Session 10 - Moderna Democratizing AI
Hierarchy
Define: Generative AI
Archive
Building Internal AI Capabilities
Moderna has long described itself as a “technology company that happens to do biology.” Even before generative AI, the company invested heavily in cloud infrastructure, integrated data systems, automation, and analytics to support its mRNA platform and an experimentation-heavy R&D process.
This session focuses on how Moderna approached AI democratization—not simply by introducing new tools, but by enabling broad, everyday use of AI across the organization. Moderna provided employees with self-service AI platforms, embedded AI into workflows, and invested in training to raise AI literacy beyond technical teams. The goal was to accelerate experimentation, learning, and productivity at scale.
At the same time, Moderna operates in a highly regulated environment where accuracy, accountability, and compliance are critical. As AI use expanded, the central challenge became how to balance decentralized experimentation with centralized governance. The case invites you to examine how Moderna designed its organization, platforms, and governance mechanisms to support widespread AI use while managing risk. Read the case below to ger prepared.
Case: Moderna: Democratizing Artificial IntelligenceDownload Moderna: Democratizing Artificial Intelligence
Now that you have read the case, consider the following case questions and bring your answers to class.
| Case Preparation Questions: 1. What does “AI democratization” mean at Moderna, and how does it support their R&D strategy? 2. What organizational changes and technological changes made Moderna’s AI integration possible? 3. What challenges or risks does Moderna face as it scales AI adoption? 4. How should Moderna balance centralized AI expertise with decentralized AI use? |