Executive summary. Sanofi turned an ambitious vision, to become the first biopharma company powered by AI at scale, into a leadership-driven transformation. Through DriveDigital, developed with HEC Paris Executive Education, AI moved beyond technology teams and became part of leaders’ everyday mandate. Starting with the Top 150 executives and expanding to 2,240 senior leaders, the programme transformed learning into action, generating 224 AI use cases and a 97% Net Promoter Score. More importantly, it helped shift leaders from discussing AI to experimenting with it: demonstrating how leadership ownership can turn technological ambition into sustained organisational adoption and business impact.
Key takeaways
- Sanofi made Data and AI a leadership responsibility, starting with its Top 150 executives to build shared understanding, accountability and sponsorship before expanding DriveDigital to 2,240 senior leaders.
- DriveDigital connected learning directly to business priorities, with leaders developing and pitching real AI applications. The programme generated 224 use cases, with several progressing into strategic initiatives, securing investment and contributing to commercial results.
- The programme helped bridge the gap between AI strategy and execution by shifting leaders from discussing AI to experimenting with it in their own functions, while building greater understanding of its opportunities, risks and practical applications.
In 2022, Sanofi’s ambition was already clear. The company had committed itself to becoming the first biopharma organisation powered by AI at scale. Data and AI sat at the heart of its strategy, with applications spanning research, manufacturing, supply operations and commercial activities. Executive sponsorship was firmly in place, and significant investments had already been made in digital capabilities.
Across the business, teams could already see the opportunities. AI promised faster discovery, better-informed decisions and new ways of working. It had become part of the strategic conversation. What remained uncertain was how that conversation would translate into coordinated action across a global organisation.
The company was not facing a shortage of content or expertise. Sanofi already offered digital learning resources, and access was widely available. Participation, however, remained low. Completion rates for broader digital learning initiatives hovered around 3%, suggesting that the challenge was less about access to knowledge than about creating ownership. People could find the information. Far fewer were taking responsibility for applying it.
Within many organisations, AI is still regarded as a specialist topic. Technical teams build capabilities. Data experts design solutions. Business leaders support the effort from a distance. Sanofi’s leadership began to see the limits of that model. Digital initiatives were emerging across the organisation, but without stronger sponsorship and a shared understanding among decision-makers, scaling those initiatives would remain difficult.
Technology was advancing rapidly. Leadership ownership was progressing much more unevenly.
Starting with the People Who Shape Decisions
When organisations launch large transformation programmes, the instinct is often to begin by strengthening technical capability. Sanofi took a different route.
The company started with its Top 150 executives. The decision reflected a simple conviction: transformation would gain traction only if senior leaders developed a common understanding of what Data and AI meant for their businesses, their teams and the decisions they made every day. The first objective was alignment, followed by accountability and sponsorship. Without those elements, individual initiatives would continue to develop in parallel rather than contribute to a broader movement.
This led to the launch of DriveDigital, developed jointly with HEC Paris Executive Education.
The programme combined adaptive online learning, collaborative work and face-to-face sessions, but its real value lay elsewhere. Participants explored business questions, identified opportunities within their own areas of responsibility, and examined how Data and AI could contribute to priorities already on their agenda.
The discussion quickly moved beyond technology itself. Leaders debated priorities, examined trade-offs and explored where data could improve decisions and where AI could create business value. Perhaps more importantly, they began discussing these questions using shared references and common assumptions.
Emmanuel Frenehard, Chief Digital Officer at Sanofi, summarised the ambition succinctly:
“Our ambition is to become the first biopharma company powered by AI at scale. This requires more than technology. It demands leaders who own data transformation as a strategic mandate.”
That idea, that Data and AI should become part of every leader’s mandate rather than the responsibility of specialists alone, became the organising principle of the initiative.
When Learning Meets Real Business Problems
One of the decisions that shaped DriveDigital was its emphasis on practical application.
Rather than discussing AI in generic terms, participants worked on challenges drawn from their environment. Teams developed ideas, tested assumptions and explored opportunities that could generate value for the business. As the programme progressed, those projects became increasingly central to the experience.
The strongest concepts moved into “Shark Tank” sessions, where leaders presented their proposals before executive juries.
Several projects gained visibility well beyond the programme itself. Blockbuster Booster, for example, explored how Data and AI could support the identification of future blockbuster products. Following its presentation to the Executive Committee, the project became part of strategic discussions within R&D and received dedicated resources. Another initiative, the Turing Project, focused on improving interactions between commercial teams and healthcare professionals through AI-driven recommendations. What began as a programme project evolved into a broader business initiative.
These examples mattered because they showed a direct connection between leadership development and enterprise priorities. Ideas did not remain inside the learning environment. They entered business discussions, secured executive sponsorship and, in some cases, attracted substantial investment.
Solving the Problem Between Strategy and Execution
The first phase delivered something Sanofi considered particularly valuable: executive alignment.
It also exposed the next challenge.
Executive commitment is essential, but large organisations rarely transform through executive commitment alone. Between strategic intent and operational reality sits a broad population of leaders responsible for translating direction into action. They manage teams, allocate resources and decide which priorities survive the pressures of day-to-day execution.
Many transformation efforts stall at precisely that point.
Sanofi recognised the risk early. Executive sponsorship had become stronger, but lasting adoption required a much wider community of leaders capable of carrying the effort into their own functions and geographies. The company, therefore, expanded the initiative.
The rationale extended well beyond increasing participation. The objective was to strengthen the organisation’s ability to translate strategic ambition into operational decisions. Senior leaders worked on issues ranging from AI governance and ethics to data-driven decision-making and experimentation. They developed use cases linked to their own areas of responsibility and presented their work before executive audiences. As responsibility spread more widely across the organisation, ownership spread with it.
Over time, another pattern began to emerge. Conversations became more concrete. Leaders grew more comfortable discussing the opportunities, limitations and risks associated with AI. Project teams found executive sponsors more easily. Data entered strategic discussions earlier and more often.
What Changed
Some results can be measured directly. By 2026, DriveDigital had engaged 2,240 senior leaders and generated 224 AI use cases. Participant satisfaction reached a Net Promoter Score of 97%. Several initiatives progressed into portfolio-level decisions, while selected commercial projects contributed to double-digit sales uplift. The Turing Project alone is expected to make a substantial contribution to commercial performance.
The numbers tell only part of the story. The more revealing changes appeared in behaviours.
Julien Durand, Senior Vice President and Chief Ethics & Compliance Officer at Sanofi, describes one of the most significant shifts in surprisingly simple terms:
“One important impact was reducing the fear around AI. People began to understand both the opportunities and the risks much more clearly.”
Fear rarely appears in transformation dashboards, yet it shapes adoption every day.
Durand also observed a noticeable shift in how leaders approached the subject:
“The work around the use cases encouraged leaders to start experimenting with AI in their own functions. It helped them move from talking about AI to identifying concrete applications in their areas.”
That shift from discussion to experimentation may ultimately explain the broader impact of the initiative.
Many organisations now face a similar challenge. Interest in AI is widespread. Pilots continue to multiply. Investment keeps growing. The harder question lies elsewhere: how can organisations spread ownership quickly enough to keep pace with technological progress?
Sanofi’s experience suggests that executive sponsorship, shared understanding, and access to knowledge matter. Yet none of these elements appears sufficient on its own. Transformation accelerates when leaders see Data and AI as part of their own mandate, rather than someone else’s expertise.
At Sanofi, that shift helped bridge the gap between strategy and execution. The technology was already in place. The harder task was building the leadership capability to turn ambition into sustained adoption.
