Enterprise Learning

The L&D problem nobody’s talking about

Most enterprise AI training is backwards. Organisations are running “how to use ChatGPT” workshops and calling it capability building. That’s like teaching someone to use a calculator and calling it mathematics education.

The real question is harder and more important: when AI can summarise, draft, analyse, and remember on your behalf, what do your people actually need to know? What skills become more valuable, not less? And what happens to your workforce’s capability if they outsource too much thinking to machines?

This isn’t theoretical. Research is already showing that over-reliance on AI summarisation reduces critical thinking and narrows the range of ideas people generate. The organisations that get L&D right in this era won’t just be more productive - they’ll be more resilient.

What I actually do

I build L&D frameworks that help organisations navigate AI adoption without accidentally making their teams less capable.

Capability architecture - Mapping which skills in your organisation should be automated, which should be augmented by AI, and which should be protected from AI altogether. I call this the Automate/Augment/Protect framework.

Learning design - Building training programmes that use AI as a scaffold, not a substitute. The distinction matters: a scaffold helps you build capability, a substitute replaces it.

Metacognition frameworks - Teaching teams to think about their own thinking in an AI-augmented environment. When do you trust the AI output? When do you push back? How do you maintain critical judgement when the machine is doing the heavy lifting?

Measurement & evaluation - Most L&D metrics measure consumption, not capability. I help build evaluation frameworks that tell you whether your people are actually getting better, not just completing modules.

AI policy for learning - Governance frameworks for how AI should and shouldn’t be used in learning contexts. Where it helps, where it hinders, and where the line is.

The framework: Automate, Augment, Protect

This is the core of how I think about AI in learning:

Automate - Procedural knowledge that AI can handle reliably. Compliance updates, reference lookups, scheduling, administrative tasks. Free up cognitive bandwidth for higher-value work.

Augment - Complex work where AI makes humans better without replacing the human contribution. Research synthesis, draft generation, scenario modelling. The human still drives judgement and decision-making.

Protect - Capability-building where the cognitive effort IS the learning. Critical analysis, creative problem-solving, ethical reasoning, interpersonal skills. If AI does this for your people, they don’t learn - and your organisation gets weaker.

Who this is for

L&D directors and CHROs building AI capability programmes
Enterprise boards who need a strategic approach to workforce AI adoption
Agency and consultancy leaders upskilling teams for AI-native service delivery
SME founders who need their small teams to be brilliant with AI, not dependent on it

Common questions

Is this just AI training? No. AI training teaches people to use tools. This is about redesigning how your organisation learns and builds capability in an AI-augmented world. The tools are part of it, but they’re not the point.

How long does a typical engagement take? Framework design is typically 6-8 weeks. Implementation support varies depending on organisation size. I also run intensive workshops for leadership teams (1-2 days) to align on the strategic approach before committing to a full programme.

Do you deliver the training yourself? I design the framework and build the programme architecture. For delivery at scale, I typically work with your internal L&D team or recommended partners. For leadership workshops and board sessions, I deliver directly.