Craig Suckling is Chief AI Officer for Europe at Capgemini, bringing more than 25 years’ experience across data, AI, and technology leadership. His career spans senior roles as a Chief Data Officer in both the private and public sectors, building and scaling start-ups and hyperscalers, working as a management consultant, serving on advisory boards, and now leading AI strategy at enterprise scale.
Craig’s path into data and AI began at university, where he studied computer science after initially training as a graphic designer. Learning to code became a new creative medium, combining engineering discipline with design thinking; a blend that has shaped his approach ever since. He thrives in complex, fast-moving environments that demand clear ownership, rapid problem-solving and close collaboration with highly capable teams.
Three major shifts have most influenced his perspective as a data and AI leader. First, data has evolved from a back-office cost into one of the most valuable corporate and national assets. Second, AI has moved from experimental research into scalable, production-grade capability, with generative and agentic AI now directly augmenting how people work and make decisions. Third, organisations are shifting away from monolithic data functions towards decentralised, product-oriented teams built on shared cloud and AI foundations.
Together, these changes underpin Craig’s belief that modern AI leadership is not about technology alone, but about orchestrating value, empowering teams, and translating technological potential into measurable real-world impact.
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?
“The most important traits for effective data and AI leadership sit at the intersection of business impact, human leadership, and systems thinking. First is the ability to translate complexity into outcomes. Data and AI leaders must connect rapidly evolving technologies to clear commercial and operational value, enabling the business to act with confidence rather than be overwhelmed by possibility.
“Authenticity and empathy are now core leadership skills. As AI reshapes roles, workflows, and decision making, leaders must acknowledge uncertainty, listen actively, and lead change in a way that brings people with them. Trust is built by being transparent about what AI will and will not do, and by showing how it augments rather than replaces human expertise.
“Effective leaders also focus on enablement over control. This means creating the conditions for innovation and autonomy across every team, supported by shared platforms, standards, and capabilities. The role is to orchestrate value, not centralise delivery.
“At the same time, leaders must create a strong culture of ethics, trust, and security. Responsible AI cannot be an afterthought. Clear principles, embedded governance, and secure foundations are essential to moving fast without increasing risk.
“Finally, adaptability and curiosity matter. The best leaders continuously learn, simplify complexity, and help organisations turn AI into everyday advantage.”
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?
“Spend as much time shaping belief as you do shaping solutions. The biggest constraint on impact is rarely the technology. It is whether people believe change is possible, safe, and worth committing to.
“Stay relentlessly curious, but do not just chase new models or tools. Be curious about how decisions get made, where power sits in organisations, and what actually stops good ideas from scaling. Take risks but take human risks as much as technical ones. Volunteer to work in messy business problems, lead ambiguous initiatives, and step into roles where success is not guaranteed.
“Think big, but start with outcomes, not architectures. The leaders who make a difference are those who can hold an ambitious vision while staying grounded in real constraints, incentives, and behaviours.
“Finally, do not wait to be ready. AI leadership is something you grow into by acting early, learning in public, and adapting fast. Progress comes from momentum, not perfection.”