The conversation about AI in large organisations tends to gravitate towards the same set of questions. Which model? Which platform? Which use case to prioritise? These are reasonable questions. They are also, increasingly, the wrong place to start.
Spend enough time listening to the people actually leading AI transformation inside major organisations, and a different picture emerges. The technology, they will tell you, is rarely what slows things down. The people question is.
That is the thread running through the latest episode of Data and AI Mastery. Featuring a compilation of conversations with senior data and AI leaders at the FCA, Aviva, The AA, Santander UK, Oxford Saïd Business School, and TransUnion, one theme surfaced consistently, regardless of sector, scale, or where each organisation sits on its AI journey. Getting people genuinely ready for AI is harder than deploying it. And most organisations are underestimating that gap.
Ask leaders what they look for when building AI-capable teams, and the answers converge quickly. Qualifications matter less than they once did. Domain expertise matters, but not as much as the willingness to question, to experiment, and to keep learning when the landscape shifts beneath you.
Harj Johal at The AA puts it plainly. The quality that consistently stands out is curiosity. Not the willingness to accept an answer, but the impulse to pull on the string. To ask what if, and then go and find out.
Sudhish Mohan goes further. Curiosity, he argues, is no longer optional. At the pace AI is moving, the knowledge someone builds today will be substantially different in six months. The only sustainable response is to develop the habit of learning itself, not just the content of what is currently known. Steve Jobs said it at Stanford years ago. It turns out he was describing a professional survival skill.
If curiosity is the asset organisations need to cultivate, fear is the liability they need to address. And it is more widespread than most leadership teams acknowledge.
Sarah Self at Aviva is direct about this. Keep AI as something only a select group of people are using, and you amplify the anxiety in everyone else. The antidote is access. Let people use the tools. Let them have the moment of realisation that comes from actually trying something, rather than reading about it. Once someone has their own experience of what AI can and cannot do, the fear tends to recede. The resistance softens.
Luke Pearce at Santander UK frames it differently but arrives at the same place. The people sitting in branches, working in central functions, and managing products every day have expertise AI cannot replicate. They do not need to be afraid of the technology. They need to be shown that it is there to augment what they already know, not to displace it.
Where organisations often go wrong is treating the people dimension of AI as a training exercise. Run the programme, tick the box, move on. The leaders in this episode are largely sceptical of that approach.
Conny Ploth makes the case for rethinking what upskilling actually looks like moving forward. Attention spans have changed. The traditional classroom model has limited appeal. What creates genuine impact, she argues, is experience. Hackathons. Live challenges. Moments where people build something, feel something, and want to share it. Emotional connection to learning is not a nice-to-have. It is what makes it stick.
Mark Bramwell at Oxford Saïd Business School describes something similar from a leadership perspective. The goal is not to make everyone an expert. It is to create a culture where people understand the direction of travel, feel safe enough to engage, and eventually develop what he calls a fear of missing out. When the departments doing interesting things with AI become visible to those who are not, the appetite to get involved tends to follow.
Nick Edwards at The AA offers a useful benchmark. Within four to five months of combining leadership education, accessible tooling, and space for people to practise, the water level across the organisation rose. Fifty use cases entered the system. Many are heading towards production.
The combination matters. Skills without tools stall. Tools without skills are wasted. Neither works without the psychological safety to experiment and sometimes fail.
The organisations making real progress are not necessarily the ones with the most advanced technology. They are the ones who asked the harder question first: are our people genuinely ready? And then did something about the answer.
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At Cambridge Spark, we work with organisations tackling exactly this challenge: building the AI literacy, cultural readiness, and practical capability that turns a workforce from resistant to ready. If the skills and literacy gap is something your organisation is navigating, explore how we can help at cambridgespark.com.