HOW WILL MACHINE LEARNING BE USED IN ENTERPRISESOFTWARE, PARTICULARLY ITSM PRACTICES

1. HOW WILL MACHINE LEARNING BE USED IN ENTERPRISESOFTWARE, PARTICULARLY ITSM PRACTICES? Throughout the years, CIOs have overinvested in optimizing the value chain: better ticketing software, expansive call-routing processes, and outsourcing to lower-cost geographies and process-centric metrics -- all with mixed results. As more and more services are offered and exposed to business units and employees through Service Catalogs, Service Desks have become inundated by queries, complaints, and calls for assistance. This can make for a significant drain on a company’s resources and productivity. With the advent of AI and Information Technologies, ITSM for cloud can now evolve into more automated, data-driven conversational experience ITSM, known as ITSM, by overlaying AI Service Desk platforms which promise a trifecta of disruptive possibilities to today’s ITSM: Self-resolve repetitive requests–knowledge serving and tasks/processes automation · Compress organizational hierarchies and accelerate decision-making · Deliver exceptional user experiences AI Service needs to ingest, parse, and normalize different data formats from a variety of data sources, systems, and enterprise domains into a canonical form that can be used to extract actionable knowledge. AI is required to deeply understand the semantics behind the acquired

2. data, modelling, and enriching the available sources of experience in a flexible and scalable way, as well as designing smart solutions to overcome knowledge gaps and to adapt the current models to specific contexts. AI Service engages directly with users in human-like conversations with Conversational AI Virtual Assistants. The aim is to improve user experience, making the offered service interactive, personalized, and user-friendly. Users can pose arbitrary questions without any predefined schema, while responses are tailored to the current conversation context and user expectations. To enable such experience, the underpinning layers need to successfully address the correct interpretation of requests which requires a deep understanding of the context behind such an inquiry, identify the appropriate resources, and formulate the corresponding answers in natural language. In a nutshell, the new AI encompasses a disruptive delivery service for today’s Service Desks, providing the following advanced functions: · Ingestion and ignition of multimodal data acquired from both internal and external sources · Accurate modelling and logical organization of the knowledge pertinent to the primary service scope · In-depth analysis and dynamic contextualization of user requests, with particular attention paid to the profile and context of the requester user. · Effective retrieval of the related content based on the exploration of multi-domain knowledge bases. · Automated tasks and process execution directly from unstructured conversations with users · On-the-fly generation of non-robotic responses in natural language. · Automated identification of knowledge gaps (understanding and fulfilment) and model self- tuning.