AI Adoption Isn't Failing Because of Training. It's Failing Before Training Even Starts.

Kathy Caprino’s recent piece in Forbes, Why AI Adoption Is Failing Inside Many Companies, is one of the sharpest breakdowns I’ve read this year of what’s actually going wrong with corporate AI rollouts. I agree with nearly all of it. Leaders are treating adoption as a usage mandate instead of a redesign of how work gets done. Employees are being measured on how much they use AI, not how well. And the numbers back it up: McKinsey found major gaps in training and support behind the rapid rise in AI access, and Deloitte found only one in five companies has a mature governance model for their AI agents. As the article puts it: “AI adoption without governance is not empowerment. It is exposure.”

All of that is true. But there’s one piece missing from the story, and it’s the piece I see most often in the organisations I work with.

The mistake happens before training. It happens at the tool-selection stage.

The Forbes piece rightly identifies that leaders push usage before trust, and productivity before clarity. What it doesn’t name is why that sequence happens in the first place. In my experience, it’s because most organisations start the whole AI journey with the wrong question.

They ask: “Which AI tool should we buy?”

Not: “Where does our team actually lose the most time?” Not: “Which parts of our workflow are repetitive enough that AI could genuinely help, and which require judgement we shouldn’t automate?” Not even: “What’s already happening informally, who on the team is already using ChatGPT on their own laptop, and for what?”

When the starting point is a tool rather than the work itself, everything the Forbes article describes downstream becomes almost inevitable. You end up with generic training that doesn’t map to anyone’s actual job. You end up rolling out a licence to 200 people and hoping adoption follows. You end up, as Raman Rai says in the piece, confusing access with adoption and pilots with progress, because nobody did the work of understanding the workflow before the tool arrived.

Governance and training are the right fixes for the wrong starting point

I don’t think the Forbes piece is wrong to call for better governance, clearer guardrails, and stronger human capacity-building. Those are exactly right for what happens after you’ve understood the work. But if you skip the diagnostic step, you’re building governance frameworks and training programmes for a rollout that was never mapped to real needs in the first place. That’s how you end up with the “top-down mandate” problem the article describes: employees don’t trust the AI initiative because it was never built around their actual work to begin with. It was built around a tool someone in leadership wanted to deploy.

The fix isn’t more training bolted onto a tool-first rollout. It’s flipping the order: understand how work is actually done, find where the real opportunities and risks sit, and only then decide what tool (if any) belongs there, alongside the training and governance to support it properly.

Where to start instead

Before anyone in your organisation asks “which AI tool should we buy,” someone should be asking a more basic set of questions: where is time actually being lost, what’s already happening informally with AI on people’s own devices, and which of those areas are worth building real capability around first.

That diagnostic is exactly what our AI Readiness Assessment is built to surface: five minutes, eight questions, no sign-up, and a clear picture of where your organisation actually stands before you spend a penny on tools or training.

Take the free AI Readiness Assessment: aminaai.co.uk/assessment

Want to talk through what it surfaces? Book a discovery call and we’ll map where AI genuinely fits into how your team works before any tool gets purchased.

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Responding to: Kathy Caprino, “Why AI Adoption Is Failing Inside Many Companies,” Forbes, 26 June 2026. Read the original article