SolarWinds report finds 80% of IT professionals say AI is shifting roles from operator to orchestrator, while challenges around trust, governance, and skills persist. This Network World article explores how AI is reshaping IT roles, shifting responsibilities toward orchestration and strategy. Reach out to Capgemini to discuss how IT teams can adapt to evolving demands.
How is AI changing day-to-day IT roles?
According to the 2026 SolarWinds IT Trends Report: The Human Side of Autonomous IT, AI is prompting a clear shift in how IT teams work:
- 80% of IT professionals say their roles are moving from hands-on operators to orchestrators of automated systems and workflows.
- Instead of spending most of their time executing tasks, IT staff are spending more time governing systems, workflows, and AI tools that execute on their behalf.
- 52% of respondents say their roles are becoming more strategic and automation-driven.
- Roles are also becoming more cross-functional (47%) and more complex (41%), as AI gets integrated into broader business processes.
In practice, this means IT teams are:
- Spending more time on proactive work like strategy and performance analysis.
- Spending relatively less time on some reactive tasks, such as routine troubleshooting.
AI is helping IT reimagine its value to the business—from “keeping the lights on” to designing, overseeing, and improving automated, data-driven operations.
Where are the biggest gaps in AI readiness and trust?
The report highlights a noticeable gap between executive confidence and technical reality, as well as ongoing trust issues with AI:
- Readiness perception gap:
- 47% of C‑suite leaders say their organizations are extremely prepared for AI-driven change.
- Only 13% of technical contributors feel the same level of readiness.
- Trust and verification challenges:
- 71% of IT professionals say they need to double-check AI outputs.
- 62% report difficulty trusting AI recommendations.
- 71% say AI has made their roles more demanding, partly because they must verify results and manage new risks.
- Adoption levels and resistance:
- 50% of respondents say their organizations have embraced AI (34% somewhat, 16% fully).
- 37% report resistance, often due to infrastructure, budget, or complexity concerns.
As SolarWinds CTO Krishna Sai notes, the organizations seeing the best outcomes are not necessarily the ones with the most AI tools, but the ones building the governance and structure needed to actually trust and manage those tools effectively.
What do IT teams need to make AI adoption work better?
The report outlines several practical enablers that IT teams say would make AI adoption more effective and sustainable:
- Clearer policies and guardrails:
- 56% of respondents want more defined AI policies and guardrails to help them adapt and use AI responsibly.
- Training and skills development:
- 50% say formal training would help them work more confidently with AI tools and automation.
- Skills gaps are flagged as an ongoing challenge as AI reshapes IT roles.
- High-quality, integrated data:
- 83% of respondents say AI effectiveness depends on the breadth and quality of available data.
- Tool fragmentation and lack of integration are cited as barriers to getting full value from AI.
- Stronger governance and oversight:
- Teams need structures to ensure accuracy, reliability, and risk management for AI-driven systems.
- Governance is becoming as important as the tools themselves.
Looking ahead, 77% of respondents expect their organizations to become more proactive over the next two to three years, supported by increased automation and data-driven insights. To get there, they will need a combination of clear rules, better training, stronger data foundations, and integrated tooling.
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