AI adoption is exposing the IT skills gap and governance strain

TL;DR: AI is speeding up IT work for 56% of daily users while 38% of leaders say it also increases job complexity, and 63% of companies now require AI training, according to JumpCloud. The real constraint is no longer tooling alone but the people, process, and risk controls needed to scale AI safely.

NHIMG editorial — based on content published by JumpCloud: AI readiness, skills gaps, and the dual nature of AI in IT operations

By the numbers:

• 56% of IT professionals who use AI daily say it saves them time and reduces stress.
• 38% of IT leaders who praise AI also report that it increases the complexity of their jobs.
• 63% of companies require their teams to complete some kind of AI training.

Questions worth separating out

Q: How should organisations train IT teams for AI adoption?

A: Organisations should train IT teams on AI integration, risk management, and compliance using real workflows, not generic awareness content.

Q: Why does AI make IT governance more complex?

A: AI makes IT governance more complex because it changes how work is delegated, reviewed, and owned.

Q: What do organisations get wrong about AI readiness?

A: Many organisations treat AI readiness as a deployment problem when it is also a people and control problem.

Practitioner guidance

• Map AI-assisted workflows end to end Identify which IT tasks are now being augmented by AI, which decisions remain human-owned, and where review or escalation points disappear when speed increases.
• Assign explicit owners for AI risk and compliance Tie each AI-enabled process to a named business, security, and legal owner so policy exceptions, data use, and approval changes do not sit in a shared grey zone.
• Build role-based training around real operational scenarios Use training that covers integration, compliance, and incident handling for AI-enabled work rather than generic awareness modules that do not change day-to-day behaviour.

What's in the full article

JumpCloud's full article covers the operational detail this post intentionally leaves for the source:

• The specific IT Trends 2026 findings behind the productivity and complexity split, including the survey framing and audience mix.
• The article's guidance on how leaders should structure AI training for technical, legal, and ethical topics.
• The role creation discussion, including the kinds of skills IT teams are expected to add as AI use expands.
• The full Q1 2026 IT Trends Report context behind the broader AI readiness discussion.

👉 Read JumpCloud's analysis of AI readiness, skills gaps, and IT complexity →

AI adoption is exposing the IT skills gap and governance strain?

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