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AI-driven Enterprise Service Automation: the future of IT

 In Enterprise AI, IT Service Management Blog

In recent years a strong emphasis has been placed on IT moving away from making technology decisions for IT’s sake alone, which many would agree was long overdue.  

As discussed in my previous blog (“Three common practices that help IT earn employee trust“), as enterprises digitally transform business processes, IT must also evolve its technologies and best practices to improve both its efficiency and perception as a driver of digital transformation.

Just as IT staff and business users gain unique and shared benefits from mobile, social and analytic technologies, the same symbiotic relationship applies with AI.  

Now is the time to define your AI strategy

Requesters (employees seeking IT services): employees want fast service that’s available 24/7 across multiple device types and locations. By leveraging AI-based virtual agents with natural language processing (NLP) capabilities, requesters can interactively ask questions, submit incidents and order goods and services, in real-time, with little to no direct contact with IT staff.

Machine learning (ML) models allow virtual agents to be trained and become smarter over time. So, requesters receive increasingly consistent and accurate responses to their help desk inquiries. Additionally, AI systems that present smart suggestions specific to a user’s issue type and location enable requesters to quickly resolve their own issues via self-service.

It’s also essential that requesters have the ability to rate the accuracy of the responses provided by virtual agents as well as notify/involve human agents.

Fulfillers (IT staff providing service and support): the benefits that fulfillers seek from AI driven enterprise service automation center around IT’s need to better scale and optimize its support of an increasingly mobile and global workforce.

Fulfillers benefit from AI technology by gaining fast access to operational data (often from disparate systems of record) such as when, where, and how IT and business services are being accessed and consumed. Surfacing, analyzing and correlating this type of user and IT related information helps fulfillers complete (or “shift left”) complex tasks as well as fully automate common issues like resetting passwords and granting system access.

AI systems that leverage prediction algorithms can also automate the process of identifying the right category and assignment group for tickets, eliminating the need for fulfillers to dedicate valuable time and resources to the mundane task of reviewing and routing tickets.

Managers (service owners, team leads, or execs): managers are responsible for ensuring that workplace technologies are delivering value across the entire organization.

Managers need operational insights that identify ways to improve IT service quality, eliminate expense leaks and drive better business outcomes. AI based technologies enrich decision-making by predicting issues before they occur.

Managers value AI systems that are capable of correlating and displaying valuable IT and business data in the form of interactive dashboards. Surfacing information such as the health of IT services by topic, geography, team and role allows IT to proactively assess future resource requirements, vendor relationships, and budget requirements.

Also essential to managers is the ability to utilize trend analytics to gain insights into how AI-driven automation supports human fulfillers and understand how it is advancing the adoption of employee self-service, reducing support costs and improving customer sat.

Why AI will soon drive all support interactions

AI-driven enterprise service automation not only enables IT departments to better scale and optimize their support functions, it also helps employees get better service faster and creates a productivity dividend for organizations that ultimately improves profitability and delivers a competitive advantage.



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