The latest ITSM.tools survey was sponsored by HCLSoftware and provided a snapshot of where the IT service management (ITSM) community currently is with Agentic AI. This previous Agentic AI in ITSM article shares some key report findings and provides a sign-up link for a webinar where these and other survey findings were discussed.
Now, this article provides more detail on how Agentic AI is increasingly being introduced into ITSM environments, including sample correlations that highlight differences across regions and company sizes.
The Key Agentic AI in ITSM Insights Previously Shared
The previous ITSM.tools article offered a few teaser insights for the webinar. These were that:
- Nearly 75% of organizations use AI capabilities in their ITSM tools
- AI is delivering measurable ITSM efficiency improvements
- Agentic AI adoption continues to grow
- Service desk operations lead Agentic AI use cases
- Data quality and governance remain major Agentic AI in ITSM adoption barriers
- Half of organizations plan to advance toward Agentic AI in the next 12 months.
More detail on these insights can be found here: https://itsm.tools/state-of-agentic-ai-in-itsm-2026/. Alternatively, the full Agentic AI in ITSM report can be downloaded here.
Additional Key Agentic Insights
The HCLSoftware Agentic AI in ITSM report includes many more insights than those shared above, for example, that:
ITSM Challenges
The top three reported ITSM challenges differed from last year’s survey:
- Demonstrating business value (37%)
- Adopting AI capabilities (33%) (not Agentic AI in ITSM per se)
- Balancing cost-efficiency with service quality (31%).
AI in ITSM Tools
The survey found that most ITSM tools offer AI. However, this doesn’t mean they’re already being used. Nearly three-quarters of respondents’ organizations were using the AI capabilities of their ITSM tools to some extent.
Agentic AI benefits
The top three benefits of Agentic AI in ITSM were considered:
- Major reduction in manual intervention by IT teams (28%)
- Ability to scale ITSM operations without proportional headcount growth (27%)
- Significantly faster incident and request resolution (MTTR) (26%).
Agentic AI governance controls
Only 4% of survey respondents believed they don’t require additional controls, with the top two required controls for Agentic AI in ITSM adoption:
- Human-in-the-loop approval for critical actions (38%)
- Explainability and audit trails for autonomous decisions (24%).
Agentic AI acceleration
The top three accelerants for Agentic AI in ITSM adoption were thought to be:
- Clear governance frameworks and best practices (40%)
- Improved internal AI literacy and change management (34%)
- Proven ROI case studies from peer organizations (34%).
Many more insights are included in the report: https://www.hcl-software.com/bigfix/products/service-management/state-of-ai-in-itsm-2026-report.
Key Agentic AI in ITSM Correlations
The report contained nine AI-related correlations:
- North American organizations most needed greater AI-value clarity (however…)
- North American organizations were the most advanced with AI adoption
- There’s still an AI success divide between Europe and North America
- Organizational size impacts tool selection and the available AI capabilities
- CXOs were the most “bullish” on AI adoption
- Cost and value both play a part in AI adoption
- Agentic AI adoption requires an understanding of AI value
- Agentic AI adoption follows proven AI success
- AI success drives trust.
Each of these is covered in more detail in the report, but the first three are also included below.
North American Agentic AI in ITSM Correlations
- Respondents from organizations headquartered in North America were most likely to state that the value of the AI capabilities in their ITSM tools is unclear. Note: Asia, Europe, and North America data was used due to sample sizes.
- All the respondents from organizations headquartered in North America were at least experimenting with the AI capabilities available in their ITSM tools. These respondents were also most likely to state that their organizations have Extensive AI capabilities in production.
- Respondents from organizations headquartered in Europe were most likely to have no AI use. Whereas those in North America were most likely to claim that AI has improved their organization’s ITSM efficiency across the board.
- Respondents from organizations headquartered in North America had the greatest increase in trust in AI.
Paying for AI Capabilities
- Unsurprisingly, respondents who stated that their organization’s AI in ITSM capabilities were free had the highest level of AI capabilities in production. Conversely, respondents who stated that “it’s all a paid-for option, but the value is unclear” were most likely to be “Experimenting or testing AI capabilities” (55%) or to have “Limited AI capabilities in production” (45%) but not “Extensive AI capabilities in production” (0%).
- None of the respondents who stated that “it’s all a paid-for option, but the value is unclear” were “Actively prioritizing Agentic AI in ITSM and autonomous operations.”
