Quick answers
What is Moderna's AI strategy?
Moderna's AI strategy rests on four pillars: vision led from the CEO (not IT), workforce-wide AI literacy before tool rollout, integrated cloud-native data infrastructure built over a decade, and a structural merger of HR and IT into a single People and Digital Technology function.
How many AI tools has Moderna built?
Moderna has deployed hundreds of internal AI tools - thousands of custom AI assistants across every department - built on a combination of OpenAI, AWS, and proprietary platforms.
Why did Moderna merge HR and IT?
To manage a combined human-AI workforce. Moderna's leadership recognised that AI changes how teams are structured, hired, and developed - so the function that designs the org and the function that deploys the technology need to operate as one.
What can a smaller business learn from Moderna's AI approach?
Three things scale down: lead the AI vision from the top, invest in literacy before tooling, and build (or buy) integrated data infrastructure before deploying advanced models. The org-merger move is harder to copy but the principle - aligning people and technology - applies at any size.
In early 2024 OpenAI published a case study about Moderna's use of ChatGPT - fast adoption, hundreds of internal tools. Early case studies make me cautious; the real test is what happens next. So I kept watching. It didn't fade - it deepened into structural change.
By mid-2025 Moderna had expanded its work with the R&D platform Benchling into a single "AI-ready" environment for hundreds of scientists - re-architecting the foundation of research itself, not just bolting on chatbots.
AI is creating extraordinary opportunities in science, but realising its full potential requires entirely new ways of working.
- Wade Davis, SVP, Moderna
Moderna's success comes from a CEO-led vision that treats AI as a core business function, not an IT project. They educated the entire workforce before deploying advanced tools, creating demand from the ground up. Their most radical move was merging HR and IT to manage a combined human-AI workforce. And none of it would have worked without a decade of cloud-native, integrated data infrastructure.
Their strategy rests on four ideas:
1. Vision from leadership, not IT. CEO Stephane Bancel frames AI as the main way to scale the company's mission - aligning everyone and securing investment. 2. Culture before code. They educated and empowered the whole workforce (the AI Academy) before rolling out advanced platforms, creating organic, employee-driven demand. 3. Build integrated systems. A best-of-breed mix (OpenAI, AWS, custom platforms) on a cloud-native foundation laid a decade ago - no data silos. 4. Redesign the organisation. They merged HR and IT into a single "People and Digital Technology" function, built for human-AI collaboration.
01The digital foundation
Moderna's success wasn't overnight - it was a decade-long "digital-first" strategy. Their core philosophy: mRNA is information, the "software of life," so medicine development could become a repeatable platform. That demanded a fully digital infrastructure, so they went cloud-native from day one, partnering with AWS over a decade ago for compute, ML tooling, and analytics - standardising on AWS streamlined managing massive scientific datasets by an estimated 70%.
A data mesh architecture treats data as a "product" with clear ownership and central governance, instead of brittle redundant pipelines. The payoff: where many companies stall for years cleaning up siloed data, Moderna built its first internal AI tool, mChat, in two weeks. Your return on AI is directly linked to the quality of your underlying data infrastructure.
02Leadership, culture and people
Technology is just a tool; its value comes from the people who use it. Bancel positions AI as a force to redesign every process - the goal is scale, not cost-cutting: launch up to 15 new products in five years with a lean team.
The vision is for a few thousand people to have the impact of 100,000 - AI making people more productive, not replacing them.
In late 2021 they launched the Moderna AI Academy with Carnegie Mellon (later Coursera) to build AI literacy across everyone, not a select few - in the first 20 months, 2,000+ learners logged 14,700+ hours, with a 30% average knowledge increase. Then they put tools in people's hands: mChat (built in two weeks) hit 80%+ adoption within months. An "AI prompt contest" surfaced the top 100 power users, who became internal champions running office hours and a busy Slack forum. The result: employees started asking for AI solutions themselves.
03How Moderna uses AI day-to-day
The strategy is embedded in daily work across every department - not theory, deployment.
AI in every department
From the research engine to the unlikeliest power users - and the metrics that prove it.
04Why custom GPTs were the game-changer
Choosing ChatGPT Enterprise in early 2024 wasn't about a better chatbot - it was a decentralised development platform over a centralised tool. The built-in GPT Builder let any employee become an AI developer, and that solved the "last mile":
- Hyper-relevance: a general AI doesn't know your jargon. Legal built a "Contract Companion" on their own templates; HR a "Benefits Assistant" on their handbook.
- Grassroots innovation: instead of central IT guessing what 6,000 people need, an analyst could build a "Data Formatting GPT" in an afternoon - no dev queue.
- Ownership drives adoption: people use the tools they built. Legal's own contract tool is why they hit 100% adoption first.
The difference between a customisable platform and a fixed tool was the difference between deploying 10 tools and sparking 3,000+. Here are ten representative examples.
| Custom GPT | Department | What it does |
|---|---|---|
| Dose ID GPT | Clinical Dev | Analyses clinical datasets to recommend optimal trial doses with rationale and charts - humans make the final call. |
| Contract Companion | Legal | Summarises contracts and answers questions about them, cutting hours of manual review. |
| Policy Bot | HR / Ops / All | Instant, accurate answers on internal policy - less admin, better compliance. |
| Earnings Prep Assistant | Brand & Comms | Automates parts of the quarterly earnings slide deck for consistent investor materials. |
| Brand Storyteller | Brand / IR | Translates biotech terminology into clear language for investors and media. |
| Self-Review Assistant | HR | Helps employees summarise accomplishments for annual reviews - consistent, faster. |
| US Benefits Assistant | HR (US) | Guides employees through annual benefits elections, cutting HR support tickets. |
| Equity Comp Explainer | HR | Explains options vs RSUs and grants - better understanding, fewer queries. |
| "Ask HR" Gateway | HR | A virtual HR router - directs questions to the right specialised GPT or a human. |
| Performance Mgmt Guide | HR / Managers | Targeted help on reviews, goal-setting and evaluation standards. |
The rollout, year by year
From a two-week chatbot to an org redesign and an AI-ready research platform.
05The radical move: merging HR and IT
In late 2024 Moderna merged HR and IT into one function - People and Digital Technology. In an AI-powered company, the silos separating people strategy from technology strategy are a barrier: choosing an AI agent (IT) directly reshapes roles and skills (HR). So they shifted from "workforce planning" to "work planning": what work needs doing, and what's the best mix of human talent and machine intelligence to do it?
They created a new C-suite role - Chief People and Digital Technology Officer - and gave it to Tracey Franklin, former head of HR. Putting an HR leader in charge signals that the central challenge of the AI era is human-centric organisational design, not just technology. It structurally supports treating AI agents as teammates, not passive tools.
It forces a level of integrated thinking that's impossible in a siloed organisation - designing the company for the next era of work.
06Governance, risk and ethics
Giving powerful tools to every employee is fast - and risky in a regulated industry. The core tension is empowerment versus control: empowerment drives innovation; central control offers oversight but slows progress. The risks are real - hallucinations, misuse in critical processes (trial dosing, performance reviews), algorithmic bias, and data privacy. Moderna manages them with a multi-layered framework:
- An AI Code of Conduct grounding responsible use in corporate values.
- Human-in-the-loop for high-stakes decisions - the Dose ID GPT informs, but humans decide.
- Structural and cultural guardrails - the HR/IT merger gives unified oversight; the AI Academy includes mandatory ethics training.
- Proactive regulatory engagement - informing bodies like the FDA about AI in core processes.
07Seven lessons from Moderna
The foundational decisions for AI success are made now.
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