the introduction of LLMs, user interaction with data is shifting from customized user web interfaces to conversational approaches. This revolutionizes how users interact with proprietary data, enabling dialogues, report generation, dataset comparison and 07

16. central. Workday also promotes a fun and enjoyable work atmosphere. While profitability is important, the company prioritizes living its values and making sustainable financial decisions. and educating young professionals about AI. His research has resulted in the publication of approximately 20 papers in academic journals, presenting innovative AI, computational intelligence, and deep learning algorithms and models with applications in investment and pricing, revenue management, energy, healthcare, and nano- manufacturing. The Future of AI As the AI landscape continues to evolve, generative AI and large language models are poised to revolutionize various industries by transforming how data is interacted with, processes are automated, and insights are generated. The potential emergence of Artificial General Intelligence (AGI) represents a significant milestone, with AGI systems anticipated to possess broad cognitive abilities across diverse tasks and domains. According to OpenAI, AGI refers to highly autonomous systems that can outperform humans in practically all economically valuable work, encompassing levels of interaction, problem-solving, and innovation that surpass current AI capabilities. In the industry, Dr. Liu has led the development of AI- driven platforms, products, and services across multiple companies. His initiatives include creating time series price forecasting and supply chain optimization models for the food industry, developing a next-generation analytics engine for online advertising, and pioneering big data analytics and clustering modeling for IP intelligence and reputation. These contributions have been utilized in advertisement targeting, transaction fraud prevention, and marketing industries, showcasing Dr. Liu's ability to drive innovation and deliver tangible business value. At Workday, AI is deeply integrated into the company's platform, driving intelligent predictions and automation. The company is actively preparing for the opportunities presented by advancements in AI, committed to incorporating the latest technologies to enhance its services and maintain a leading edge in innovation. By embracing the potential of generative AI, Workday aims to continue delivering cutting-edge solutions that empower its users and transform industries. In 2018, Dr. Liu founded an AI technology company, leading teams to build a conversational product for the finance and investment industry using Natural Language Understanding (NLU) technologies. The product's major components include a conversational platform based on NLU technologies, a knowledge graph platform utilizing Neo4J and APOC and graph algorithms, a search platform based on ElasticSearch, a big data ETL platform using Spark, Kafka, and Redis, and a web crawling platform to collect real-time finance text and quantitative data. your work.‘ ‘ ‘ ‘ ‘ ‘ ‘ ‘ My advice to budding entrepreneurs aspiring to venture into the AI sector is to stay curious, be resilient, and prioritize ethical considerations in Transforming the Tech Industry At Workday, Dr. Liu has proposed, initiated, and led several key projects, presenting them at the Annual Workday Product & Technology Conferences, known as the Annual Spelunking Conference. These projects and proposals include the Workday Resource Forecasting/Optimization Platform, Forecasting-as-a-Service, a conversational front end for the Workday system using large language models (LLMs), and transforming the Object Management Service (OMS) into an AI-Agent friendly data environment. Dr. Liu's contributions to AI continue to drive innovation and enhance Workday's ability to deliver intelligent, adaptive enterprise solutions. Given the opportunity, Dr. Liu would focus on the early development of generative AI and the integration of function calling with large language models (LLMs). The potential of generative AI spans various applications, enhancing AI's ability to generate high-quality content, design innovative solutions, and assist in creative processes across multiple domains. Integrating function calling with LLMs significantly enhances their usability and effectiveness, allowing LLMs to execute specific tasks, access external databases, and interact with various software systems seamlessly. This integration leads to more intelligent and context-aware AI agents, improving user experience and productivity. In addition to his professional work, Dr. Liu dedicates time to mentoring and teaching young professionals, helping them learn the latest advancements in AI. His commitment to education and mentorship underscores his dedication to fostering the next generation of AI leaders, equipping them with the skills and knowledge necessary to navigate and contribute to the dynamic field of artificial intelligence. Impact on AI Dr. Liu has significantly impacted the field of artificial intelligence through his contributions to advancing AI technologies, developing products across various domains, 06 www.ciobusinessworld.com www.ciobusinessworld.com 16 The Future of Forecasting and Optimization analysis, model building, and actionable insights. The interaction between users and their data becomes more intelligent, leading to a trend where user needs shift towards business intelligence as users have more freedom to ask complicated analytical questions. Over the next five years, machine learning is poised to play an increasingly central role in forecasting and optimization platforms. Advances in generative models will enable more generalized predictions and optimized decision-making processes, driving efficiency and innovation across industries. A significant trend in forecasting has emerged, with companies leveraging transformer models to build generalized large time series foundation models. Examples include Amazon's Chronos, Salesforce's Moirai, Google's TimesFM, and Datadog's Toto. Both AI agents and conversational interaction require a friendly data environment and smart function calling, which are challenging to build. Continuous improvement of model accuracy is necessary, but understanding domain-specific data remains a significant challenge. To assist AI agents and conversational interaction, labeling and tagging data will become critical to create a more friendly data environment. These large time series pre trained foundation models represent a paradigm shift in forecasting. Traditionally, developing an effective forecasting model required a forecasting expert to tailor a model to a specific dataset. However, with these generalized models, this expertise is no longer a necessity. The models can generalize across various datasets, democratizing prediction modeling by reducing the reliance on specialized forecasting expertise and the need for specific data and computational resources. Workday recognizes these industry trends and opportunities. The company has partnered with Salesforce to develop a new AI employee service agent that will automate time-consuming tasks, provide personalized support, and surface data-driven insights to help employees work smarter and faster. The combination of Salesforce's new Agentforce Platform and Einstein AI with the Workday platform and Workday AI will enable organizations to create and manage agents for various employee service use cases. This AI agent will work with and elevate humans to drive employee and customer success across the business. At Workday, AI is at the core of the platform, powering intelligent predictions and automation like no one else can. AI/ML and Big Data Analytics: The Next Big Trend The next big trend in AI/ML and big data analytics is expected to be in generative and multimodal AI and AGI. These technologies are set to continue evolving, with some models becoming much larger and others, oriented to specific industries or applications, becoming smaller. Equipped with either large or small language models, the application of AI agents is anticipated to become widespread. Advice to Aspiring Entrepreneurs To budding entrepreneurs aspiring to venture into the AI sector, Dr. Liu offers valuable advice: stay curious, be resilient, and prioritize ethical considerations in your work. Understanding your target market, staying attuned to industry trends, and being prepared to pivot when necessary are critical components of success in the dynamic and rapidly evolving field of AI. Continuous learning and adaptation are essential, as the AI landscape is constantly changing and presenting new opportunities and challenges. Furthermore, Dr. Liu emphasizes the importance of ethical considerations in AI development. Strive to develop AI solutions that are fair, transparent, and beneficial to society. By prioritizing ethical considerations, entrepreneurs can ensure that their innovations contribute positively to the world and build trust with users and stakeholders. This approach not only enhances the impact of AI solutions but also aligns with the broader societal goal of harnessing technology for the greater good. Industry leaders, such as ChatGPT 3.5 and subsequent versions, serve as language foundational models, and companies are exploring ways to apply these foundation models to their businesses. AI agents based on these foundation models have demonstrated the potential to connect LLMs with company domain knowledge, providing automated services. AI agents act as cognition amplifiers, anticipating user needs and helping them accomplish tasks. They offer predictive, conversational and generative capabilities along with advanced analytics, providing users with intelligent and context-aware interactions. The internet may evolve into a network of AI agents, with humans focusing more on reviewing and approving the work of AI agents. With the introduction of LLMs, user interaction with data is shifting from customized user web interfaces to conversational approaches. This revolutionizes how users interact with proprietary data, enabling dialogues, report generation, dataset comparison and 07

