How Roche drives AI outcomes in a changing world

AI forces organizations to make consequential decisions during uncertainty. Roche chief digital and technology officer Wafaa Mamilli says this is the new leadership imperative. She believes success depends not on certainty but building the right foundations: trusted data, governance that enables speed, upskilling the employee base, and focusing on outcomes. At Roche, that approach drives applications ranging from kidney disease prediction and digital pathology, to new ways of discovering drugs and coaching people leaders. The challenge today, Mamilli says, is building organizations that can learn, adapt, and deliver value while the future unfolds, rather than predicting what’s next.

How is Roche using AI to drive growth and impact?

Our overarching mission is to prevent and cure diseases, and improve patient outcomes while reducing structural healthcare system costs. Data and AI are foundational enablers of this strategy. The high-quality data we’ve been assembling throughout our more than 125 years are part of this foundation.

We’re using data and AI to quickly make sense of a massive amount of information — including genomic sequences, medical images, clinical records, and complex biology — and turn it into real medical breakthroughs at every stage of the patient journey.

We understand AI is a human and change management challenge, not a technical one. That’s why we prepared a holistic approach, which includes what we call everyday AI, to upskill our employees and embed AI in everyday work; reshaping with AI, which is reimagining our end-to-end processes; and our big ideas, which are large transformational investments.

Can you detail some real examples that bring this strategy to life?

We’re building AI tools across the entire value chain. Our enterprise platform, Galileo, includes internal generative AI tools, search engines, and compliance-safe sandbox environments.

We also have custom AI-powered coaching tools to help managers prepare for staff conversations. In our diagnostics business, we implemented an AI algorithm called Kidney Klinrisk to help physicians predict the risk of chronic kidney disease progression before irreversible damage.

Plus, we use AI image analysis in our digital pathology to assist pathologists in identifying cancer cells faster, and in R&D, we have AI-powered simulations to model clinical trial scenarios.

In manufacturing, we’ve deployed digital twins of our production lines, reducing development cycles by two to four times, and cutting technology transfer times by 50%. In drug discovery, we allow scientists to model over 100 experiments, compared to five in a physical plant.

But none of these examples imply that we’ve figured it out. We need to be confident and humble at the same time, but we’re still working through this just like anyone else.

How do you balance AI innovation and risk?

We develop life-saving medicines and vital diagnostics that directly impact human health, so we’ve always balanced speed and safety with the right governance framework. To position governance as a velocity enabler, we established a dedicated, horizontal framework focused on AI risk and ethics, and an AI strategy and governance function to ensure we leverage models responsibly.

But as important, I personally engage in understanding what’s at stake, because everything is changing overnight. That attention to detail is critical, because our job is to align, comply, and govern while allowing speed. We act with speed, assess, experiment, and then say yes or no to scaling the innovation. That’s how we lead this from the executive team down.

What changes have you made to your IT organization for this new wave of AI innovation?

I renamed my organization Roche Digital Technology, RDT, to position us as powering the business with digital tech and AI in a federated model. I created dedicated AI and data teams, which report to two new roles in RDT, chief AI officer and chief data officer. I intentionally made these two different roles because we need our data structured and ready for what we want to do with AI. There’s no AI without data, and we have foundational work to do there.

Think of the AI team as what the market calls forward deployed engineers — they work with all the other teams to re-engineer processes and deploy AI, while feeding the AI platform and tools teams so the platforms evolve to match the enterprise and marketplace. Enterprise architecture and portfolio governance are capabilities teams that support the full organization.

Describe the profile of the CAIO, as you’ve defined it on your team.

The AI officer is business outcomes driven and passionate, as well as tech savvy with high learning agility. This leader needs an entrepreneurial, risk-taking mindset, an ability to deliver, and deep process knowledge.

Remember business process re-engineering? There are some similarities here. We need people who can think through the workflow, not just what’s implemented in the systems but the actual workflow, what people do offline between systems, and think work and workflow, which we’ve never fully figured out. We need people who can step back, look end-to-end, and, with the knowledge of AI, reimagine what a process can look like now. So business process savviness is critical.

What advice do you have for tomorrow’s CIOs?

You have to be both a business and a technology leader. I call that a business minded technologist since business fluency is table stakes. You need to understand strategy, customers, and the economics of how the enterprise creates value. But particularly, in this moment, deep technology acumen matters enormously. The CIO has to understand not only what technology can do today, but what’s becoming possible tomorrow, and translate that into choices for the enterprise.

This is why I believe this is the most exciting time to be CIO. Technology and now AI is no longer enabling the business. It’s reshaping how companies operate, how decisions get made, how people work and increasingly how value is created.

So my advice for tomorrow’s CIOs is don’t be passive or apologetic about being a technologist. If there isn’t a chair for you at a table, bring your own by bringing an enterprise perspective and insights others can’t.

Few roles have the same vantage point across the organization. Use it. Connect the dots across functions. Understand the technology deeply enough to challenge assumptions. Bring confidence and humility, have the courage to make choices, and recognize that the hardest part of transformation is rarely the technology itself but bringing people with you.