Trust in AI
- The respondents who stated that their organizations had “Extensive AI capabilities in production” all had positive views of AI. 13% still trusted AI, and 87% had increased trust in AI. 100% stated that “they help.”
- The respondents with “Extensive AI capabilities in production” were far more likely to be “Actively prioritizing Agentic AI and autonomous operations.” Whereas respondents from organizations “Experimenting or testing AI capabilities” or with “Limited AI capabilities in production” were most likely to be “Gradually moving from assistive AI toward Agentic AI.”
Read the Full Agentic AI in ITSM Report
To download the full HCLSoftware Agentic AI in ITSM report, please visit here: https://www.hcl-software.com/bigfix/products/service-management/state-of-ai-in-itsm-2026-report.
Agentic AI in ITSM FAQs
Agentic AI refers to AI systems that can make decisions, initiate actions, and complete tasks with varying levels of autonomy. In ITSM, Agentic AI goes beyond assisting service desk agents by proactively resolving incidents, automating workflows, and managing routine service operations.
According to the survey, nearly 75% of organizations are already using the AI capabilities available in their ITSM tools to some extent. This demonstrates that AI has become a mainstream component of modern IT service management.
The survey identified the top three ITSM challenges as:
Demonstrating business value
Adopting AI capabilities
Balancing cost-efficiency with service quality
Survey respondents identified several key benefits, including:
Reduced manual intervention by IT teams
The ability to scale ITSM operations without increasing headcount
Faster incident and service request resolution
Improved operational efficiency
Greater automation of repetitive tasks
IT service desk operations remain the leading use case for Agentic AI in ITSM. Organizations are using AI to automate ticket handling, assist support analysts, improve self-service, and accelerate incident resolution.
The biggest barriers include:
Poor data quality
Weak governance
Privacy and security concerns
Limited AI expertise
Difficulty demonstrating business value
These operational challenges often have a greater impact than the AI technology itself.
As AI becomes more autonomous, organizations need controls that ensure AI operates safely and responsibly. Survey respondents highlighted human approval for critical actions and explainable decision-making as the two most important governance requirements.
The most requested controls include:
Human-in-the-loop approval for high-impact decisions
Explainability and audit trails
Clear governance frameworks
Accountability for autonomous actions
Compliance with organizational policies
These controls help build confidence in AI-driven operations.
Organizations believe adoption will increase through:
Clear governance frameworks and best practices
Better AI education and change management
Proven return-on-investment case studies
Increased organizational trust in AI
Successful implementation depends as much on people and processes as technology.
Yes. The survey found that organization size influences both ITSM tool selection and the AI capabilities available. Larger organizations often have access to more advanced AI features and greater resources to deploy them.
Yes. North American organizations were generally found to be further ahead in AI adoption in ITSM and more likely to have extensive AI capabilities in production. European organizations were more likely to report limited or no AI usage, indicating a continuing regional maturity gap.
Some organizations remain uncertain about the business value of AI, particularly when advanced capabilities require additional licensing or investment. Without clear ROI metrics and success stories, many remain in the experimentation phase rather than expanding AI deployment.
The research found a strong relationship between successful AI deployments and trust. Organizations with extensive AI capabilities in production reported significantly higher confidence in AI and were much more likely to prioritize Agentic AI in ITSM initiatives.
Yes. Organizations that have already achieved measurable success with AI are more likely to expand into Agentic AI in ITSM and autonomous operations. Positive experiences build organizational confidence and encourage broader adoption.
Technology alone cannot deliver successful AI transformation. Employees need to understand how AI works, where it creates value, and how governance protects the organization. Effective change management helps build confidence and encourages adoption.
Demonstrating measurable business value remains one of the biggest priorities for IT leaders. Organizations are increasingly looking for evidence that AI improves productivity, reduces costs, enhances service quality, and delivers a tangible return on investment.
The findings indicate that Agentic AI in ITSM adoption will continue to accelerate as organizations improve governance, strengthen data quality, build AI expertise, and gain confidence through successful AI implementations. Many organizations expect to progress toward more autonomous ITSM operations over the next 12 months.
Before expanding Agentic AI in ITSM, organizations should ensure they have:
High-quality, well-governed data
Clearly documented ITSM processes
Appropriate AI governance controls
Strong integration across IT systems
Clear success metrics and ROI measurements
An effective change management strategy
Building these foundations increases the likelihood of successful and responsible Agentic AI adoption.
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.