17. your work.‘ ‘ ‘ ‘ ‘ ‘ ‘ ‘ My advice to budding entrepreneurs aspiring to venture into the AI sector is to stay curious, be resilient, and prioritize ethical considerations in 17 www.ciobusinessworld.com www.ciobusinessworld.com The Future of Forecasting and Optimization analysis, model building, and actionable insights. The interaction between users and their data becomes more intelligent, leading to a trend where user needs shift towards business intelligence as users have more freedom to ask complicated analytical questions. Over the next five years, machine learning is poised to play an increasingly central role in forecasting and optimization platforms. Advances in generative models will enable more generalized predictions and optimized decision-making processes, driving efficiency and innovation across industries. A significant trend in forecasting has emerged, with companies leveraging transformer models to build generalized large time series foundation models. Examples include Amazon's Chronos, Salesforce's Moirai, Google's TimesFM, and Datadog's Toto. Both AI agents and conversational interaction require a friendly data environment and smart function calling, which are challenging to build. Continuous improvement of model accuracy is necessary, but understanding domain-specific data remains a significant challenge. To assist AI agents and conversational interaction, labeling and tagging data will become critical to create a more friendly data environment. These large time series pre trained foundation models represent a paradigm shift in forecasting. Traditionally, developing an effective forecasting model required a forecasting expert to tailor a model to a specific dataset. However, with these generalized models, this expertise is no longer a necessity. The models can generalize across various datasets, democratizing prediction modeling by reducing the reliance on specialized forecasting expertise and the need for specific data and computational resources. Workday recognizes these industry trends and opportunities. The company has partnered with Salesforce to develop a new AI employee service agent that will automate time-consuming tasks, provide personalized support, and surface data-driven insights to help employees work smarter and faster. The combination of Salesforce's new Agentforce Platform and Einstein AI with the Workday platform and Workday AI will enable organizations to create and manage agents for various employee service use cases. This AI agent will work with and elevate humans to drive employee and customer success across the business. At Workday, AI is at the core of the platform, powering intelligent predictions and automation like no one else can. AI/ML and Big Data Analytics: The Next Big Trend The next big trend in AI/ML and big data analytics is expected to be in generative and multimodal AI and AGI. These technologies are set to continue evolving, with some models becoming much larger and others, oriented to specific industries or applications, becoming smaller. Equipped with either large or small language models, the application of AI agents is anticipated to become widespread. Advice to Aspiring Entrepreneurs To budding entrepreneurs aspiring to venture into the AI sector, Dr. Liu offers valuable advice: stay curious, be resilient, and prioritize ethical considerations in your work. Understanding your target market, staying attuned to industry trends, and being prepared to pivot when necessary are critical components of success in the dynamic and rapidly evolving field of AI. Continuous learning and adaptation are essential, as the AI landscape is constantly changing and presenting new opportunities and challenges. Furthermore, Dr. Liu emphasizes the importance of ethical considerations in AI development. Strive to develop AI solutions that are fair, transparent, and beneficial to society. By prioritizing ethical considerations, entrepreneurs can ensure that their innovations contribute positively to the world and build trust with users and stakeholders. This approach not only enhances the impact of AI solutions but also aligns with the broader societal goal of harnessing technology for the greater good. Industry leaders, such as ChatGPT 3.5 and subsequent versions, serve as language foundational models, and companies are exploring ways to apply these foundation models to their businesses. AI agents based on these foundation models have demonstrated the potential to connect LLMs with company domain knowledge, providing automated services. AI agents act as cognition amplifiers, anticipating user needs and helping them accomplish tasks. They offer predictive, conversational and generative capabilities along with advanced analytics, providing users with intelligent and context-aware interactions. The internet may evolve into a network of AI agents, with humans focusing more on reviewing and approving the work of AI agents. With the introduction of LLMs, user interaction with data is shifting from customized user web interfaces to conversational approaches. This revolutionizes how users interact with proprietary data, enabling dialogues, report generation, dataset comparison and 07

18. The Future of Forecasting and Optimization analysis, model building, and actionable insights. The interaction between users and their data becomes more intelligent, leading to a trend where user needs shift towards business intelligence as users have more freedom to ask complicated analytical questions. Over the next five years, machine learning is poised to play an increasingly central role in forecasting and optimization platforms. Advances in generative models will enable more generalized predictions and optimized decision-making processes, driving efficiency and innovation across industries. A significant trend in forecasting has emerged, with companies leveraging transformer models to build generalized large time series foundation models. Examples include Amazon's Chronos, Salesforce's Moirai, Google's TimesFM, and Datadog's Toto. Both AI agents and conversational interaction require a friendly data environment and smart function calling, which are challenging to build. Continuous improvement of model accuracy is necessary, but understanding domain-specific data remains a significant challenge. To assist AI agents and conversational interaction, labeling and tagging data will become critical to create a more friendly data environment. These large time series pre trained foundation models represent a paradigm shift in forecasting. Traditionally, developing an effective forecasting model required a forecasting expert to tailor a model to a specific dataset. However, with these generalized models, this expertise is no longer a necessity. The models can generalize across various datasets, democratizing prediction modeling by reducing the reliance on specialized forecasting expertise and the need for specific data and computational resources. Workday recognizes these industry trends and opportunities. The company has partnered with Salesforce to develop a new AI employee service agent that will automate time-consuming tasks, provide personalized support, and surface data-driven insights to help employees work smarter and faster. The combination of Salesforce's new Agentforce Platform and Einstein AI with the Workday platform and Workday AI will enable organizations to create and manage agents for various employee service use cases. This AI agent will work with and elevate humans to drive employee and customer success across the business. At Workday, AI is at the core of the platform, powering intelligent predictions and automation like no one else can. AI/ML and Big Data Analytics: The Next Big Trend The next big trend in AI/ML and big data analytics is expected to be in generative and multimodal AI and AGI. These technologies are set to continue evolving, with some models becoming much larger and others, oriented to specific industries or applications, becoming smaller. Equipped with either large or small language models, the application of AI agents is anticipated to become widespread. Advice to Aspiring Entrepreneurs To budding entrepreneurs aspiring to venture into the AI sector, Dr. Liu offers valuable advice: stay curious, be resilient, and prioritize ethical considerations in your work. Understanding your target market, staying attuned to industry trends, and being prepared to pivot when necessary are critical components of success in the dynamic and rapidly evolving field of AI. Continuous learning and adaptation are essential, as the AI landscape is constantly changing and presenting new opportunities and challenges. Furthermore, Dr. Liu emphasizes the importance of ethical considerations in AI development. Strive to develop AI solutions that are fair, transparent, and beneficial to society. By prioritizing ethical considerations, entrepreneurs can ensure that their innovations contribute positively to the world and build trust with users and stakeholders. This approach not only enhances the impact of AI solutions but also aligns with the broader societal goal of harnessing technology for the greater good. Industry leaders, such as ChatGPT 3.5 and subsequent versions, serve as language foundational models, and companies are exploring ways to apply these foundation models to their businesses. AI agents based on these foundation models have demonstrated the potential to connect LLMs with company domain knowledge, providing automated services. AI agents act as cognition amplifiers, anticipating user needs and helping them accomplish tasks. They offer predictive, conversational and generative capabilities along with advanced analytics, providing users with intelligent and context-aware interactions. The internet may evolve into a network of AI agents, with humans focusing more on reviewing and approving the work of AI agents. With the introduction of LLMs, user interaction with data is shifting from customized user web interfaces to conversational approaches. This revolutionizes how users interact with proprietary data, enabling dialogues, report generation, dataset comparison and 18

