Fluency Over Literacy: Teaching People, Not Systems

Most of the training for your AI is nowhere close to where it needs to be pointing and directing and therefore misses the point. It teaches the system — how to click, prompt, or navigate — as if user manuals are enough to build transformation. But people don’t need technical walkthroughs. They need strategic fluency. They need to know when to trust the tool, when to override it, and how to work with AI without becoming dependent on it.

Literacy is surface-level. Fluency is behavioural. It shows up not in what people know about AI, but in how they use it in complex, real-world scenarios. That’s the difference between adoption and enablement.

The real constraint isn’t whether people understand how the model works. It’s whether they understand how to use it well inside their actual role. That’s why generic training fails. A support analyst, a sales rep, and a project manager all interact with risk, data, and ambiguity differently. If the training doesn’t reflect that, it doesn’t land.

Fluency also means understanding the limits. Teams need to know how confident the system is, what assumptions it makes, and where its blind spots lie. That’s how trust is earned — not through hype, but through honest framing and contextual relevance.

The organisations gaining ground aren’t investing in more demos. They’re investing in enablement — not just onboarding, but iterative coaching, contextual walkthroughs, and role-specific up-skilling.

If your team can describe the AI but not use it, that’s not maturity. That’s performative adoption. Stop teaching the system. Start teaching the human.