Eloy Sasot is Chief Data Officer at ASML, with a career defined by curiosity and a willingness to work across boundaries of industry, geography and discipline. His experience spans nine sectors, including B2C, B2B and government, and has taken him through multicultural environments across Europe, Asia, and the Americas.
Eloy began his career in a highly technical setting at the European Space Agency, where he published scientific papers on space weather and worked as a spacecraft orbit coder. Seeking to connect deep technical expertise with real-world business impact, he complemented his Master’s in Mathematical Engineering with an MBA. This combination opened the door to transformation roles across diverse domains, from change programmes in wind energy to global pricing leadership in financial services at American Express.
His first end-to-end data leadership role came at News Corp, where he built a data-driven function from the ground up and later led it globally. He went on to spearhead global data and AI transformation at Sodexo, focusing on strategy, delivery and capability building at scale. Subsequently, as Group Chief Data and Analytics Officer at Richemont, he helped shape how data and AI could support sustainable, next-generation luxury retail.
In 2023, Eloy joined ASML as Chief Data Officer. Beyond being Europe’s largest company by market capitalisation, ASML plays a foundational role in enabling the global data and AI ecosystem.
Across his career, Eloy has learned that the greatest challenges in data and AI are rarely technical. Instead, they centre on trust, incentives, timing and helping organisations learn effectively without repeatedly relearning the same lessons.
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?
For me, effective data and AI leadership rests on three core qualities: purposefulness, adaptability, and curiosity.
“Purposefulness starts with a clear ‘why’. Leading data and AI transformation is demanding, and resilience comes from believing you are serving something larger, enabling stakeholders to embrace change while building a sustainable ecosystem for long-term growth, not just short-term value.
“Adaptability is the ability to balance strategic direction with operational delivery, while adjusting to shifting contexts. In my organisation, this means navigating high growth alongside cyclical market dynamics. Earlier in my career, I underestimated how much leadership time is spent on translation between technical teams, executives, and external stakeholders and how critical that translation is to momentum.
“Finally, deep and humble curiosity is essential. While we have learned a great deal about data and AI over the past two decades, recent advances require thoughtful adaptation.”
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?
“Think twice before going for it – and I mean that sincerely.
“Driving data and AI transformation at C-suite level requires a level of commitment that only makes sense if it is fuelled by purpose and a genuine appreciation for the craft. By nature, data and AI leaders are often misunderstood for long periods both in terms of why change is needed and what it truly takes to deliver it. This is frequently compounded by under-resourcing that only corrects itself over time.
“For some, this ambiguity and resistance can be exhausting. For others, it becomes a source of creative tension and innovation grit. Be honest with yourself about which camp you fall into. If you’re still drawn to the role after that reflection, you’re probably ready. And when it clicks, it can be beautiful.”
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