The Next Frontier for AI in Health Care Is the Factory Floor

As therapeutic pathways grow increasingly complex, manufacturing modalities diversify and supply networks face mounting pressure to regionalize, the stakes for operational excellence have never been higher. In this evolving landscape, health care innovation will deliver its full value only when medical breakthroughs reach patients faster and more reliably — at a scale and cost that are sustainable for health care systems and budgets worldwide.

We have entered a new era, with artificial intelligence (AI) driving one of the fastest technological transformations in modern history. According to McKinsey's latest “State of AI” report,¹ 88% of organizations now use AI in at least one business function, a milestone that signals a fundamental shift in how enterprises operate.

Recent data from the U.S. indicate how health care has emerged as the vanguard of this movement, leading the change with an adoption pace 2.2 times faster than other sectors. This is no longer a pilot phase: With 75% of health care systems and 72% of physicians using AI in their daily workflows, technology has become foundational to the practice of medicine — a shift also mirrored by patients.

In addition, the impact of AI is already highly visible in drug discovery, helping scientists accelerate early drug development and reduce the risk of failure. Today, AI for drug discovery and development is the most widespread application in the biopharmaceutical sector, according to NVIDIA’s “State of AI in Healthcare and Life Sciences: 2026 Trends.”²

Yet drug discovery is only the beginning.

For innovation to reach patients in our current environments, biopharmaceutical manufacturing and the global supply chain must evolve as quickly as the science itself. As an industry, we must accelerate investments in AI-powered manufacturing and supply. But to transform our industry, the challenge also lies in preparing the workforce that operates these increasingly intelligent systems.

To ensure that production becomes more resilient, the factory of the future must be able to anticipate supply chain disruptions and adapt quickly to meet changing public health needs. Building such systems requires coordinated action across industry, governments and education systems.

Intelligent factories will define the next phase of health care

Pharmaceutical manufacturing is undergoing a profound transformation as advanced therapies require more flexible, digitally integrated and resilient production systems.

AI is increasingly playing a central role in meeting these demands and fundamentally reshaping how factories are designed and operated. At Sanofi, we’re embracing this transformation. Using digital twins, we simulate production environments and optimize systems before a single brick is laid, accelerating facility design, construction and technology transfer to bring new capacity online faster.

By connecting data across our global operations, we’re transforming supply chain and inventory management. Predictive analytics and advanced telemetry enable us to anticipate equipment behavior, prevent breakdowns or failures and optimize performance in real time. Our AI-powered yield analytics platform analyzes thousands of live data points across production lines, enabling us to replicate optimal batch performance at scale. This approach is delivering production yield gains of 5% to 10%, translating into more affordable medicines manufactured, with millions of additional doses made available to patients, without expanding our physical footprint.

This is happening not only at Sanofi but across the whole pharmaceutical industry. AI-powered factories are becoming strategic infrastructure. Eli Lilly is currently building a new AI supercomputer, Novartis uses machine learning for real-time monitoring of its plants, Merck utilizes AI in manufacturing to decrease false reject rates in quality assessments and Moderna leverages AI-based tools to improve quality control systems.

Why empowering teams matters as much as technology

Yet technology alone will not transform manufacturing.

Integrating AI into highly regulated manufacturing environments remains complex, requiring new industrial capabilities and employees equipped with the skills and expertise to operate these systems safely and reliably.

As in all major transformations, the success of this next-generation technology and AI-enabled innovation will ultimately depend on the people who run them. The goal isn’t to replace the workforce but to augment human expertise, to reshape, not necessarily replace, critical human oversight.

A recent report by the BCG Henderson Institute estimates that 50% to 55% of roles will be redefined by AI over the next two to three years. In the factory environment, this shifts the focus from replacing human labor to augmenting it, where AI handles routine execution while humans remain central to tasks requiring judgment, coordination and complex problem-solving. While AI identifies patterns and generates insights within complex data sets, engineers and operators interpret those insights and translate them into real-time decisions. Human oversight ensures transparency and accountability in a highly regulated environment.

As factories become more digitally enabled, roles across manufacturing are evolving. Operators increasingly monitor performance through real-time advanced analytics and dashboards. Engineers rely on digital twins and simulations to optimize processes before scaling them. Quality teams leverage algorithmic transparency and data governance frameworks to support science-based, data-driven decision-making.

Data literacy, digital risk awareness and critical reasoning are rapidly becoming core capabilities for the industrial workforce.

Turning transformation into collective progress

Scaling intelligent manufacturing will require coordinated action across industry, education systems and governments, to develop the skills needed to operate the factory of the future.

Pharmaceutical companies must invest in digital capabilities across their organizations, fostering innovation and collaboration among research and scientists, process and data engineers, and operational leaders. Equally important is building an integrated approach with suppliers and original equipment manufacturers to create a smart, AI-enabled ecosystem that supports increasingly resilient, agile and cost-effective supply chains.

Engineering schools and vocational programs have the opportunity to further integrate AI, data analytics and digital manufacturing into their core curricula while promoting partnerships with industry.

And finally, governments play a critical role by supporting industrial innovation ecosystems and investing in large-scale reskilling initiatives that accelerate the transition toward intelligent and future-ready industrial networks.

When industry, academia and policymakers move together, the conditions for manufacturing excellence and resilient supply chains can emerge far more quickly. The opportunity now is to elevate manufacturing and supply to a defining pillar of health care innovation, enabled by AI and increasingly driven by data. As we face increasing geopolitical tensions and growing therapeutic complexity, resilient manufacturing systems are becoming essential to public health.

And the time is now. This is the time to shape the future and define what modern health care manufacturing can — and will need to — become.

Brendan O'Callaghan is the executive vice president of manufacturing and supply at Sanofi.

References

1. McKinsey & Company. The State of AI in 2025: Agents, Innovation, and Transformation. November 5, 2025. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai?

2. NVIDIA. State of AI in Healthcare and Life Sciences: 2026 Trends. 2026. https://www.nvidia.com/content/dam/en-zz/Solutions/lp/survey-report/healthcare-state-of-ai-report-2026-4559650-web.pdf