The starting point
A new strategy, AI tool or structure will not change working practices on its own. People need to understand what is expected, develop new skills and have a chance to practise them in their work.
Talent development starts with a practical question: what will leaders, managers and teams need to be able to do for the transformation to succeed? I focus on connecting that ambition with capabilities people can use.
What I seek to clarify
Make learning a collective capability grounded in real work.
Start with real situations at work
A training catalogue alone cannot prepare people for changing roles. The starting point is the work itself: assessing an AI response, sharing knowledge, making a decision with incomplete information or collaborating differently.
Learning becomes useful when people can work on real problems, receive feedback and apply what they have learned. Progress needs to show up in practice, beyond attendance numbers.
Support managers as learners too
Managers need to explain the purpose of change, clarify responsibilities and help teams try new ways of working. They also need room to learn, discuss difficulties and adjust their approach.
My background brings together engineering, management, change and knowledge sharing. It makes me attentive to the gap between understanding a transformation and feeling able to contribute to it.
Make learning a shared practice
Preparing future capabilities also means creating regular opportunities to share, experiment and reflect. Over time, this can reduce reliance on a few experts and strengthen collective confidence and autonomy.
Questions that make learning useful
- Which skills will our direction require over the coming months?
- What do managers need to learn to support new uses of AI?
- Where can people apply their learning in real work?
- How will we know that teams are more capable and make better decisions?
For further context, explore my convictions.