Gets a workforce genuinely capable with AI tools, rather than merely trained.
What separates them
Attendance is easy to count and change is not, so the real question is what they measured weeks after the session, not during it.
Ask these
01
How do you measure whether training actually changed how people work, rather than just that they turned up?
Tests whether they measure behaviour change rather than attendance or satisfaction scores.
A strong answer
They describe a specific behavioural or output measure taken before and after, for example a change in usage patterns or in how tasks get completed, checked again weeks later rather than immediately after the session.
The confident failure
They describe attendance figures or an immediate feedback form as the measure of success, with nothing measured later or tied to actual work.
02
Tell me about a training programme that didn't work. What did you find out about why, and what did you change?
Tests honesty and depth about failure, and whether they iterate on real signal.
A strong answer
They give a specific example and a concrete reason for the failure, for example that the training didn't match how people actually worked day to day. They also describe a real change they made to their approach afterwards.
The confident failure
They say training generally goes well, or attribute a poor result vaguely to engagement without describing what they actually found or changed.
03
How do you tailor what you teach to people with very different starting points, some sceptical, some already using these tools daily?
Tests whether they treat enablement as one size fits all or adapt to the actual audience.
A strong answer
They describe a specific way of assessing starting points, such as a short pre-session task or an informal audit of current usage, and how the content was adjusted for different groups as a result.
The confident failure
They describe a single standard curriculum delivered to everyone, claiming it works for all levels without any specifics on adaptation.
04
What do you do when the person most resistant to using a new tool is someone senior, whose buy-in you actually need?
Tests political and interpersonal skill in driving adoption, not just teaching ability.
A strong answer
They give a specific example and describe the underlying objection, for example a fear of looking less capable. They also describe a tailored approach that addressed that objection, rather than a generic pitch on benefits.
The confident failure
They describe pushing harder on the technical benefits or escalating past the person, with no attempt to understand the actual resistance.
What we ask when assessing for the register
Harder, and answerable only by somebody who has done the work. Published because a question that stops working when it is known was never testing anything.
01
Describe a case where adoption looked successful on the surface, people were using the tool, but you found out later it wasn't actually helping. How did you find that out?
Tests whether they look past surface usage metrics to real value.
A strong answer
They give a specific example and describe the deeper signal that revealed the problem, for example that usage was high but output quality or time saved hadn't actually changed. They also say what they did about it.
The confident failure
They treat usage numbers alone as proof of success, with no deeper investigation, or claim this situation has never come up for them.
02
Tell me about a time you had to tell a sponsor that their programme's headline metric was misleading. How did that conversation go?
Tests integrity and communication under pressure, when the easy path is to let a good looking number stand.
A strong answer
They give a specific example and name the misleading metric and why it misled. They also describe how they reframed success for the sponsor, and what happened to the programme afterwards.
The confident failure
They say they've never encountered a misleading metric, or describe softening the message so much that nothing actually changed as a result.
Ask these whatever the discipline
Tell me about something you built that failed in production. What broke, how did you find out, and what did you change?
What would you refuse to do on this project, and what would you tell me instead?
How would you know, three months in, that this was not working?
What is the part of your own work that you are least confident about?
Relevant here, and none of them is evidence on its own. What each does and does not prove is set out in full on the certifications page.
Foundation Certificate in Artificial Intelligence, BCS, The Chartered Institute for IT. Anything at all about building or assessing AI systems. BCS states there are no entry requirements, and the certificate is honest about being a foundation.