20. Articial Intelligence: Balancing Cybersecurity Risks and Defenses A the modern digital landscape. This article delves into how AI is contributing to increased cybersecurity risks while simultaneously bolstering defense mechanisms, highlighting the complex interplay between innovation and vulnerability in today's cyber realm. rtificial Intelligence (AI) stands at the forefront of both cybersecurity risks and defenses, embodying a dual role that shapes improperly transferring $25M to an account controlled by the attacker. Adversarial AI: Researchers have demonstrated the potential for AI algorithms to be manipulated or deceived, leading to adversarial attacks. These attacks exploit vulnerabilities in AI systems, causing them to misclassify data or make incorrect decisions, undermining the reliability of AI-based cybersecurity defenses. • Increasing Cyber Risks Privacy Concerns: AI-powered surveillance and data analysis tools raise concerns about privacy infringement. The collection and analysis of vast amounts of personal data can lead to unauthorized access, data breaches, and regulatory non- compliance, posing significant risks to individuals and organizations alike. AI's proliferation in cyber introduces novel risks and challenges that organizations must navigate. Examples include: • Sophisticated Cyberattacks: AI-driven tools can enhance the sophistication and efficiency of cyberattacks. Malicious actors utilize AI to automate tasks like reconnaissance, phishing, and malware deployment, making attacks and malware more targeted and difficult to detect. • AI's Role in Enhancing Cybersecurity Defenses Conversely, AI-driven technologies are instrumental in strengthening cybersecurity defenses, offering proactive measures to mitigate evolving threats: Social Engineering: AI can also make social engineering harder to detect. Phishing emails can be more tailored and contain fewer errors and “tells.” Even video and audio can be faked with AI. In one incident, an attacker used AI to make live deep fakes to impersonate top executives on video calls, thereby tricking an employee into • Threat Detection and Analysis: AI excels in detecting patterns and anomalies within vast datasets, enabling quicker identification of potential threats. Machine Learning algorithms • • can analyze network traffic, user behavior, and system logs in real-time, alerting security teams to suspicious activities promptly. addressed by courts and it may be a while before we have reliably answers. Skill Gap: Effective implementation of AI- powered cybersecurity requires skilled professionals capable of managing, interpreting, and refining AI systems. Bridging the skill gap through training and education is essential to maximizing the potential of AI in cybersecurity defenses. • Automated Response and Mitigation: AI automates incident response processes, allowing for rapid containment and mitigation of cyber threats. Automated systems can isolate compromised systems, update security configurations, and deploy patches to vulnerable software, reducing the window of opportunity for attackers. • Future Outlook Predictive Capabilities: AI's predictive analytics forecast potential cyber threats based on historical data and current trends. This proactive approach enables organizations to preemptively strengthen defenses, allocate resources effectively, and prioritize security measures based on identified risks. • Looking ahead, the evolution of AI in cybersecurity will continue to shape the landscape of digital resilience and vulnerability. Innovations in AI-driven threat detection, behavioral analytics, and automated response systems will redefine cybersecurity strategies, empowering organizations to combat emerging threats effectively. Challenges and Ethical Considerations Striking a balance between leveraging AI's capabilities to fortify defenses while mitigating inherent risks remains paramount. Embracing collaborative efforts among cybersecurity professionals, researchers, and policymakers will drive advancements in AI technologies that safeguard digital assets and uphold cybersecurity resilience. While AI presents significant opportunities for cybersecurity, several challenges and ethical considerations must be addressed: Bias and Fairness: AI algorithms can inadvertently perpetuate biases present in training data, leading to discriminatory outcomes in cybersecurity decisions. Ensuring fairness and transparency in AI models is crucial to mitigating these risks. • Conclusion In conclusion, Artificial Intelligence represents a pivotal force in the dual narrative of cybersecurity, both augmenting risks and fortifying defenses in today's interconnected digital ecosystem. Organizations must navigate this complex landscape with a nuanced understanding of AI's potential vulnerabilities and transformative capabilities. By harnessing AI-driven technologies responsibly, organizations can proactively defend against evolving cyber threats, uphold data integrity, and foster a resilient cybersecurity posture. Embracing ethical considerations, regulatory compliance, and continuous innovation will enable AI to fulfill its promise as a cornerstone of modern cybersecurity defenses, safeguarding businesses and individuals against the ever-evolving threat landscape. Regulatory Compliance: The deployment of AI in cybersecurity must adhere to regulatory frameworks governing data privacy, security standards, and ethical guidelines. Compliance ensures that AI technologies operate within legal boundaries and uphold user trust. • Intellectual Property: Use of AI raises difficult intellectual property problems. For example, if AI generates cybersecurity code, procedures, policies, or other documents in part, on another person's copyrighted works, does it violate their copyright? These questions have yet to be fully • 20

21. CXO • can analyze network traffic, user behavior, and system logs in real-time, alerting security teams to suspicious activities promptly. addressed by courts and it may be a while before we have reliably answers. Articial Intelligence: Balancing Cybersecurity Risks and Defenses A the modern digital landscape. This article delves into how AI is contributing to increased cybersecurity risks while simultaneously bolstering defense mechanisms, highlighting the complex interplay between innovation and vulnerability in today's cyber realm. Skill Gap: Effective implementation of AI- powered cybersecurity requires skilled professionals capable of managing, interpreting, and refining AI systems. Bridging the skill gap through training and education is essential to maximizing the potential of AI in cybersecurity defenses. • Automated Response and Mitigation: AI automates incident response processes, allowing for rapid containment and mitigation of cyber threats. Automated systems can isolate compromised systems, update security configurations, and deploy patches to vulnerable software, reducing the window of opportunity for attackers. • Future Outlook Predictive Capabilities: AI's predictive analytics forecast potential cyber threats based on historical data and current trends. This proactive approach enables organizations to preemptively strengthen defenses, allocate resources effectively, and prioritize security measures based on identified risks. • Looking ahead, the evolution of AI in cybersecurity will continue to shape the landscape of digital resilience and vulnerability. Innovations in AI-driven threat detection, behavioral analytics, and automated response systems will redefine cybersecurity strategies, empowering organizations to combat emerging threats effectively. rtificial Intelligence (AI) stands at the forefront of both cybersecurity risks and defenses, embodying a dual role that shapes improperly transferring $25M to an account controlled by the attacker. Challenges and Ethical Considerations Striking a balance between leveraging AI's capabilities to fortify defenses while mitigating inherent risks remains paramount. Embracing collaborative efforts among cybersecurity professionals, researchers, and policymakers will drive advancements in AI technologies that safeguard digital assets and uphold cybersecurity resilience. Adversarial AI: Researchers have demonstrated the potential for AI algorithms to be manipulated or deceived, leading to adversarial attacks. These attacks exploit vulnerabilities in AI systems, causing them to misclassify data or make incorrect decisions, undermining the reliability of AI-based cybersecurity defenses. • While AI presents significant opportunities for cybersecurity, several challenges and ethical considerations must be addressed: Bias and Fairness: AI algorithms can inadvertently perpetuate biases present in training data, leading to discriminatory outcomes in cybersecurity decisions. Ensuring fairness and transparency in AI models is crucial to mitigating these risks. • Increasing Cyber Risks Conclusion Privacy Concerns: AI-powered surveillance and data analysis tools raise concerns about privacy infringement. The collection and analysis of vast amounts of personal data can lead to unauthorized access, data breaches, and regulatory non- compliance, posing significant risks to individuals and organizations alike. AI's proliferation in cyber introduces novel risks and challenges that organizations must navigate. Examples include: • In conclusion, Artificial Intelligence represents a pivotal force in the dual narrative of cybersecurity, both augmenting risks and fortifying defenses in today's interconnected digital ecosystem. Organizations must navigate this complex landscape with a nuanced understanding of AI's potential vulnerabilities and transformative capabilities. By harnessing AI-driven technologies responsibly, organizations can proactively defend against evolving cyber threats, uphold data integrity, and foster a resilient cybersecurity posture. Embracing ethical considerations, regulatory compliance, and continuous innovation will enable AI to fulfill its promise as a cornerstone of modern cybersecurity defenses, safeguarding businesses and individuals against the ever-evolving threat landscape. Sophisticated Cyberattacks: AI-driven tools can enhance the sophistication and efficiency of cyberattacks. Malicious actors utilize AI to automate tasks like reconnaissance, phishing, and malware deployment, making attacks and malware more targeted and difficult to detect. • Regulatory Compliance: The deployment of AI in cybersecurity must adhere to regulatory frameworks governing data privacy, security standards, and ethical guidelines. Compliance ensures that AI technologies operate within legal boundaries and uphold user trust. • AI's Role in Enhancing Cybersecurity Defenses Conversely, AI-driven technologies are instrumental in strengthening cybersecurity defenses, offering proactive measures to mitigate evolving threats: Social Engineering: AI can also make social engineering harder to detect. Phishing emails can be more tailored and contain fewer errors and “tells.” Even video and audio can be faked with AI. In one incident, an attacker used AI to make live deep fakes to impersonate top executives on video calls, thereby tricking an employee into • Intellectual Property: Use of AI raises difficult intellectual property problems. For example, if AI generates cybersecurity code, procedures, policies, or other documents in part, on another person's copyrighted works, does it violate their copyright? These questions have yet to be fully • Threat Detection and Analysis: AI excels in detecting patterns and anomalies within vast datasets, enabling quicker identification of potential threats. Machine Learning algorithms • 21 www.ciobusinessworld.com

