With more than 25 years across data engineering, analytics, and AI, Tekin Mentes currently serves as Chief Data and AI Officer at Shell. His trajectory has followed the technology shifts rather than the job titles, from software development at Oracle, through business intelligence leadership at Airbus and 3M, to senior data roles at Logitech and LeasePlan.
A formative chapter came early for Tekin, building a large-scale business intelligence competency centre that delivered tangible operational outcomes including materially faster financial closes, before being deliberately dismantled and rebuilt under a newly appointed Chief Data Officer. That reset, driven by the emergence of new frameworks and large-scale data platforms, reshaped how Tekin understood the role of data leadership: less about optimisation of what exists, more about anticipating structural change.
Since then, he has worked through successive waves of big data, cloud, and now AI, leading data and analytics at LeasePlan before joining Shell four years ago. At Shell, his remit deliberately spans both data and AI, reflecting his long-standing belief that separating the two is increasingly artificial.
Unlike many CDOs who come up through governance-heavy or banking-led models, Tekin’s background is deeply technical. He has consistently reported into technology leadership rather than operating as a parallel data function. In an environment where organisations are fragmenting responsibilities across CDOs, CAIOs and other roles, he sees this integrated model as a practical advantage, and one reason Shell chose to formalise the Chief Data and AI Officer role.
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?
“Open-mindedness is the biggest trait,” Tekin stated, particularly in the current AI landscape. “We don’t even know what’s coming next: agentic AI, robotics, quantum, maybe something else.” For him, staying open does not mean chasing everything new. “The most important thing is not to jump on it,” Tekin added, “but to approach it with a critical mindset and really ask whether this is valuable or not.”
That balance was shaped early in his career. “Gene Glassman as a mentor made me think out of the box,” he reflected. “Things will change over time.” Since then, Tekin’s instinct has been to watch where the hype is forming and assess whether it is substantive. “We’ve seen hypes before with metaverse, AR, and blockchain. I’m not saying they had no value, but they’re not having the impact AI is having right now.”
Critical thinking matters just as much as technical awareness. “Being open-minded, aware of what’s happening around you, but applying critical thinking, that’s important for every leader, and actually for every person.” Tekin sees this clearly inside large, traditional organisations. “People are scared on the ground about what’s happening with AI… If we can teach them that these tools are here to make life easier, faster, and support better decision-making, they should be using them, not afraid of them.”
That places responsibility squarely on leadership. “We need to prepare our workforce for the future,” Tekin said. “Being visible, walking the talk, that’s how cultural change happens.” Without that shift, he believes, culture itself will become the obstacle in front of the next wave.
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?
“The most dangerous statement in a company is ‘we’ve always done it this way’,” Tekin said. It’s a line he puts on a single slide on day one with every new team and it frames his non-traditional advice to aspiring data and AI leaders.
For him, progress depends on actively resisting comfort. “Change is the thing that triggers evolution,” Tekin said. “That’s what I enjoy.” When he joins an organisation, he is deliberate. “I choose companies that are genuinely on a transformation path. If they’re not, I don’t join.” He will typically spend three or four years driving change, learning what the next wave demands, and then reassess. “If a company flattens out with no innovation and no urgency, I move on.”
That mindset is as much about personal growth as organisational impact. Tekin reflected candidly on staying too long earlier in his career. “I stayed nine years. Everything was fine. I was in my comfort zone. I even thought I could retire there. That was the wrong decision.” Each subsequent move was driven by learning. “I learned Hadoop when big data arrived. Then cloud at Logitech when AWS was coming. Then AI.” Had he stayed put, “maybe I would have learned it five years later, or not at all.”
Tekin’s advice is simple, but uncomfortable. “Follow the change. If you stay too long, your motivation gets stuck, your knowledge gets stuck, and so does your career.”
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