What most AI training actually delivers
Most AI training sessions follow a similar structure: an overview of what AI is, a demonstration of some tools, a few examples of use cases, and a Q&A. Attendees leave having learned something. They might feel positive about AI. Some will try a tool when they get back to their desk.
But ask those same people three weeks later what they've changed about how they work, and the answer is usually: not much. The session created awareness. It didn't create behaviour change.
These are different things. Awareness is knowing that something exists and broadly what it does. Behaviour change is doing something differently, consistently, because it's better than what you were doing before. The gap between the two is where most AI training fails.
Why awareness doesn't translate to change
The problem is usually one of specificity. Generic training — covering AI broadly, with examples from other industries or other roles — doesn't give people the specific mental models they need to apply what they've learned to their own work.
Someone who works in procurement needs to see how AI helps with supplier communications, contract review, and spend analysis — not how it's being used in healthcare or marketing. The moment of recognition ("that's exactly what I do every Tuesday") is what creates the motivation to try something new. Generic examples don't produce that moment.
The second issue is that awareness training rarely addresses the friction points. People know AI tools exist. What stops them using them is a combination of uncertainty about when to use them, concern about the quality of the output, and the simple inertia of established habits. Training that only covers capability — and not the practical how-to of integrating a tool into a real workflow — leaves people with knowledge but no pathway to action.
What training that changes behaviour looks like
It starts with the audience's actual work. Before the session, effective training involves understanding what the people in the room actually do — which tasks take the most time, where the frustrations are, what good output looks like in their context. The session is then built around those specifics, not a generic curriculum.
It shows, rather than tells. Demonstration using the client's own tools and workflows — not a sanitised demo environment — is significantly more effective than slides. When people see a tool working on something they recognise, the connection between capability and application becomes immediate.
It includes hands-on practice. The session where people just watch is not the same as the session where people try something themselves, make a mistake, try again, and find that it works. The latter produces behaviour change. The former produces notes that don't get read.
It addresses the anxiety directly. Effective training makes space for the questions people are actually worried about — about accuracy, about job security, about what's appropriate to use AI for. Ignoring these concerns doesn't make them go away. Addressing them honestly, with clear guidance on appropriate use and quality checking, removes a significant barrier to adoption.
It has a follow-through structure. The session itself is not enough. Behaviour change requires repetition and reinforcement. Training that includes a 30-day action plan — specific things to try in the first month — and some form of follow-up support produces measurably better adoption than training that ends when the session ends.
How to evaluate AI training before you book it
Ask the provider how they tailor the content to your industry and roles. If the answer is vague, the training is probably generic. Ask what attendees will walk away with beyond a slide deck. Ask how they measure whether adoption has happened. Ask whether the session includes hands-on practice or is primarily demonstration and presentation.
The answers will tell you quickly whether you're looking at awareness training or at something that's been designed to produce real change.
The goal of AI training isn't for people to know more about AI. It's for people to work differently because of AI. That's a higher bar — and the sessions that clear it are built very differently from the ones that don't.