| | 9 FEBRUARY 2026While AI agents are clearly a major trend, the ability to support them with solid data practices will define who succeeds in this next phase of innovation.Leading Through Strategy and ExecutionOne area the company has been focusing on consistently is data governance. We already have strong foundations, especially around compliance and regulatory requirements. Working in a highly regulated industry, Philip Morris pays close attention to rules and data handling, often more than companies in other sectors. That focus is deeply embedded in how we operate.As we continue investing in AI, governance becomes even more important. It is not just about managing data properly but also about how we govern AI itself. AI governance must ensure that our solutions are responsible, controlled and aligned with internal standards and external regulations.We are continuously evolving this. As AI becomes more integrated into business processes, our approach to governance is expanding with it. We see it not only as a safeguard but also as a strategic element that ensures our AI efforts remain sustainable, efficient and aligned with our broader responsibilities.Adapting to the Future of Data and AnalyticsI believe technological solutions will become much easier to use in five to ten years. The technical complexity will be simplified, making tools more accessible. What will matter most is the ability to understand business strategy and translate it into data-driven solutions. The role of data professionals will shift from focusing on technical details to becoming strong connectors between business needs and data capabilities.I see myself and others in this space becoming more involved in business discussions, speaking the language of strategy and aligning it with the right data approaches. The ability to bridge this gap will become essential.At the same time, I believe data quality and data governance will remain critical. As companies continue to handle sensitive customer and employee data, the need for structured and compliant data practices will only grow. No matter how advanced the tools become, these areas will remain at the core of responsible and effective data work.I advise anyone entering the data space to learn core languages like SQL and Python, and to build a strong foundation in statistics. No matter how tools evolve, these foundations will remain essential. Being able to speak both the data and business languages and knowing how to connect them to solve real problems will be the most valuable skill in the years ahead. Being able to speak both the data and business languages and knowing how to connect them to solve real problems will be the most valuable skill in the years ahead.
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