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Maister

Our philosophy

Companies are not short of AI training. They are short of anything to show for it.

Almost every small and medium-sized company has now run something: a webinar, a lunch-and-learn, a license rollout with a slide deck attached. Very few can point to a number that moved. The reasons are consistent, and they are not about which model you picked.

Take the Readiness Check

A meeting room at the end of the day
The question we keep being asked “We trained everyone. Why is nothing different?”

What we see

Why the gain stops before it reaches the business

6%

of companies see a meaningful impact on their EBIT from AI.

The problem

Eighty per cent of people who use AI at work report that it has improved their productivity, but only six per cent of companies see a meaningful impact (>5%) on their EBIT.1

ConclusionPersonal gains are not translating into business outcomes.

<4%

of workers can write an effective automation.2

A key reason

The use of AI is shallow. The most common use of AI at work is as a replacement for search, and more than seventy per cent of workers use it for one-off tasks. Most people have access to agents at work but only ten per cent understand what an agent is.2

ConclusionPeople are not using AI for the highest-impact work.

58%

of companies now offer AI training, up from a quarter a year ago.3

And yet

Companies have taken action. The share offering AI training has more than doubled in a year, but this has not produced the proficiency or the gains they expected: sixty-two per cent of knowledge workers have had some AI training, while only five and a half per cent are proficient.2

ConclusionThe training on offer today is not working.

1McKinsey, The State of AI 2026.  2Section, AI Proficiency Report 2026.  3Workera, State of Skills Intelligence 2026.

A Maister training room before a session

What we found

We went looking for why AI training has not worked

We read the evidence on corporate AI training: what companies buy, what their people can do afterwards, and where it comes apart. Five things came back again and again. The program is built around them.

McKinsey, The State of AI 2026 · BCG, AI at Work 2025 and 2026 · HBR 2025 · METR 2026 · Section and Workera, 2026. The last two are vendor research and are directional rather than audited.

Colleagues gathered round a laptop demo

Show, then scale.

Nothing changes a room like a colleague demonstrating something they built themselves.

What we believe

Training is the start of the change, not the delivery of it

An engagement is not finished when the sessions end. It is finished when someone inside the business can say what changed and show the number. That is why the assessment comes first, why the competition exists, and why the ninety days is included rather than sold.

See the full program

Not sure where you are

Find out in about three minutes.

Eleven questions place you in one of four profiles and suggest a route through the program. It is a self-assessment, not a diagnosis — but it is the same ground the paid assessment covers with evidence.

Take the Readiness Check