AI was supposed to make IT service management simpler – fewer escalations, faster resolutions, and a quieter service desk. But SolarWinds’ IT Trends Report 2026 tells a more complicated story. ITSM automation is delivering genuine wins in places, but it’s also creating new layers of complexity – particularly around AI incident management. For service desk teams, the gap between leadership expectations and frontline reality has become one of the defining challenges of the moment.
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The Incident Management Paradox
Based on a survey of over 1,000 IT leaders, SolarWinds’ latest report has exposed a striking contradiction.
44% of IT professionals say managing incident response across teams has become a new or increased responsibility since AI adoption.
However only 27% report any meaningful reduction in alert volume thanks to AI. This means while AI might be doing more, the demand on teams isn’t shrinking like it’s supposed to.
First-line managers, those closest to day-to-day IT service management operations, are feeling this most acutely. 41% say AI has increased expectations without reducing workload — more than double the 18% of C-suite leaders who say the same. As one survey respondent said:
“It can make work easier, but we cannot guarantee what it may help with or what risks can come.”
The underlying cause appears to be pace. Organizations are deploying ITSM automation faster than they’re building governance structures to support it, leaving service desk teams to absorb the overhead. This includes manual checks, cross-team coordination, and risk management – without the infrastructure to handle it efficiently.
The Shift From Reactive to Proactive
There is a meaningful bright spot. For the first time, IT teams are genuinely spending less time in reactive mode: 23% of respondents say time spent responding to and troubleshooting incidents has decreased – making it the only core IT activity to register a reduction. Meanwhile, 66% report spending more time on proactive issue prevention.
This shift is one of IT service management’s most long-standing goals, and AI appears to finally be moving the needle. As one respondent put it:
“I expect AI to automate routine ticket routing and network monitoring, allowing our IT team to focus on strategic practices.”
Realizing that potential consistently, however, depends on having the right ITSM automation tooling and strong governance foundations in place.
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Faster Diagnosis – But a Trust Deficit That Slows It Down
AI’s most concrete win in service management is in diagnostics. 61% of IT professionals say AI has accelerated root cause analysis, helping teams identify the source of incidents faster than before. For AI incident management to deliver its full value, though, trust needs to catch up with capability.
Right now, it hasn’t. 71% of respondents still manually double-check AI outputs, and 62% report difficulty trusting AI recommendations. In a service desk environment, that trust gap translates directly into slower resolutions – teams receive AI-generated answers but spend time verifying rather than acting on them.
The report also flags data quality as a core factor: 83% agree that AI is only as effective as the breadth and quality of data it can access, pointing to fragmented IT environments as a significant root cause of the trust problem itself.
Final Takeaways
AI is reshaping IT service management in ways that are both promising and deeply challenging.
For example, reducing reactive firefighting and accelerating diagnostics while simultaneously adding coordination overhead that many service desk teams aren’t yet resourced to handle. The organizations pulling ahead are those treating governance and data quality as prerequisites for ITSM automation, not afterthoughts.
As AI becomes more autonomous and embedded in service operations, the question for IT leaders is no longer about adoption. Rather, the question is whether the foundations, skills, and trust required to make AI incident management truly work are being built fast enough to keep pace.
FAQs
What is IT service management (ITSM)?
IT service management is the practice of designing, delivering, and improving IT services to meet business needs. It covers service desk operations, incident and change management, and asset tracking, typically guided by frameworks like ITIL.
What is ITSM automation?
ITSM automation uses software – increasingly AI-powered – to handle repetitive service management tasks without human intervention. This includes ticket routing, incident categorization, and alert triage. It requires strong data foundations and governance to work reliably.
What is AI incident management?
AI incident management applies artificial intelligence to the detection, diagnosis, and resolution of IT incidents. This correlates to alerts, surfacing root causes, and suggesting fixes. As this report highlights, trust and data quality remain the key hurdles to unlocking its full value.
What is root cause analysis in ITSM?
Root cause analysis (RCA) identifies the underlying cause of an IT incident rather than just its symptoms. AI is increasingly used to speed up this process. Although teams still need confidence in AI outputs before acting on them decisively.
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