Daragh Kelly, Chief Data Officer at The Economist, began his career as an economist in the Irish government. Although he did not recognise it at the time, policy economics proved a strong foundation for a future in data and AI. While the context was different, it helped him develop capabilities that continue to shape his leadership today: statistical rigour, causal thinking, influencing non-technical audiences, navigating complexity, and effective storytelling.
Since moving into data and AI more than twenty years ago, Daragh has built a reputation for delivering step-change improvements in the value organisations derive from data. His work has focused on a combination of operating model transformation and technical innovation, rather than technology alone. Experience across a wide range of industries, geographies and business models has been particularly formative, enabling him to identify reusable patterns while remaining alert to situational nuance and context.
With a breadth of experience, Daragh resists the idea of a fixed playbook. His approach continues to evolve, and he notes that how he works today differs markedly even from two years ago. For him, effective leadership in data and AI depends less on codified frameworks and more on personal attributes: curiosity, humility, a low tolerance for stagnation, and a willingness to invest the time and effort required to keep learning.
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?
“I would highlight a few things that have always been important and are becoming more so.
“Learning Rate: I think a combination of curiosity, humility, a low boredom threshold and a willingness to do the work to learn new things is important. I find my success is a function of my learning rate and the speed with which I can adapt.
“Boldness: An excitement and passion for new frontiers and the willingness to go early and go fast toward those frontiers.
“Value Orientation: There is a reason why 80-90% of AI initiatives fail to deliver value, or even to move outside the POC phase. That reason is that they weren’t really designed to do so. A focus on value delivery, however that is defined, remains at the core of the job.”
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?
“Learn to write well. Read prose and poetry by people who write beautifully. Practice the craft of writing well. Don’t write in PowerPoint because presentations and bullet points are the enemy of clear thinking and communication. Write in prose instead. Writing isn’t just a way of communicating, it’s an aid to thinking and to self-awareness so you’ll see a benefit even if you never share what you wrote with anyone else.”