Global AI in Manufacturing Market Report, Size & Analysis _ BIS Research

1. Global AI in Manufacturing Market Report, Size & Analysis | BIS Research The global AI in manufacturing market is valued at $5.12 billion in 2024 and is expected to grow at a CAGR of 38.46% to reach $132.54 billion by 2034.In the landscape of modern industry, few innovations have been as transformative as Artificial Intelligence (AI). Among the sectors experiencing a significant upheaval due to AI, manufacturing stands out prominently. The integration of AI technologies into manufacturing processes has not only enhanced efficiency but has also unlocked unprecedented potential for innovation, cost reduction, and quality improvement. AI is reshaping the manufacturing landscape by boosting productivity, efficiency, and data-driven decision-making. Automation of tasks through AI-powered robots not only streamlines operations but also enhances workplace safety. By freeing up human workers to focus on more complex activities, AI enables manufacturers to stay competitive in a rapidly evolving global market, paving the way for a more agile and responsive industry. The Current State of AI in Manufacturing: AI has penetrated various facets of manufacturing, revolutionizing operations across the production cycle. From product design and prototyping to supply chain management and predictive maintenance, AI-powered solutions are reshaping the industry. Machine learning algorithms analyze vast amounts of data to optimize production processes, predict equipment

2. failures, and streamline logistics, leading to reduced downtime and enhanced productivity. Robotics and automation, fueled by AI, have ushered in an era of smart factories, where machines work in tandem with human operators, augmenting capabilities and driving operational excellence. Despite these positive drivers, the market faces hurdles such as skilled workforce availability, particularly in developing nations. However, leveraging AI, machine learning, and natural language processing (NLP) for smart enterprise processes presents lucrative opportunities for the expansion of AI in manufacturing sector. With AI and big data analytics, companies can swiftly analyze extensive structured and unstructured data from diverse sources. This enables them to identify anomalies, reduce maintenance expenses, enhance customer service, implement predictive and preventive maintenance measures, and leverage raw data for informed decision-making. The AI in manufacturing market in the North America region is experiencing significant growth. Many countries in the North America region, including the U.S., Canada, and Mexico, have implemented policies and incentives to promote the adoption of AI. These policies typically include subsidies, tax incentives, and regulatory measures aimed at reducing emissions and promoting sustainable transportation solutions. Request A Free Detailed Sample for the AI in Manufacturing Market Market Segmentation: Segmentation 1: by End-Use Industry • Automotive • Medical Devices • Electronics • Energy and Power • Heavy Metals and Machine Manufacturing • Aerospace and Defense • Others Segmentation 2: by Application • Assembly/Quality Testing • Product Development and Engineering • Procurement • Order Management • Maintenance • Logistics and Inventory Management • Others Segmentation 3: by Component • Software

3. • • Hardware Service Segmentation 4: by Technology • Machine Learning • Computer Vision • Natural Language Processing (NLP) • Others Segmentation 5: by Region • North America • Europe • Asia-Pacific • Rest-of-the-World Key Market Players and Competition Synopsis The companies that are profiled in the global AI in manufacturing market have been selected based on input gathered from primary experts and analyzing company coverage, product portfolio, and market penetration. Some of the prominent companies in this market are: • IBM • Microsoft • Siemens • Nvidia Corporation • Google LLC Key Applications of AI in Manufacturing: Predictive Maintenance: AI algorithms analyze sensor data to predict equipment failures before they occur, enabling proactive maintenance and minimizing downtime. Quality Control: Computer vision systems powered by AI inspect products for defects with unparalleled accuracy, ensuring adherence to quality standards. Supply Chain Optimization: AI optimizes inventory management, demand forecasting, and logistics routing, leading to efficient supply chain operations and cost savings. Process Optimization: AI algorithms optimize production processes by identifying inefficiencies, reducing waste, and enhancing throughput.

4. Product Design and Prototyping: Generative design algorithms leverage AI to explore countless design permutations, leading to innovative product designs optimized for performance and manufacturability. The Future of AI in Manufacturing: The future of AI in manufacturing holds immense promise, with continued advancements poised to further transform the industry. AI-powered autonomous factories, equipped with self-learning systems capable of continuous improvement, will redefine the notion of manufacturing agility and responsiveness. Collaborative robots, enhanced by AI, will work seamlessly alongside human operators, augmenting human capabilities and unlocking new levels of productivity. The convergence of AI with other transformative technologies such as 5G, IoT, and additive manufacturing will accelerate innovation and drive the emergence of entirely new business models and value chains. Conclusion: As AI continues to permeate every aspect of manufacturing, the industry stands on the brink of a profound transformation. From predictive maintenance and quality control to supply chain optimization and autonomous manufacturing, the applications of AI are reshaping the manufacturing landscape, driving efficiency, innovation, and competitiveness. Embracing AI-powered solutions is no longer a choice but a necessity for manufacturers looking to thrive in the digital age. As we navigate this era of unprecedented change, the integration of AI in manufacturing will be a defining factor in shaping the factories of tomorrow.