22. • can analyze network traffic, user behavior, and system logs in real-time, alerting security teams to suspicious activities promptly. addressed by courts and it may be a while before we have reliably answers. Skill Gap: Effective implementation of AI- powered cybersecurity requires skilled professionals capable of managing, interpreting, and refining AI systems. Bridging the skill gap through training and education is essential to maximizing the potential of AI in cybersecurity defenses. • Automated Response and Mitigation: AI automates incident response processes, allowing for rapid containment and mitigation of cyber threats. Automated systems can isolate compromised systems, update security configurations, and deploy patches to vulnerable software, reducing the window of opportunity for attackers. • Future Outlook Predictive Capabilities: AI's predictive analytics forecast potential cyber threats based on historical data and current trends. This proactive approach enables organizations to preemptively strengthen defenses, allocate resources effectively, and prioritize security measures based on identified risks. • Looking ahead, the evolution of AI in cybersecurity will continue to shape the landscape of digital resilience and vulnerability. Innovations in AI-driven threat detection, behavioral analytics, and automated response systems will redefine cybersecurity strategies, empowering organizations to combat emerging threats effectively. Challenges and Ethical Considerations Striking a balance between leveraging AI's capabilities to fortify defenses while mitigating inherent risks remains paramount. Embracing collaborative efforts among cybersecurity professionals, researchers, and policymakers will drive advancements in AI technologies that safeguard digital assets and uphold cybersecurity resilience. While AI presents significant opportunities for cybersecurity, several challenges and ethical considerations must be addressed: Bias and Fairness: AI algorithms can inadvertently perpetuate biases present in training data, leading to discriminatory outcomes in cybersecurity decisions. Ensuring fairness and transparency in AI models is crucial to mitigating these risks. • Conclusion In conclusion, Artificial Intelligence represents a pivotal force in the dual narrative of cybersecurity, both augmenting risks and fortifying defenses in today's interconnected digital ecosystem. Organizations must navigate this complex landscape with a nuanced understanding of AI's potential vulnerabilities and transformative capabilities. By harnessing AI-driven technologies responsibly, organizations can proactively defend against evolving cyber threats, uphold data integrity, and foster a resilient cybersecurity posture. Embracing ethical considerations, regulatory compliance, and continuous innovation will enable AI to fulfill its promise as a cornerstone of modern cybersecurity defenses, safeguarding businesses and individuals against the ever-evolving threat landscape. Regulatory Compliance: The deployment of AI in cybersecurity must adhere to regulatory frameworks governing data privacy, security standards, and ethical guidelines. Compliance ensures that AI technologies operate within legal boundaries and uphold user trust. • Intellectual Property: Use of AI raises difficult intellectual property problems. For example, if AI generates cybersecurity code, procedures, policies, or other documents in part, on another person's copyrighted works, does it violate their copyright? These questions have yet to be fully • 22

24. Christophe Foulon Building a Secure Future I This is the story of Christophe Foulon, a cybersecurity leader whose journey from the Helpdesk to influential roles in the industry demonstrates a commitment to innovation, education, and community service. n the heart of the tech industry, where the hum of servers and the clatter of keyboards set the rhythm, a promising young professional embarked on his career at the Helpdesk. Here, he mastered the fundamentals of infrastructure and technology, laying the groundwork for a remarkable journey in cybersecurity. From Helpdesk Beginnings to Cybersecurity Leadership Recognizing the value of his experiences, he created the podcast “Breaking into Cybersecurity,” which quickly became a vital resource for aspiring tech professionals. Through this platform, he shared practical advice and personal stories, resonating with a broad audience seeking to enter the cybersecurity field. Starting his career in the Helpdesk, Christophe Foulon gained a solid foundation in infrastructure and technology. He documented his journey in the podcast “Breaking into Cybersecurity” and authored books such as “Develop your Cybersecurity Path” and “Hack the Cybersecurity Interview.” As his career progressed, he gave back to the community by serving as a Board member and Director for the non-profit Whole Cyber Human Initiative, which focuses on helping veterans transition into cybersecurity and supporting workforce development grants. Now, as a cyber leader, Christophe assists organizations of all sizes with their cybersecurity maturity and risk management. His dedication to helping others didn't stop there. He authored two key books, “Develop your Cybersecurity Path” and “Hack the Cybersecurity Interview,” offering strategic guidance and insights drawn from his own journey. These publications became essential reading for those navigating their way into cybersecurity careers. Dedication to Nexigen's Vision and Values A significant milestone in his career was his involvement with the Whole Cyber Human Initiative, a non-profit organization focused on supporting veterans. As a Board member and Director, he played a critical role in aiding veterans' transition into cybersecurity roles, leveraging workforce development grants to facilitate their career growth. This work was particularly meaningful, providing him with the opportunity to make a substantial impact on individuals' lives and the broader community. Christophe Foulon appreciates Nexigen's dedication to service and community support. As a technical professional, he is particularly drawn to Nexigen's innovative approach to artificial intelligence, which includes creating centers of excellence and governance frameworks. These initiatives provide organizational guardrails around data while allowing data scientists and business analysts the freedom to work with large data models. Nexigen's community- team members' interests with relevant initiatives, encouraging them to take ownership and develop new capabilities. At Nexigen, Christophe values the company's commitment to innovation, trust, service, and community. His work involves innovating safe architectural designs to enable businesses, alongside supporting university research on the trust and safety uses of AI for future development. Nexigen's dedication to community service is evident in its support for AI Centers of Excellence movements like CinyAIWeek, which has gained such popularity that other cities and research hubs are seeking to organize similar activities. Championing Cybersecurity Education and Responsible Innovation Christophe Foulon is passionate about driving business and community awareness around teaching security and privacy topics to younger audiences. His goal is to develop a robust cyber talent pipeline and illustrate cybersecurity as a promising career path. He believes that establishing foundational cybersecurity literacy among students is crucial for enhancing security across all sectors of society. Furthermore, Christophe advises companies in the security space to lead by example. He emphasizes the importance of implementing security and privacy by design principles to mitigate the impact of data exposures, breaches, or accidental leaks. By prioritizing these principles, companies can develop effective solutions while safeguarding customer and organizational data responsibly. driven efforts, such as supporting AI Centers of Excellence like CinyAIWeek, further highlight their commitment to bringing together thought leaders and businesses. Nexigen highly values its employees, regularly organizing company outings, giving holiday gifts, and recognizing outstanding work. The company celebrates team victories during Monday calls, acknowledging those who go above and beyond in serving clients. This "employee-first" mentality boosts customer satisfaction by fostering better service through happier, more engaged employees. Empowered staff offer empathetic and consistent support, leading to improved customer experiences. Additionally, a positive company image, stemming from employee-focused policies, enhances customer loyalty. This approach encourages innovation, reduces conflicts, and results in smoother interactions and fewer complaints. Fostering Innovation and Community When building teams, Christophe Foulon focuses on understanding each team member's unique skills, competencies, and motivations. He combines these individual strengths with the necessary skills and competencies to achieve the business mission. Christophe also assesses the changing business environment and aligns 24

