Earlier this year, I predicted that Artificial intelligence (AI) would move from innovation labs to mainstream workflow projects this year. In IT organizations, I believe service management teams will lead this trend. Here’s why.

Barriers to AI

A few years ago, I attended an IT Service Management (ITSM) conference. I sat in on a couple of speaking sessions billed as AI. But really, what I heard were service management automation presentations. To be frank, some vendors have added to the confusion around what AI is and how it can help IT organizations. Gartner highlighted other barriers to AI adoption by IT in one of their blogs:

  • Barriers to skills – acquisition of new skills are required
  • Fears of the unknown – including understanding the tangible and intangible benefits
  • Finding a start point – finding use cases and defining a strategy

I believe all these factors contribute to why AI has been slow to go mainstream until now. Organizations had yet to figure out the value that AI could bring and justify budgets. Projects were confined to research labs until that value was revealed and could be justified to executive teams.

AI Use Cases Revealed

But there has been a marked increase in the adoption of AI in the last few years. According to the 2019 CIO survey results published by Gartner, between 2015 and 2019, AI implementations reportedly grew 270%. From 10% in 2015 to 37%. By the beginning of 2019, 37% of those surveyed had implemented AI in some form or another. Add to that a prediction by Forrester based on their research. They predict that in 2020 companies will be laser-focused on the value of AI, accelerate adoption, and overcome data issues. It becomes clear that the importance of AI is recognized.

How does that relate to Enterprise Service Management (ESM)? Enterprise Management Associates (EMA) analyst organization researched the primary use cases for AI. They found that 70% were focused on integrated operations (availability, change management, performance), self-service, routine service desk processes (incident, problem, request), ESM, and major incident response. To put this into perspective, the research found 6% of use cases were focused on SecOps, 3% Internet of Things, 8% DevOps, 15% integrated asset and financial planning (in many organizations, I see this banded under ITSM and ESM).

The CIOs questioned in Gartner’s survey mentioned previously also identified chatbots as the main AI-based application in their enterprises. Chatbots is one of the main areas of adoption that I see in our own customer base to provide better experiences for end-users. Vendor developments also fuel this adoption. IDC found that chatbots, knowledge curation, and incident/request routing were the three big categories of AI features and capabilities that vendors were working on in helpdesk software.

Automation Synergies

EMA’s research also discovered synergies between automation and artificial intelligence. The value of automation is now widely recognized. The same survey highlighted that 67% of organizations were automating simple to complex tasks already. Only 4% had no plans to automate. Since AI recommendations drive automation, this also supports the premise that AI is finally going into mainstream projects.

If you intend to take your project out of the lab and into production, then there are things you need to consider. I’ll wrap up with EMA’s top two recommendations from those surveyed:

  1. Educate users ahead of time
  2. Prepare for the change in your IT team and understand process changes and impacts.

My prediction and others from my colleagues are available to hear in full on in this recorded webcast, The Future of Enterprise Service Management.