Morgan Rees is Head of Enterprise Data Analytics at Capgemini Invent UK, where he leads the firm’s work in delivering practical, high-impact data and AI solutions. His career began with an engineering degree and an early role in the defence industry, which first exposed him to the use of data in a commercial and operational context. He subsequently moved into consulting, joining the Operational Research team at what was then Capgemini Consulting.
Over time, Morgan has helped shape and navigate the evolution of the analytics profession, from operational research and business analytics, through the emergence of data science, to today’s rapid acceleration of AI. He now focuses on data and AI strategy, innovation and scaling, helping organisations turn insight into better decision-making and measurable outcomes.
A significant part of Morgan’s experience has been working with Central Government, where he has led large-scale data transformations in complex, highly regulated and secure environments. This has included redesigning business processes to embed AI and establishing repeatable models that allow innovation to scale safely and sustainably.
What most defines Morgan’s leadership approach is his belief that data only becomes powerful when it changes minds and behaviours. He places strong emphasis on storytelling as a leadership skill, using evidence to influence decisions, build confidence in emerging technologies and inspire organisations to see AI not just as a tool for optimisation, but as a catalyst for rethinking what is possible.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“Data and AI leadership is increasingly about creating the conditions for safe, confident adoption of data and AI services at scale. That means reading your organisation and customers well, influencing people, and building flexible governance frameworks.
“A product mindset matters too, understanding how to shape clear roadmaps and take your teams on a journey from ideas to experimentation to scaling. Leaders need to avoid the easy metrics and measure outcomes over outputs, and put business adoption, value and safety first.
“As with any leadership role, the most important skill is how you manage relationships with people. In my organisation, the most influential skills for me have been how to adapt my style to different audiences, how to understand what motivates people and how to get the balance right between direction and freedom when it comes to leading highly talented data and AI professionals.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“My non-traditional advice for data leaders today is ‘learn to lead on ideas.’ As a data and AI leader, you’ll now be asked to defend the social, political, and economic consequences of what you are creating, not just the architecture behind it. That means cultivating a broader worldview than would have been the case for a data leader ten years ago.
“To understand the real impact of AI in your organisation or for your customers, people will expect you to understand and comment on topics as wide ranging as history, economics, sociology, and law. I always advocate for debating skills to learn how to position a point of view using plain language, and practise arguing the case for and against your own solutions! And you will need humility; we can’t predict the future. But you should have a point of view on the future you want to see, and the future you want your teams to create.”