25. BUSINESS PROFILE team members' interests with relevant initiatives, encouraging them to take ownership and develop new capabilities. Christophe Foulon Building a Secure Future At Nexigen, Christophe values the company's commitment to innovation, trust, service, and community. His work involves innovating safe architectural designs to enable businesses, alongside supporting university research on the trust and safety uses of AI for future development. Nexigen's dedication to community service is evident in its support for AI Centers of Excellence movements like CinyAIWeek, which has gained such popularity that other cities and research hubs are seeking to organize similar activities. Championing Cybersecurity Education and Responsible Innovation Christophe Foulon is passionate about driving business and community awareness around teaching security and privacy topics to younger audiences. His goal is to develop a robust cyber talent pipeline and illustrate cybersecurity as a promising career path. He believes that establishing foundational cybersecurity literacy among students is crucial for enhancing security across all sectors of society. Furthermore, Christophe advises companies in the security space to lead by example. He emphasizes the importance of implementing security and privacy by design principles to mitigate the impact of data exposures, breaches, or accidental leaks. By prioritizing these principles, companies can develop effective solutions while safeguarding customer and organizational data responsibly. I This is the story of Christophe Foulon, a cybersecurity leader whose journey from the Helpdesk to influential roles in the industry demonstrates a commitment to innovation, education, and community service. n the heart of the tech industry, where the hum of servers and the clatter of keyboards set the rhythm, a promising young professional embarked on his career at the Helpdesk. Here, he mastered the fundamentals of infrastructure and technology, laying the groundwork for a remarkable journey in cybersecurity. From Helpdesk Beginnings to Cybersecurity Leadership driven efforts, such as supporting AI Centers of Excellence like CinyAIWeek, further highlight their commitment to bringing together thought leaders and businesses. Recognizing the value of his experiences, he created the podcast “Breaking into Cybersecurity,” which quickly became a vital resource for aspiring tech professionals. Through this platform, he shared practical advice and personal stories, resonating with a broad audience seeking to enter the cybersecurity field. Starting his career in the Helpdesk, Christophe Foulon gained a solid foundation in infrastructure and technology. He documented his journey in the podcast “Breaking into Cybersecurity” and authored books such as “Develop your Cybersecurity Path” and “Hack the Cybersecurity Interview.” As his career progressed, he gave back to the community by serving as a Board member and Director for the non-profit Whole Cyber Human Initiative, which focuses on helping veterans transition into cybersecurity and supporting workforce development grants. Now, as a cyber leader, Christophe assists organizations of all sizes with their cybersecurity maturity and risk management. Nexigen highly values its employees, regularly organizing company outings, giving holiday gifts, and recognizing outstanding work. The company celebrates team victories during Monday calls, acknowledging those who go above and beyond in serving clients. This "employee-first" mentality boosts customer satisfaction by fostering better service through happier, more engaged employees. Empowered staff offer empathetic and consistent support, leading to improved customer experiences. Additionally, a positive company image, stemming from employee-focused policies, enhances customer loyalty. This approach encourages innovation, reduces conflicts, and results in smoother interactions and fewer complaints. His dedication to helping others didn't stop there. He authored two key books, “Develop your Cybersecurity Path” and “Hack the Cybersecurity Interview,” offering strategic guidance and insights drawn from his own journey. These publications became essential reading for those navigating their way into cybersecurity careers. Dedication to Nexigen's Vision and Values A significant milestone in his career was his involvement with the Whole Cyber Human Initiative, a non-profit organization focused on supporting veterans. As a Board member and Director, he played a critical role in aiding veterans' transition into cybersecurity roles, leveraging workforce development grants to facilitate their career growth. This work was particularly meaningful, providing him with the opportunity to make a substantial impact on individuals' lives and the broader community. Christophe Foulon appreciates Nexigen's dedication to service and community support. As a technical professional, he is particularly drawn to Nexigen's innovative approach to artificial intelligence, which includes creating centers of excellence and governance frameworks. These initiatives provide organizational guardrails around data while allowing data scientists and business analysts the freedom to work with large data models. Nexigen's community- Fostering Innovation and Community When building teams, Christophe Foulon focuses on understanding each team member's unique skills, competencies, and motivations. He combines these individual strengths with the necessary skills and competencies to achieve the business mission. Christophe also assesses the changing business environment and aligns 25 www.ciobusinessworld.com

26. team members' interests with relevant initiatives, encouraging them to take ownership and develop new capabilities. At Nexigen, Christophe values the company's commitment to innovation, trust, service, and community. His work involves innovating safe architectural designs to enable businesses, alongside supporting university research on the trust and safety uses of AI for future development. Nexigen's dedication to community service is evident in its support for AI Centers of Excellence movements like CinyAIWeek, which has gained such popularity that other cities and research hubs are seeking to organize similar activities. Championing Cybersecurity Education and Responsible Innovation Christophe Foulon is passionate about driving business and community awareness around teaching security and privacy topics to younger audiences. His goal is to develop a robust cyber talent pipeline and illustrate cybersecurity as a promising career path. He believes that establishing foundational cybersecurity literacy among students is crucial for enhancing security across all sectors of society. Furthermore, Christophe advises companies in the security space to lead by example. He emphasizes the importance of implementing security and privacy by design principles to mitigate the impact of data exposures, breaches, or accidental leaks. By prioritizing these principles, companies can develop effective solutions while safeguarding customer and organizational data responsibly. driven efforts, such as supporting AI Centers of Excellence like CinyAIWeek, further highlight their commitment to bringing together thought leaders and businesses. Nexigen highly values its employees, regularly organizing company outings, giving holiday gifts, and recognizing outstanding work. The company celebrates team victories during Monday calls, acknowledging those who go above and beyond in serving clients. This "employee-first" mentality boosts customer satisfaction by fostering better service through happier, more engaged employees. Empowered staff offer empathetic and consistent support, leading to improved customer experiences. Additionally, a positive company image, stemming from employee-focused policies, enhances customer loyalty. This approach encourages innovation, reduces conflicts, and results in smoother interactions and fewer complaints. Fostering Innovation and Community When building teams, Christophe Foulon focuses on understanding each team member's unique skills, competencies, and motivations. He combines these individual strengths with the necessary skills and competencies to achieve the business mission. Christophe also assesses the changing business environment and aligns 26

28. ARTICLE Innovative AI Leaders: Shaping the Future Through Vision andTechnology who understand the profound implications of AI and are committed to harnessing its power for the greater good. the forefront of innovation, enabling businesses to achieve levels of efficiency, accuracy, and personalization that were previously unimaginable. One of the key characteristics of these leaders is their ability to anticipate and respond to the challenges and opportunities that AI presents. They are not content with simply applying existing technologies; they are constantly looking for ways to innovate and push the envelope. This often involves a willingness to take risks, explore uncharted territories, and challenge the status quo. In healthcare, AI has become an invaluable tool in diagnostics, treatment planning, and drug discovery. AI algorithms can analyze complex medical data, identify patterns, and suggest treatment options with a level of precision that far exceeds human capabilities. Innovative leaders in this field are pushing the boundaries of what AI can do, exploring its potential to revolutionize patient care, reduce healthcare costs, and improve outcomes. Another defining trait of AI leaders is their focus on ethical considerations. As AI becomes more integrated into our daily lives, concerns about privacy, bias, and the potential for misuse have come to the forefront. Innovative AI leaders are addressing these issues head-on, developing frameworks and guidelines that ensure AI is used responsibly and ethically. They are advocating for transparency, accountability, and fairness in AI systems, recognizing that the long-term success of AI depends on public trust and acceptance. In the financial sector, AI is transforming how businesses manage risk, detect fraud, and make investment decisions. The ability to process vast amounts of data in real-time allows AI to offer insights that were previously unattainable. This has led to more secure, transparent, and efficient financial systems. Leaders in AI-driven finance are developing sophisticated tools that not only enhance security and compliance but also open up new avenues for growth and innovation. A technological advancement, the role of AI in our lives is expanding at an unprecedented rate. At the helm of this revolution are the innovative AI leaders—visionaries whose work is driving the adoption and integration of AI across various sectors. These leaders are not only advancing the capabilities of AI but are also addressing the ethical, social, and economic implications of its widespread use. rtificial Intelligence (AI) is not just a buzzword; it is a transformative force that is reshaping industries, economies, and societies at large. As we stand on the cusp of a new era in AI's Impact on Society and the Future Manufacturing is another industry that has seen a significant impact from AI. Intelligent automation, powered by AI, is streamlining production processes, reducing waste, and increasing efficiency. AI-driven robots and systems are capable of handling complex tasks that require precision and consistency, allowing human workers to focus on more strategic and creative roles. The leaders driving AI in manufacturing are ensuring that the industry remains competitive in a global market where speed and innovation are key. The influence of AI extends far beyond the industries it directly impacts. It is reshaping society as a whole, changing the way we live, work, and interact with each other. AI has the potential to solve some of the most pressing challenges of our time, from climate change to healthcare access. However, it also raises important questions about the future of work, the role of humans in an AI-driven world, and the potential for social and economic disruption. The Rise of AI in Modern Industries AI's journey from concept to reality has been remarkable. What was once the stuff of science fiction is now a critical component of modern industry. From healthcare to finance, manufacturing to media, AI is at Innovative AI leaders are at the forefront of these discussions, exploring how AI can be harnessed to create a better future for all. They are investing in education and training programs to ensure that the workforce is prepared for the changes that AI will bring. They are also exploring ways to use AI to address global challenges, such as improving access to healthcare, reducing carbon emissions, and enhancing food security. In the entertainment and media sectors, AI is redefining how content is created, distributed, and consumed. AI technologies that understand and predict audience preferences are transforming the media landscape, from personalized recommendations on streaming platforms to AI-generated content. Leaders in this space are not just keeping up with trends—they are setting them, creating new forms of entertainment that engage and inspire audiences in unprecedented ways. As we look to the future, it is clear that AI will play an increasingly important role in our lives. The leaders who are driving AI innovation today are laying the foundation for a future where technology and humanity work together to solve the challenges of tomorrow. They are not just shaping the future of AI; they are shaping the future of society itself. The Role of AI Leaders in Driving Innovation Behind every significant advancement in AI is a leader or a team of leaders who are pushing the boundaries of what this technology can achieve. These individuals and organizations are not just technologists; they are visionaries 28

