Paola Cagliani is Group Chief Data and AI Officer at Admiral, where she leads the company’s data and AI agenda as a core driver of business strategy and value creation across multiple European markets.
She began her career in statistics and data analytics at IBM, building a strong foundation in problem-solving and insight generation. From there, Paola moved into roles that placed her directly within business lines rather than at arm’s length from them. At Vodafone, she led major initiatives to unlock the commercial value of data, driving strategic transformation and improving decision-making. She later spent five years at Eni, leading a large-scale data transformation that included migrating systems to the cloud, applying machine learning at scale, and monetising data through predictive and commercial use cases.
A defining feature of Paola’s career has been a business-first approach to data. Rather than simply supporting the P&L, she has held direct commercial accountability, using data-driven methods to optimise performance well before AI became mainstream. This perspective proved critical during her time as European CIO and CDO at Admiral, where success depended on abstracting away from technology choices and focusing relentlessly on solving core business problems.
Today, as Group Chief Data and AI Officer, Paola leads the delivery of a unified data platform supporting machine learning and advanced analytics at scale, while accelerating the adoption of generative AI. She sees the boundary between business and data strategy as increasingly blurred, with her role focused not just on execution, but on co-shaping Admiral’s future direction through data and AI-led innovation.
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 believe the two most critical traits for effective data leadership today are resilience and strategic translation (the ability to speak both tech and business fluently).
“In my organisation, resilience has undoubtedly been the most influential. Driving transformation in a highly successful, federated company is paradoxically difficult; stakeholders often resist change precisely because the status quo feels comfortable. It requires immense energy and courage to challenge established silos and drive a unified group agenda without alienating local teams.
“However, resilience must be paired with the skill of Translation. A CDAO must articulate why a centralised data platform or genAI governance matters to a CEO, not in terms of architecture, but in terms of P&L and speed-to-market.
“This combination has been vital for me. By translating complex technical shifts into tangible business outcomes, I was able to turn initial scepticism into advocacy. It allowed me to move the conversation from compliance to value, fostering a culture where business leaders no longer see data as an IT function, but as their own competitive lever.”
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?
“My advice is counter-intuitive for a data professional: Unlearn the need for certainty.
“We are trained to seek statistical significance, to validate, and to be precise. We use data as a shield to say, ‘The numbers say X’, but the C-suite operates in ambiguity. If you wait for the data to be perfect, the opportunity is gone.
“The leap to top leadership happens when you stop being the person who says, ‘We need more analysis’ and become the person who says, ‘Given the imperfect data, here is the bet we should take.’ To reach the C-suite, you must trade accuracy for velocity. You must have the courage to use data not to eliminate risk, but to take calculated risks. Stop being a validator of the past and become a navigator of uncertainty.”