Kier is sending 50 leaders to Oxford to learn how to lead with AI

Most AI training budgets go to the people at the keyboard. The managers who decide which projects get AI, how much risk is acceptable and what counts as a result are often left to work it out from vendor briefings. Kier has gone the other way, at least for its first move.
The UK infrastructure group has partnered with Saïd Business School at the University of Oxford on a program for 50 of its leaders, called the AI Strategy and Leadership Journey. It opens with a three-day residential at Oxford's Global Leadership Centre and then continues online. After the residential, participants keep working with Oxford in cross-business Growth Groups meant to find places to apply what they learned across Kier. It sits inside the group's Naturally Digital strategy, alongside a renewed Microsoft partnership announced earlier this year and digital tools and agents already in use, including in health and safety.
Chief executive Stuart Togwell said the approach is to "always have humans at the helm", and that investing in leadership is about equipping people to make informed, responsible and safe decisions. He was also clear about how he will judge it: "The real measure of success will be how we apply this learning across Kier." Leaders are expected to take the insights back into the business, share them and find practical opportunities that support growth.
Professor Andrew Stephen, the program's academic director, said Kier's leaders had embraced the opportunity with openness, and pointed out that given the group's role in national infrastructure, the benefits could reach well beyond the business.
The Growth Groups are the part I would watch. A residential at Oxford builds shared language and confidence. It does not, by itself, change how a bid gets priced or how a site team plans a week. That happens when the same 50 people come back with a small number of real problems, test them with the teams who own the work and report what changed. If the Growth Groups are set up that way, with named owners and a short list of use cases, the program becomes a pipeline. If they become a discussion forum, the learning fades by the next planning cycle.
For leadership teams trying to turn that kind of learning into tested projects, our AI Design Sprints are built around one real problem and a decision at the end.
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