29. who understand the profound implications of AI and are committed to harnessing its power for the greater good. the forefront of innovation, enabling businesses to achieve levels of efficiency, accuracy, and personalization that were previously unimaginable. One of the key characteristics of these leaders is their ability to anticipate and respond to the challenges and opportunities that AI presents. They are not content with simply applying existing technologies; they are constantly looking for ways to innovate and push the envelope. This often involves a willingness to take risks, explore uncharted territories, and challenge the status quo. In healthcare, AI has become an invaluable tool in diagnostics, treatment planning, and drug discovery. AI algorithms can analyze complex medical data, identify patterns, and suggest treatment options with a level of precision that far exceeds human capabilities. Innovative leaders in this field are pushing the boundaries of what AI can do, exploring its potential to revolutionize patient care, reduce healthcare costs, and improve outcomes. Another defining trait of AI leaders is their focus on ethical considerations. As AI becomes more integrated into our daily lives, concerns about privacy, bias, and the potential for misuse have come to the forefront. Innovative AI leaders are addressing these issues head-on, developing frameworks and guidelines that ensure AI is used responsibly and ethically. They are advocating for transparency, accountability, and fairness in AI systems, recognizing that the long-term success of AI depends on public trust and acceptance. In the financial sector, AI is transforming how businesses manage risk, detect fraud, and make investment decisions. The ability to process vast amounts of data in real-time allows AI to offer insights that were previously unattainable. This has led to more secure, transparent, and efficient financial systems. Leaders in AI-driven finance are developing sophisticated tools that not only enhance security and compliance but also open up new avenues for growth and innovation. AI's Impact on Society and the Future Manufacturing is another industry that has seen a significant impact from AI. Intelligent automation, powered by AI, is streamlining production processes, reducing waste, and increasing efficiency. AI-driven robots and systems are capable of handling complex tasks that require precision and consistency, allowing human workers to focus on more strategic and creative roles. The leaders driving AI in manufacturing are ensuring that the industry remains competitive in a global market where speed and innovation are key. The influence of AI extends far beyond the industries it directly impacts. It is reshaping society as a whole, changing the way we live, work, and interact with each other. AI has the potential to solve some of the most pressing challenges of our time, from climate change to healthcare access. However, it also raises important questions about the future of work, the role of humans in an AI-driven world, and the potential for social and economic disruption. Innovative AI leaders are at the forefront of these discussions, exploring how AI can be harnessed to create a better future for all. They are investing in education and training programs to ensure that the workforce is prepared for the changes that AI will bring. They are also exploring ways to use AI to address global challenges, such as improving access to healthcare, reducing carbon emissions, and enhancing food security. In the entertainment and media sectors, AI is redefining how content is created, distributed, and consumed. AI technologies that understand and predict audience preferences are transforming the media landscape, from personalized recommendations on streaming platforms to AI-generated content. Leaders in this space are not just keeping up with trends—they are setting them, creating new forms of entertainment that engage and inspire audiences in unprecedented ways. As we look to the future, it is clear that AI will play an increasingly important role in our lives. The leaders who are driving AI innovation today are laying the foundation for a future where technology and humanity work together to solve the challenges of tomorrow. They are not just shaping the future of AI; they are shaping the future of society itself. The Role of AI Leaders in Driving Innovation Behind every significant advancement in AI is a leader or a team of leaders who are pushing the boundaries of what this technology can achieve. These individuals and organizations are not just technologists; they are visionaries 29 www.ciobusinessworld.com

30. CXO The Evolution And Distinction Of AGV And AMR Concepts In Mobile Robotics M concepts of mobile robotics. Therefore, we will discuss the concepts of AGV and AMR , even though this is a complex topic due to the rich history and evolution of mobile robotics. subsequently spreading to other industries such as FMCG (Fast Moving Consumer Goods: Food, Beverage, Pharma, Cosmetics, etc.), Equipment, and later, significantly, eCommerce. The only distinction that most people (about 90%) might agree on is that AMRs typically use SLAM localization, while AGVs use other localization technologies. Beyond that, the features vary depending on who you ask. Personally, I still tend to use the term AGV frequently. However, I am increasingly trying to adopt the terms “mobile robot” or simply “robot” to avoid confusion among customers and suppliers alike. 2. An increase in supply: new players began emerging worldwide, especially in China and Europe. In conclusion, understanding the current landscape of mobile robotics involves recognizing the historical and technological evolution that has led to the diverse terminology we see today. While the acronyms AGV and AMR represent different aspects of mobile robotics, the core concepts often overlap. Therefore, it is essential to focus on the specific features and capabilities of each solution rather than getting too caught up in the terminology. By doing so, we can better navigate the complexities of this ever-evolving industry. any have expressed confusion about the distinctions between AGV (Automated Guided Vehicle) and AMR (Autonomous Mobile Robot) and have requested a clarifying article to organise the various In this environment, established companies in the sector chose not to invest in studying new technologies. Instead, they leveraged the falling prices of technological components. This strategy enabled them to boost sales while also increasing profit margins, creating a comfortable position for them. Let me clarify, the purpose of this article is not to establish the definitive differences between AGVs and AMRs. Instead, it aims to provide an understanding of the current context regarding these acronyms and how to navigate them. Conversely, newcomers needed to differentiate themselves to enter the market. They capitalized on the new technologies, particularly SLAM localization. Some have pointed out the differences from existing AGVs and introduced new acronyms: AMR (Autonomous Mobile Robot), IAV (Intelligent Autonomous Vehicle), SAV (Smart Autonomous Vehicle), among others. Ultimately, AMR became the most widely adopted new term. When I entered this industry in 2013, the terms AGV and AGC (Automated Guided Cart, generally referring to mouse-type vehicles) were predominantly used. Occasionally, a client might use the term robot (though we seldom did within the sector). It's crucial to note that even back then, mobile robots existed that didn’t rely on ground lines and had flexible paths (e.g., those by Seegrid). Nevertheless, at that time, we categorized every mobile robot as an AGV. So, how did we reach our current state? What has transpired along the way? Primarily, two significant developments occurred: 1. The prices of technological components required for AGVs began to drop rapidly. 2. The advent of new technologies drastically enhanced the quality of solutions: lithium batteries, advanced safety lasers, safety PLCs, traction systems designed specifically for AGVs, and most notably, new localization solutions (distinct from navigation). In particular, 2D SLAM localization, also known as natural localization, mapping, or contour-based localization, made a significant impact. The reduction in component prices had two major effects: 1. An increase in demand, initially within the automotive sector and What’s the issue here? Each newcomer attributed different features to the AMR acronym based on their own robot's characteristics. This inconsistency is why there is still no clear consensus on the differences between AGVs and AMRs. 30

31. subsequently spreading to other industries such as FMCG (Fast Moving Consumer Goods: Food, Beverage, Pharma, Cosmetics, etc.), Equipment, and later, significantly, eCommerce. The only distinction that most people (about 90%) might agree on is that AMRs typically use SLAM localization, while AGVs use other localization technologies. Beyond that, the features vary depending on who you ask. Personally, I still tend to use the term AGV frequently. However, I am increasingly trying to adopt the terms “mobile robot” or simply “robot” to avoid confusion among customers and suppliers alike. 2. An increase in supply: new players began emerging worldwide, especially in China and Europe. In conclusion, understanding the current landscape of mobile robotics involves recognizing the historical and technological evolution that has led to the diverse terminology we see today. While the acronyms AGV and AMR represent different aspects of mobile robotics, the core concepts often overlap. Therefore, it is essential to focus on the specific features and capabilities of each solution rather than getting too caught up in the terminology. By doing so, we can better navigate the complexities of this ever-evolving industry. In this environment, established companies in the sector chose not to invest in studying new technologies. Instead, they leveraged the falling prices of technological components. This strategy enabled them to boost sales while also increasing profit margins, creating a comfortable position for them. Conversely, newcomers needed to differentiate themselves to enter the market. They capitalized on the new technologies, particularly SLAM localization. Some have pointed out the differences from existing AGVs and introduced new acronyms: AMR (Autonomous Mobile Robot), IAV (Intelligent Autonomous Vehicle), SAV (Smart Autonomous Vehicle), among others. Ultimately, AMR became the most widely adopted new term. What’s the issue here? Each newcomer attributed different features to the AMR acronym based on their own robot's characteristics. This inconsistency is why there is still no clear consensus on the differences between AGVs and AMRs. 31 www.ciobusinessworld.com

