There’s now so much information available on the adoption of artificial intelligence (AI) in IT service management (ITSM) that it can be hard to know where other organizations are in their AI “journeys.” A little like the oft-used phrase “We use ITIL,” the statement “We’ve adopted AI” can mean so much and so little at the same time. So this article aims to provide you with a “temperature check” of AI in ITSM based on a recorded webinar with HCLSoftware and the creation of a new survey-based AI in ITSM report (a link to the finalized survey report was shared in this article). Here are four key points about the 2025 state of AI in ITSM that will hopefully help with your organization’s future AI approaches and use cases.
1. Understand the “why” of AI in ITSM
As stated in the webinar, I have two perspectives on the need for AI in ITSM.
The first is somewhat internal – meeting the many challenges IT organizations face with new capabilities needed to help address them. Every IT organization likely has its own challenges. Still, we can see a lot of similarities based on the data captured from the aforementioned AI in ITSM survey.
In this, the top three challenges reported by respondents in the AI in ITSM survey (who could choose their top three challenges) were:
- Automating repetitive tasks to improve efficiency (45%, joint first)
- Enhancing user experience (45%, joint first)
- Aligning ITSM with business objectives (34%).
If you’re wondering about costs, “Balancing cost-efficiency with service quality” was in fourth place in the AI in ITSM survey at 30%.
The second perspective is the need for competitive advantage, or the reverse – avoiding competitive disadvantage. You must have the proverbial “skin in the game,” or your organization will be left behind. So, start experimenting as a minimum to avoid being placed at a competitive disadvantage.
2. Recognize that different AI types and their use cases
Keeping up with the different AI-type names and their use cases can be hard, but simply throwing the term “AI” around can confuse things when considering AI in ITSM. It also misses the different AI types and their best use cases. For example, predictive analytics (as the name suggests) is about forecasting for decision-making and action-taking. While generative AI (or GenAI) is good for content creation, and Agentic AI agents undertake actions autonomously.
There are many ITSM use cases for each AI type:
- Predictive analytics – incident trend forecasting (which ties in with proactive problem management), asset issue or failure prediction, change risk assessment, and service level agreement (SLA) breach prediction.
- GenAI – ticket resolution suggestions, automated knowledge article creation, ticket summarization, and GenAI-powered virtual agents that understand context and intent.
- Agentic AI – autonomous incident resolution or service request fulfillment, self-healing systems, and automated workflow agents that can work with people or other agents, such as automated change management or employee onboarding.
3. Understand the difference between virtual agents and AI agents
This is critical when looking at AI in ITSM.
For me, the simplest way to differentiate between virtual agents and AI agents is that virtual agents are focused on end-user interactions – for example, a chatbot that’s the first line of Level 1 IT support. They respond to human prompts.
While AI agents are the AI type called Agentic AI earlier – they’re focused on achieving specific goals through actions. They might not converse with a human in doing so, and they might work with other AI agents to achieve an overall goal. For example, employee onboarding – where different AI agents work together, each focused on their own area of specialism.
4. Be clear about the primary motivation for using AI in ITSM
Going back 10-15 years, everyone was introducing IT self-service portals. However, many IT organizations struggled to realize the expected return on investment (ROI) because user adoption was low. This was often due to the primary motivation for the portal initiatives being cost-saving, with the user experience neglected. Ultimately, if it’s easier to call the IT help desk than use an IT self-service portal, that’s what you’ll do.
Savvy organizations now understand the importance of experience to IT’s success, and the results of our AI in ITSM survey show this, with the top two reported benefits of AI being:
- Increasing employee productivity (32%)
- Improving the end-user experience (20%, joint second)/Better decision-making (20%, joint second).
Cost savings might be important, but focusing primarily on them is probably not the best way to achieve them.
More on these four key AI in ITSM points and other important areas, including some great ITSM tool product management perspectives, are shared in the aforementioned webinar. This can be watched on the Brighttalk webinar platform from December 17 2025, 8:30am GMT (registration is open now).
Further Reading
Stephen Mann
Principal Analyst and Content Director at the ITSM-focused industry analyst firm ITSM.tools. Also an independent IT and IT service management marketing content creator, and a frequent blogger, writer, and presenter on the challenges and opportunities for IT service management professionals.
Previously held positions in IT research and analysis (at IT industry analyst firms Ovum and Forrester and the UK Post Office), IT service management consultancy, enterprise IT service desk and IT service management, IT asset management, innovation and creativity facilitation, project management, finance consultancy, internal audit, and product marketing for a SaaS IT service management technology vendor.
