SHOW NOTES

Once organizations move beyond early AI experiments, a new question appears: Do we have the right people to scale this? Eventually internal learning reaches its limits. You need deeper expertise. But hiring AI talent is one of the most competitive challenges companies face today — and the real question is not just who to hire, but how to build the right combination of people.

In this episode, Kenza and Amanda discuss when external AI expertise is actually needed, why the search for a unicorn AI hire so often fails, and what a healthy AI team really looks like. They explore how to integrate new talent without creating an elite separate group — and how to retain people who have endless options elsewhere.

This is also Amanda's final episode as co-host. She hands over to the next season with a clear message: AI transformation starts with the people who already understand your business.

KEY TAKEAWAYS

• Hiring too early is as problematic as hiring too late. The trigger should be scaling from pilots to production — not ambition.

• AI success does not come from one brilliant hire. It comes from a system of people working together.

• The strongest teams combine technical specialists, domain experts, and operational leaders — and pair new external talent with long-tenured internal knowledge.

• AI talent stays where they can see their work matter. Meaningful problems and speed of execution matter more than compensation alone.

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SHOW NOTES

When executives ask about AI transformation, the question is often: what is the right organisational design? Central team or decentralised? The honest answer is: you need both - and the balance shifts as your transformation matures.

In this episode, Amanda and Kenza explore what it actually takes to structure an organisation for AI. They discuss why a dedicated central team is critical in the early stages, how to handle the tension between day jobs and transformation work, and why measuring return on investment in AI is far harder - and more nuanced - than most boards expect.

KEY TAKEAWAYS

• Start with a central team close to the CEO to orchestrate initiatives and set the guardrails. Its importance decreases as the organisation matures.
• People cannot drive transformation on top of their day jobs. Organisations must explicitly free up capacity or accept that performance targets will temporarily take a back seat.
• AI handles structure well. Humans handle chaos. The smartest deployments automate the repetitive 80% and invest in people for the complex 20%.
• Before you automate anything, optimise the process first. Automating a broken process just makes the broken parts faster.

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When organizations talk about AI transformation, the instinct is often to ask: how do we measure culture? But the harder question is how to shape it. Culture is not what is written on a values poster - it is what people do when no one is watching.

In this episode, Amanda and Kenza explore why culture is the single most important lever in any AI transformation and how to move it deliberately. They discuss how a clear strategic vision needs to reach every level of the organization, why middle management deserves far more attention than it typically receives, and how to build a genuine learning culture where experimentation is encouraged and mistakes are not punished.

KEY TAKEAWAYS

• Culture is not the values on the lobby wall. It is how people behave when no one is watching.
• AI transformation cannot be delegated to the CTO alone - every executive owns a piece of it.
• The "frozen middle" is not resistant to change. It is overwhelmed. Organizations must explicitly create space for managers to learn and experiment.
• As long as mistakes carry career risk, adoption will stall. Psychological safety is not a nice-to-have. It is a prerequisite.

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Right now, in boardrooms everywhere, the same question keeps coming up: What are we actually doing about AI? Not in theory. Not in a pilot. But in the business.

In this first episode, Kenza and her co-host Amanda introduce the podcast and the question that drives it: why AI transformation has moved from the innovation lab to the executive agenda — and what that shift really means for leaders.

They explore the gap between AI expectation and organizational reality, why most leadership teams are still figuring it out, and what a genuinely useful conversation about AI at the executive level actually looks like. The show is positioned not at the extremes — not deep tech, not distant future — but in the messy middle where real leadership decisions happen.

KEY TAKEAWAYS

• AI has moved from innovation experiment to strategic priority — and leadership teams are expected to have answers.

• The real challenge is not technology. It is deciding where to place the first serious bet — and what that means for the rest of the organization.

• The most valuable AI conversations are the ones that usually stay inside executive rooms. This podcast brings them out.

Hosted on Acast. See acast.com/privacy for more information.