32. subsequently spreading to other industries such as FMCG (Fast Moving Consumer Goods: Food, Beverage, Pharma, Cosmetics, etc.), Equipment, and later, significantly, eCommerce. The only distinction that most people (about 90%) might agree on is that AMRs typically use SLAM localization, while AGVs use other localization technologies. Beyond that, the features vary depending on who you ask. Personally, I still tend to use the term AGV frequently. However, I am increasingly trying to adopt the terms “mobile robot” or simply “robot” to avoid confusion among customers and suppliers alike. 2. An increase in supply: new players began emerging worldwide, especially in China and Europe. In conclusion, understanding the current landscape of mobile robotics involves recognizing the historical and technological evolution that has led to the diverse terminology we see today. While the acronyms AGV and AMR represent different aspects of mobile robotics, the core concepts often overlap. Therefore, it is essential to focus on the specific features and capabilities of each solution rather than getting too caught up in the terminology. By doing so, we can better navigate the complexities of this ever-evolving industry. In this environment, established companies in the sector chose not to invest in studying new technologies. Instead, they leveraged the falling prices of technological components. This strategy enabled them to boost sales while also increasing profit margins, creating a comfortable position for them. Conversely, newcomers needed to differentiate themselves to enter the market. They capitalized on the new technologies, particularly SLAM localization. Some have pointed out the differences from existing AGVs and introduced new acronyms: AMR (Autonomous Mobile Robot), IAV (Intelligent Autonomous Vehicle), SAV (Smart Autonomous Vehicle), among others. Ultimately, AMR became the most widely adopted new term. What’s the issue here? Each newcomer attributed different features to the AMR acronym based on their own robot's characteristics. This inconsistency is why there is still no clear consensus on the differences between AGVs and AMRs. 32

34. The impact of Middle East AI on the enterprise sector with a focus on the growth, and bringing innovative technology solutions to the market, Mohamed Shatla is a seasoned executive with over 20 years of experience in the technology and telecommunications sectors. He has a proven track record of driving business transformation and leading large-scale international programmes. An expert in digital product development, strategic sales for our clients. One of our core specialisations is in Salesforce AI. We harness the power of Salesforce's AI capabilities, including EinsteinGPT, to create intelligent, data-driven solutions that empower businesses to optimise their operations, enhance customer engagement, and drive growth. It is essential always to preserve industry focus. As such, as an IT consultancy firm, not only do we customise solutions for specific needs, but we also guide our customers on prevailing trends within their market, ensuring that our development goes beyond tactical fixes to achieve long-lasting, future-proof impact. Throughout his career, Mohamed has held key leadership roles in both multinational corporations and high-growth enterprises, culminating in a tenfold increase in sales revenue and robust local brand recognition. His ability to navigate complex challenges, foster collaboration, and deliver exceptional results has positioned him as a trusted leader in the industry. He also holds a Master's degree in Technology Management, and is enthusiastic about R&D activities and new product development. In addition to our work with Salesforce AI, we take great pride in being regional pioneers in developing and deploying sovereign AI solutions, powered by SambaNova. This involves creating enterprise-wide models with advanced control over data security. With SambaNova, the model becomes the sole property of the customer, which is essential in safeguarding intellectual property and ensuring regulatory compliance. This approach allows our clients to maintain full control over their AI initiatives, aligning perfectly with the stringent demands of their industries and regions. As an angel investor and strategic thinker, Mohamed is committed to nurturing start-ups, mentoring emerging leaders, and contributing his expertise in digital transformation. As the Managing Partner at CloudingAI, Mohamed is passionate about harnessing the power of AI and cloud technologies to drive innovation and growth for evolving technological businesses in the region. How have businesses in the Middle East been adopting AI technologies compared to other regions? Tell us more about your company and the area of AI technology you specialise in. AI spending in the region is growing rapidly. As forecasted by IDC, AI spending in the Middle East and Africa is expected to witness a significant increase, with a projected compound annual growth rate (CAGR) of 29.7% through At CloudingAI, our primary focus is on leveraging advanced AI technologies to drive transformative outcomes 2026, ultimately reaching $6.4 billion. This makes the Middle East one of the fastest-growing regions globally in terms of AI investment. to change. We are in discussions with several state-owned organizations regarding the development of dedicated AI centres for local use. This initiative will enable SMEs to develop cloud-based AI models based on local fully compliant infrastructure. According to a 2023 survey by McKinsey, 62% of respondents in GCC report using AI in at least one business function in their organisations, with a significant lead by the retail and consumer goods sector. The power of AI- supported data mining to gain consumer insights is a significant driving force for its adoption in marketing strategies and decision-making. Which trends will define the development of AI in the near future? One of the most significant trends is the increasing emphasis on AI governance and ethical AI. As AI technologies become more pervasive, ensuring that they are used responsibly and ethically will be crucial. This includes developing frameworks for transparency, accountability, and bias reduction. The 2023 survey by McKinsey also revealed that 30% of the companies already have a clearly defined AI strategy and 35% of the companies have the technology infrastructure to support AI. As such, it has been identified that increasing AI adoption in the region requires support from senior leadership, linking the AI strategy to enterprise strategy, investing in AI talent, and making analytics user- friendly. Another trend is the convergence of AI with other emerging technologies like quantum computing, blockchain, and edge computing. This integration will unlock new capabilities, enabling more powerful, secure, and efficient AI solutions. What is the current stance on AI regulation, and what are the latest advances in the Middle East? AI-driven automation will continue to expand, particularly in industries such as healthcare, finance, and manufacturing. This trend is driven by the need for increased efficiency and the ability to process and analyse large datasets in real-time, leading to more informed decision-making. Several GCC countries have already created a regulatory ecosystem for the safe and ethical development of AI. For example, in the UAE, AI regulation is primarily overseen by the Ministry of Artificial Intelligence, the Telecommunications and Digital Government Regulatory Authority (TDRA), and the National Cybersecurity Council, which focuses on ensuring ethical use, data protection, and cybersecurity. In Saudi Arabia, this area falls under the realm of the Saudi Data and Artificial Intelligence Authority (SDAIA), which is further supported by the National Cybersecurity Authority (NCA) and the Ministry of Communications and Information Technology (MCIT). Moreover, personalized AI experiences will become more prevalent as businesses strive to offer highly tailored services to their customers. AI will play a critical role in understanding consumer behaviour and preferences, leading to more engaging and relevant user experiences. What advice would you give to business leaders who are considering integrating AI into their operations? It's crucial to align AI initiatives with your core business objectives. Start by identifying specific business problems that AI can solve. This alignment not only clarifies the purpose of AI within your organization, but also helps to measure its impact. It's important to involve key stakeholders early in the process to map out internal processes and ensure a future-proof data pipeline. Mohamed Shatla Managing Partner Clouding AI The introduction of sovereign AI systems will play a critical role in this context. By keeping AI development within the country, GCC nations can mitigate risks associated with international data breaches and cyber-attacks. State authorities can require system operators to pre-configure their servers in accordance with their regulations, ensuring that any development within this ecosystem will be compliant by default. As the ancient Romans would say, “Make haste slowly.” AI is here to stay. Hence, any such initiatives should be made with a must-have ramp-up plan for the near future. Currently, sovereign AI primarily benefits large enterprises that can afford on-site infrastructure. However, this is about 34

