AI is delivering the ROI IT teams expected, but it isn’t necessarily reducing their workload. Instead, it is creating a new layer of work around managing, validating and maintaining AI systems.
SolarWinds has released its 2026 State of ITSM Report, which studies how IT teams are using AI in their Information Technology Service Management (ITSM) workflows. The report, based on a survey of IT professionals around the world, finds a gap between AI’s productivity gains and its impact on workloads.
According to the study, 84% of respondents say AI has met or exceeded ROI expectations, and they report meaningful time savings across core ITSM tasks. Yet 52% say their overall workload has increased since adopting AI, and only 7% say the cost of AI adoption matched what they planned for.
After an average of about 16 months using AI in their ITSM environment, most teams are still managing AI’s overhead rather than realizing its full potential, adds SolarWinds.
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AI Time Savings Come With Added Workload
Respondents report AI saves an average of 3.2 hours per week on detecting and flagging issues, 3.0 hours on end-user requests, and 2.9 hours on ticket triage. But those savings are largely being reinvested into a new category of work that did not exist at the same scale before AI:
- Managing and maintaining AI tools and integrations: 48%
- Reviewing and validating AI-generated outputs: 47%
- Training and fine-tuning AI models: 37%
Study finds, the costs that catch organizations off-guard compound this further. The top expenses — staff training (48%), data quality and cleanup (47%), and ongoing tuning and maintenance (45%) — are not one-time setup costs. They are recurring parts of the operating model, and more than four in five respondents (83%) now spend three or more hours per week just keeping their AI systems running reliably.
SolarWinds says, despite clear productivity gains, IT teams are discovering that AI isn’t reducing their workload; it’s reshaping it.
Reactive Instead of Proactive
SolarWinds’ survey found that AI is still being used mainly to respond to IT issues rather than prevent them. Identifying issues before they affect users was cited by 31% of respondents, while 23% pointed to prioritizing and routing issues. Only 19% said preventing issues before they occur was AI’s biggest impact.
At the same time, investment is increasing, with 85% reporting higher AI-in-ITSM budgets year-over-year. Of these, 36% said the increase was significant, while agentic workflows recorded the highest expected investment growth
Top Recommendations from SolarWinds for ITSM Teams
- Start where the path to value is clear: Focus AI on high-frequency tasks such as ticket triage, issue detection and incident documentation.
- Reduce integration overhead: Keep AI within existing service workflows where possible to limit maintenance.
- Strengthen the data foundation: Treat data quality as part of the AI strategy, since poor data can affect AI performance.
- Measure outcomes: Track business and user outcomes rather than simply measuring AI activity.
- Train teams: Provide AI training and change-management support as adoption expands.
Commenting on the research findings, Abdul Rehman Tariq Butt, Regional Director, Middle East, SolarWinds, says, “AI adoption alone is never a guarantee of success. Without the governance and data discipline highlighted in the report, speed can simply accelerate the workload problem.”
Disclaimer: This article is based on SolarWinds’ 2026 State of ITSM Report, a global study. Readers are advised to review the full report for its methodology and complete findings.
