Good News — 7 in 10 of Your People Are Ready for AI

Seven in ten of your people say they feel ready to work with AI. You probably think that number is closer to four in ten — and that's where the rollout goes sideways. When leaders underestimate readiness, they design for a reluctant, under-confident team. They slow-walk training. They add approvals. The 70% who are already there wait, lose momentum, and move on. The rollout stalls. Your people were already there — leadership just never checked. Asking people what they think, feel, and can actually do is the oldest move in change management. It's also the most skipped one.

What's actually happening

Research published in Workplace Insight this month identifies what it calls the trust speed problem: organisations moving at software speed while trust develops at human speed. It's a useful frame because it doesn't assign blame.

Leaders aren't wrong to want faster adoption — the competitive case is real. Workers aren't being difficult — they're navigating genuine uncertainty with incomplete information. The gap between them is a coordination problem, and coordination problems are fixable when you can actually see them.

The data shows where coordination breaks down. Only 36% of organisations clearly demonstrated how AI would create opportunity rather than displace roles. Just 39% of employees participated in redesigning the jobs AI would affect. And only 31% of leaders feel confident their organisations have the AI knowledge to assess opportunities and risks.

That last number sits alongside a workforce reporting 70% readiness. Leaders are underselling their own people — and making rollout decisions based on that undersell. The timeline misalignment follows directly: 45% of executives expect AI fully integrated within 12 months, while just 30% of workers think that's realistic. When leaders don't know where their people stand, plans land wide.

The organisations closing the gap fastest share one measurable difference: 49% have mature processes for measuring workforce trust, compared to 18% everywhere else. The difference isn't enthusiasm or budget. It's the discipline of finding out rather than assuming.

Your next step

This is also where the cost from the botsitting research compounds. When leaders underestimate readiness, the framework gets under-resourced. When the framework is thin, AI gains erode — verification overhead, guilt and guesswork all pile up. The perception gap and the productivity gap feed each other.

The entry point is simple: find out where your team actually stands. Not where you assume they stand, not where they perform in a mandated training session — where they genuinely are, across governance, transparency, manager confidence and training readiness.

The organisations closing the adoption gap fastest didn't just want it more. They measured where they actually were — and built from there.

The Change Made Simple AI Readiness Scorecard was built from a change management perspective — looking at the four areas that determine whether AI adoption actually lands. Ten questions, about 4 minutes, no sign-up. You'll walk away with tailored actions designed to give your AI project the best chance of succeeding.

Written by Sheena Karim Connect on LinkedIn ↗