IT service management (ITSM) and wider IT adoption of AI capabilities have been a long time coming
Believe it or not, progressive enterprises were looking at the early opportunities of enterprise AI use a quarter of a century ago. However, this was more likely from a “watching brief” perspective rather than real-world use cases.
The IT industry, including the ITSM community, has had a more practical view of AI opportunities for closer to a decade. In ITSM circles, these opportunities started to receive significant interest, and ITSM tool vendors added AI-based capabilities to their offerings. Then 2023 happened, and generative AI (gen AI) became the hottest ITSM trend by a long margin.
2023 and the breakout of generative AI
In 2023, the world (and not just the IT world) woke up to the opportunity of AI. Thanks to the media buzz around ChatGPT. However, it wasn’t simply a technology “buy-in” but a “perfect storm” of AI usability, accessibility, and viral adoption. Even company board members became aware of gen AI’s opportunities thanks to ChatGPT’s media coverage and “word-of-mouth” success.
You might think that this detour into ChatGPT’s success has nothing to do with what AI adoption in ITSM looks like in 2024, but it does. Unlike any other ITSM “trend” before it, gen AI has rapidly risen on IT to-do lists. It usurped the work of the ITSM tool vendors focused on the “traditional” AI opportunities based on machine learning and natural language processing (NLP) to be the “easier to use” AI technology.
So, where does this leave AI adoption in ITSM at the end of 2024 and heading into 2025?
ITSM AI adoption in 2024
As mentioned in the previous section, the rise in ITSM gen AI interest and adoption has been unlike any other ITSM trend, including “traditional” AI. If we look back to the end of 2023, survey data from ITSM.tools showed that three-quarters of ITSM tools had added AI capabilities. But this was before the meteoric rise of gen AI.
By the end of 2024, gen AI capabilities had become the “go-to” AI option with popular ITSM tools. Not all ITSM AI opportunities align with ITSM tool capabilities. However, the investments of ITSM tool vendors have made it easier for organizations to take their first steps in adopting AI for ITSM using these solutions.
ITSM AI adoption insights – investment
Research shows that AI initiatives are more likely to originate within the IT organization than the C-suite. However, this somewhat expectedly differs according to organizational size, region, and industry.
Two-thirds of IT organizations have an AI budget allocation – with the smallest of organizations least likely to have an AI budget allocation and the largest organizations likely to have the highest percentage budget allocation. Based on survey data, Europe appears to be most cautious about AI spending.
In terms of return on investment (ROI), it’s still too early for most organizations (two-thirds of organizations) to understand how AI adoption has benefited them.
ITSM AI adoption insights – use cases
Gen AI has not only sped up adoption, but it has also altered the top areas of ITSM AI adoption impact. While AI has always offered both “heavy lifting” and “heavy thinking” improvement opportunities for ITSM, the ease of using gen AI for the latter has elevated data analysis to the top area where AI has impacted ITSM operations. Even ahead of virtual agents and the incident management process.
The top two realized, rather than anticipated, benefits relate to end-users. These are increasing employee productivity and improving user experiences. Followed by optimizing operations, reducing costs, and enabling better decision-making.
Looking ahead to continued ITSM AI adoption in 2025
Late-2024 survey data shows a healthy start to AI adoption in ITSM, with gen AI now driving ITSM use cases. Expect this to continue in 2025.
However, there are still potential barriers to AI (or gen AI) adoption. Governance and compliance have jumped to the top of the list of AI adoption concerns, with customer data security dropping to second place.
Trust in AI is also a potential barrier that will need organizational change management tools and techniques to address the likely resistance to change. However, it’s essential to appreciate the difference between AI used to augment human beings and AI employed without human oversight and input. Trust in AI is growing year-on-year, but it will likely take successful AI use cases within your organization to truly gain buy-in from all parties.
Finally, the motivation for AI adoption in ITSM is vital to understand. The IT industry learned this the hard way with IT self-service portals and the time taken for these investments to get close to delivering a suitable ROI. Cost-reduction strategies often drove these portals, and the initiatives neglected the end-user experience. This mustn’t be repeated with AI adoption, with end-users needing to be front-and-center in AI capability design and delivery.