Most organisations are rolling out AI faster than they're teaching anyone to use it well.

That's not a technology problem. It's a learning one.

The licences get bought. The tools get switched on. The dashboard lights up with adoption numbers. And everyone assumes the capability arrived with the subscription.

It didn't.

Deloitte's 2026 research found the AI skills gap - not the technology - is now the single biggest barrier to getting value from AI. And according to Accenture, only around a quarter of workers have had any training on how to work alongside it.

So, we've handed people the most powerful tool of their careers and largely left them to work it out in the dark.

Here's the part that gets missed: AI literacy isn't knowing which buttons to press.

It's judgement.

• Knowing when to trust an output and when to challenge it.

• Spotting where the model is confidently wrong.

• Understanding what should never be typed into the box.

• Knowing which decisions still belong to a human.

None of that comes with the tool. All of it can be taught. Which is exactly what makes it a learning problem - and a solvable one.

But it won't be solved by a one-off webinar on prompts. AI literacy has to be built where the work happens: role-specific, tied to the real decisions people make, practised on the tasks they actually do.

That's how we'd build it at Learnopolis. Not generic AI awareness. The specific judgement each role needs to use AI well, and safely.

Giving people a tool they've never been taught to question isn't adoption. It's risk with a faster interface.

Jen