35. The impact of Middle East CXO AI on the enterprise 2026, ultimately reaching $6.4 billion. This makes the Middle East one of the fastest-growing regions globally in terms of AI investment. to change. We are in discussions with several state-owned organizations regarding the development of dedicated AI centres for local use. This initiative will enable SMEs to develop cloud-based AI models based on local fully compliant infrastructure. sector with a focus on the growth, and bringing innovative technology solutions to the market, Mohamed Shatla is a seasoned executive with over 20 years of experience in the technology and telecommunications sectors. He has a proven track record of driving business transformation and leading large-scale international programmes. According to a 2023 survey by McKinsey, 62% of respondents in GCC report using AI in at least one business function in their organisations, with a significant lead by the retail and consumer goods sector. The power of AI- supported data mining to gain consumer insights is a significant driving force for its adoption in marketing strategies and decision-making. Which trends will define the development of AI in the near future? One of the most significant trends is the increasing emphasis on AI governance and ethical AI. As AI technologies become more pervasive, ensuring that they are used responsibly and ethically will be crucial. This includes developing frameworks for transparency, accountability, and bias reduction. The 2023 survey by McKinsey also revealed that 30% of the companies already have a clearly defined AI strategy and 35% of the companies have the technology infrastructure to support AI. As such, it has been identified that increasing AI adoption in the region requires support from senior leadership, linking the AI strategy to enterprise strategy, investing in AI talent, and making analytics user- friendly. Another trend is the convergence of AI with other emerging technologies like quantum computing, blockchain, and edge computing. This integration will unlock new capabilities, enabling more powerful, secure, and efficient AI solutions. What is the current stance on AI regulation, and what are the latest advances in the Middle East? AI-driven automation will continue to expand, particularly in industries such as healthcare, finance, and manufacturing. This trend is driven by the need for increased efficiency and the ability to process and analyse large datasets in real-time, leading to more informed decision-making. An expert in digital product development, strategic sales for our clients. One of our core specialisations is in Salesforce AI. We harness the power of Salesforce's AI capabilities, including EinsteinGPT, to create intelligent, data-driven solutions that empower businesses to optimise their operations, enhance customer engagement, and drive growth. It is essential always to preserve industry focus. As such, as an IT consultancy firm, not only do we customise solutions for specific needs, but we also guide our customers on prevailing trends within their market, ensuring that our development goes beyond tactical fixes to achieve long-lasting, future-proof impact. Several GCC countries have already created a regulatory ecosystem for the safe and ethical development of AI. For example, in the UAE, AI regulation is primarily overseen by the Ministry of Artificial Intelligence, the Telecommunications and Digital Government Regulatory Authority (TDRA), and the National Cybersecurity Council, which focuses on ensuring ethical use, data protection, and cybersecurity. In Saudi Arabia, this area falls under the realm of the Saudi Data and Artificial Intelligence Authority (SDAIA), which is further supported by the National Cybersecurity Authority (NCA) and the Ministry of Communications and Information Technology (MCIT). Moreover, personalized AI experiences will become more prevalent as businesses strive to offer highly tailored services to their customers. AI will play a critical role in understanding consumer behaviour and preferences, leading to more engaging and relevant user experiences. Throughout his career, Mohamed has held key leadership roles in both multinational corporations and high-growth enterprises, culminating in a tenfold increase in sales revenue and robust local brand recognition. His ability to navigate complex challenges, foster collaboration, and deliver exceptional results has positioned him as a trusted leader in the industry. He also holds a Master's degree in Technology Management, and is enthusiastic about R&D activities and new product development. What advice would you give to business leaders who are considering integrating AI into their operations? In addition to our work with Salesforce AI, we take great pride in being regional pioneers in developing and deploying sovereign AI solutions, powered by SambaNova. This involves creating enterprise-wide models with advanced control over data security. With SambaNova, the model becomes the sole property of the customer, which is essential in safeguarding intellectual property and ensuring regulatory compliance. This approach allows our clients to maintain full control over their AI initiatives, aligning perfectly with the stringent demands of their industries and regions. It's crucial to align AI initiatives with your core business objectives. Start by identifying specific business problems that AI can solve. This alignment not only clarifies the purpose of AI within your organization, but also helps to measure its impact. It's important to involve key stakeholders early in the process to map out internal processes and ensure a future-proof data pipeline. The introduction of sovereign AI systems will play a critical role in this context. By keeping AI development within the country, GCC nations can mitigate risks associated with international data breaches and cyber-attacks. State authorities can require system operators to pre-configure their servers in accordance with their regulations, ensuring that any development within this ecosystem will be compliant by default. As an angel investor and strategic thinker, Mohamed is committed to nurturing start-ups, mentoring emerging leaders, and contributing his expertise in digital transformation. As the Managing Partner at CloudingAI, Mohamed is passionate about harnessing the power of AI and cloud technologies to drive innovation and growth for evolving technological businesses in the region. As the ancient Romans would say, “Make haste slowly.” AI is here to stay. Hence, any such initiatives should be made with a must-have ramp-up plan for the near future. How have businesses in the Middle East been adopting AI technologies compared to other regions? Currently, sovereign AI primarily benefits large enterprises that can afford on-site infrastructure. However, this is about Tell us more about your company and the area of AI technology you specialise in. AI spending in the region is growing rapidly. As forecasted by IDC, AI spending in the Middle East and Africa is expected to witness a significant increase, with a projected compound annual growth rate (CAGR) of 29.7% through At CloudingAI, our primary focus is on leveraging advanced AI technologies to drive transformative outcomes 35 www.ciobusinessworld.com

36. 2026, ultimately reaching $6.4 billion. This makes the Middle East one of the fastest-growing regions globally in terms of AI investment. to change. We are in discussions with several state-owned organizations regarding the development of dedicated AI centres for local use. This initiative will enable SMEs to develop cloud-based AI models based on local fully compliant infrastructure. According to a 2023 survey by McKinsey, 62% of respondents in GCC report using AI in at least one business function in their organisations, with a significant lead by the retail and consumer goods sector. The power of AI- supported data mining to gain consumer insights is a significant driving force for its adoption in marketing strategies and decision-making. Which trends will define the development of AI in the near future? One of the most significant trends is the increasing emphasis on AI governance and ethical AI. As AI technologies become more pervasive, ensuring that they are used responsibly and ethically will be crucial. This includes developing frameworks for transparency, accountability, and bias reduction. The 2023 survey by McKinsey also revealed that 30% of the companies already have a clearly defined AI strategy and 35% of the companies have the technology infrastructure to support AI. As such, it has been identified that increasing AI adoption in the region requires support from senior leadership, linking the AI strategy to enterprise strategy, investing in AI talent, and making analytics user- friendly. Another trend is the convergence of AI with other emerging technologies like quantum computing, blockchain, and edge computing. This integration will unlock new capabilities, enabling more powerful, secure, and efficient AI solutions. What is the current stance on AI regulation, and what are the latest advances in the Middle East? AI-driven automation will continue to expand, particularly in industries such as healthcare, finance, and manufacturing. This trend is driven by the need for increased efficiency and the ability to process and analyse large datasets in real-time, leading to more informed decision-making. Several GCC countries have already created a regulatory ecosystem for the safe and ethical development of AI. For example, in the UAE, AI regulation is primarily overseen by the Ministry of Artificial Intelligence, the Telecommunications and Digital Government Regulatory Authority (TDRA), and the National Cybersecurity Council, which focuses on ensuring ethical use, data protection, and cybersecurity. In Saudi Arabia, this area falls under the realm of the Saudi Data and Artificial Intelligence Authority (SDAIA), which is further supported by the National Cybersecurity Authority (NCA) and the Ministry of Communications and Information Technology (MCIT). Moreover, personalized AI experiences will become more prevalent as businesses strive to offer highly tailored services to their customers. AI will play a critical role in understanding consumer behaviour and preferences, leading to more engaging and relevant user experiences. What advice would you give to business leaders who are considering integrating AI into their operations? It's crucial to align AI initiatives with your core business objectives. Start by identifying specific business problems that AI can solve. This alignment not only clarifies the purpose of AI within your organization, but also helps to measure its impact. It's important to involve key stakeholders early in the process to map out internal processes and ensure a future-proof data pipeline. The introduction of sovereign AI systems will play a critical role in this context. By keeping AI development within the country, GCC nations can mitigate risks associated with international data breaches and cyber-attacks. State authorities can require system operators to pre-configure their servers in accordance with their regulations, ensuring that any development within this ecosystem will be compliant by default. As the ancient Romans would say, “Make haste slowly.” AI is here to stay. Hence, any such initiatives should be made with a must-have ramp-up plan for the near future. Currently, sovereign AI primarily benefits large enterprises that can afford on-site infrastructure. However, this is about 36

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