The speed of artificial intelligence (AI) adoption within IT organizations is now beating most peoples’ expectations. “Generative AI” (GenAI) was the go-to IT service management (ITSM) trend in 2024, with this driven by the success of ChatGPT. This success propelled AI availability and adoption, with ITSM tool vendors quickly adding GenAI-powered capabilities to their offerings. Now, in 2025, “Agentic AI” has come to the fore. However, no matter the “flavor” of AI and its name, successful AI adoption needs experience data. This blog explains why.
What’s Agentic AI?
It can seem tricky to keep up with the changing face of AI. Only a few years ago, the ITSM market was selling “AI capabilities.” Then, it was selling “GenAI capabilities.” Now, it’s “Agentic AI capabilities.” I guess we work in a space where marketing matters. So what’s Agentic AI?
Agentic AI is the name given to AI systems designed to act autonomously, make decisions and take actions to achieve specific goals with minimal human intervention. Unlike “traditional AI,” Agentic AI can adapt, learn, and operate independently (and in dynamic environments).
Agentic AI combines advanced AI capabilities such as machine learning, natural language processing (NLP), and decision-making algorithms to perform complex tasks. For example, automating and managing workflows, solving problems, or interacting with end-users. Not only is it autonomous and adaptable, but it’s also goal-oriented and context-aware.
In some ways, I can’t help but think that what was offered in ITSM tools in 2024 was Agentic AI, but it was still called GenAI as that was the popular term. However, as I’ve already said – no matter the AI type, there’s a need for experience data for successful AI adoption.
How AI and experience data are linked (or should be linked)
If you look at any annual “X Trends for ITSM” article, you’ll likely see both AI and experience management (or better experiences) listed. They’re both ITSM trends in their own right (and have been for half a decade now). However, it’s important to understand the connectivity between the two so that your organization’s investments in both Agentic AI and experience management deliver optimal benefits.
An obvious point to start is that Agentic AI will improve experiences (for both service providers and service receivers). Or at least this is what the marketing states. However, the reality might not be so rosy. After all, how often has your IT organization invested in and delivered new technology capabilities that failed to provide the expected benefits?
Let’s return these skeletons to the closet for now and consider “the other side of the coin” for the relationship between experience data and AI.
A quick sense check of your ITSM (and wider corporate) Agentic AI initiatives
If your IT organization is frantically investing in Agentic AI capabilities for ITSM right now, here are some interesting questions to pose to the people involved:
- What’s the main motivation for the AI investment?
- Is the AI being applied to areas where employees experience the most frustration or delays?
- Has direct employee feedback been gathered to identify the ITSM challenges for AI to solve?
- Will the AI capabilities improve employee productivity by reducing IT-related downtime?
- Do employees feel AI-driven IT support is as good (or better) than human support?
- Do employees trust AI-generated solutions, or do they prefer human support?
- Are employees more or less satisfied with IT services after AI implementation?
There might be some good, bad, and ugly answers given. However, if nothing else, these questions might just save your organization from investing in Agentic AI because it can rather than because it should! The answers to the questions might also overlap somewhat. Still, their intention is very clear – testing whether Agentic AI’s introduction is focused on what improves business operations and outcomes the most.
Another way to view this is whether the new Agentic AI capabilities will improve IT efficiency without significantly improving end-user productivity. It’s the classic “inside-out” issue seen with continual improvement – where investments improve IT but not the parent organization – that must be avoided with Agentic AI adoption.
How experience data and Agentic AI are linked
Agentic AI adoption in ITSM needs a strategic approach to deliver real value, and without clear direction, the AI investments risk being misaligned with actual end-user needs.
Experience data should serve as the connective tissue between ITSM and Agentic AI – identifying pain points, opportunities, and priorities to help ensure your Agentic AI initiatives focus on what truly matters. Examples of where experience data will help with Agentic AI adoption and use include:
- Prioritizing Agentic AI investments using end-user experience data, targeting the areas with the most significant impact. For example, if employees are most concerned about their slow IT service desk engagements, AI-powered automation and recommendations can streamline ticket triage and incident resolution.
- Helping to ensure Agentic AI improves – not degrades – IT experiences. Even when Agentic AI is applied to the right areas, it may unexpectedly adversely impact end-user experiences. For example, an AI-powered chatbot might reduce IT’s workload. However, IT must refine the chatbot’s responses if employees struggle to quickly get the solutions they need.
- Driving Agentic AI adoption and identifying additional training needs. Experience data provides insights into how well your employees are adopting the new Agentic AI capabilities. Your IT organization can use this to pinpoint areas where additional training or support is needed. For example, if AI-chatbot adoption is low, experience data might reveal that your employees lack confidence or trust in the AI-generated solutions.
- Enabling Agentic AI to personalize IT support provision. Agentic AI can deliver tailored solutions by understanding end-user preferences, pain points, and expectations from captured experience data. For example, AI-powered virtual agents can customize their recommended troubleshooting steps based on an employee’s technical proficiency and past interactions with IT.
Hopefully, this blog has allowed you to understand the connectivity between Agentic AI and experience data (and the risk of introducing Agentis AI capabilities without the right insight). To learn more about how our customers are using experience data to drive Agentic AI success, get a 30-minute introduction to our platform with one of our team.
You may also like to read the following article: AI in ITSM: Avoiding the Hype and Focusing on Value
