Julie De Moyer is Chief Data Officer Beauty at LVMH, where she leads the Data and AI agenda across 15 Beauty Maisons, balancing global scale with the distinct identities of some of the world’s most recognised luxury brands.
Her perspective as a data and AI leader has been shaped at the intersection of commercial pragmatism and technical rigour. With an academic background in economics and early roles in product marketing and strategy, Julie quickly recognised that data and AI are not cost centres, but powerful catalysts for cultural and business transformation.
Formative experiences at organisations including the World Bank, Accenture and Nike reinforced a core lesson that even the most sophisticated algorithm delivers little value if it is not embedded into real human workflows. This insight has consistently guided her approach to leadership, prioritising adoption, usability and decision impact over technical elegance alone.
At LVMH, Julie has navigated the complexity of leading data and AI across a multi-brand, heritage-focused environment. Her role requires balancing centralised governance and standards with the unique “personalities” and creative autonomy of individual Maisons. This experience has deepened her belief that effective AI leadership is as much about empathy and influence as it is about technology and scale.
Julie’s focus has evolved from simply interpreting what data says to ensuring data empowers people to make better decisions. She brings a leadership style that respects tradition while driving modernisation, shaping a data-driven culture that aligns innovation with the values and craftsmanship at the heart of the luxury industry.
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 critical trait for an AI leader today is intellectual translation: the ability to turn complex technical constraints into strategic business narratives.
“In our organisation, change management has been the most influential skill. Data is often met with scepticism in creative-led industries. By focusing on ‘Augmented Intelligence’ (helping people do their jobs better) rather than ‘Artificial Intelligence’ (replacement), I was able to build the trust necessary to move projects past the pilot stage.
“Resilience is the second; AI projects often face data quality roadblocks. The ability to maintain momentum and stay focused on the long-term vision while solving messy, tactical data issues is what separates successful leaders from those who merely experiment.”
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 speak the language of the P&L, not the Python library.
“To reach the C-Suite, stop talking about models and start talking about margins. My non-traditional advice is to shadow a non-technical department, like Finance or Supply Chain, for a month. Understand their stressors, their jargon, and how they are measured.
“Aspiring leaders often try to impress the board with the sophistication of their AI. In reality, the C-Suite cares about three things: risk, revenue, and resiliency. If you can frame your data strategy as a direct lever for one of those three, your seat at the table is guaranteed.”