AstraZeneca continues to accelerate its transformation as a data-driven biopharmaceutical leader, expanding its global footprint and strengthening its commitment to more predictive, preventive, and personalized healthcare. The company now operates across 100+ countries and has announced a multi-year plan to expand manufacturing, bolster AI-enabled R&D, and advance therapies across oncology, respiratory, cardiovascular, immunology, and rare diseases.

With sustained double-digit investment in R&D, AstraZeneca’s strategy reflects a clear belief: AI and data are central to the future of life sciences.

In the first installment of this series, Brian Dummann, Vice President of Insights & Technology and Chief Data Officer at AstraZeneca, explored how AstraZeneca is democratizing AI and rewiring governance models to accelerate responsible innovation. The second installment discussed how the company is embedding responsible AI into its data governance foundations and empowering business leaders to measure value and scale transformation.

In this final part of his conversation with Nathan Turajski, Senior Director of Product Marketing at Informatica, Dummann turns to the future — exploring how AstraZeneca is upskilling its workforce, collaborating with an expanding innovation ecosystem, and preparing for an AI-powered shift across the entire healthcare landscape.

Building an AI-fluent workforce

As AI adoption accelerates across AstraZeneca, Dummann emphasizes that skill development can no longer be limited to traditional data teams. While the company has long invested in data literacy and data fluency programs, he notes that these typically reached employees closely involved in data creation and stewardship.

But AI, he stresses, is reshaping expectations across the enterprise. “We’ve actually done something pretty bold internally,” he says. “We’ve created an optional program for our employees to engage in AI. We call it ‘Thriving in the Age of AI.’ And it has been the most subscribed training program that is not a mandatory program in our history.”

More than 17,000 employees have already completed a level of certification, with many publicly celebrating their achievements on LinkedIn. Business units have introduced internal challenges, encouraging entire teams to reach “Silver,” the second tier of the program.

“This is people investing a fair amount of their time learning about AI and what it can do,” Dummann explains. “The effects of hallucination, the regulations, some of the limitations of what we can and can’t do.”

AstraZeneca is now designing more advanced tiers, including function-specific “Platinum” level training in partnership with external organizations, covering disciplines such as AI-enabled project management.

Dummann sees these graduates as the future internal catalysts: “We see this program ultimately as people go through the levels, creating our ambassadors that are going to be the change agents. But more importantly, bringing the entire IQ around AI up in the organization.”

For Dummann, AI literacy will soon become a core measure of enterprise readiness.

AI and data fluency converge

One of the unexpected benefits of this program, he says, is how AI upskilling naturally strengthens data literacy.

“In that AI training, we are pulling in some of the disciplines around data that were relevant,” he notes. By linking these capabilities, AstraZeneca is helping employees build a more holistic understanding of how data and AI interact to drive outcomes.

“By bringing up AI literacy, you also bring up data literacy and use that as the carpet or the coattails to ride on AI upskilling,” he adds.

He expects that by year-end, more than a third of the company may have completed a certification — an unprecedented scale of capability-building.

A broader innovation ecosystem

As AI evolves rapidly, AstraZeneca’s strategy intentionally avoids dependence on a single vendor or platform. Instead, Dummann describes a more diversified and outward-looking approach.

“We’re not going to get all of our AI from one partner,” he says. “And we’re not going to get all of our great ideas from just within the organization.”

To stay ahead, AstraZeneca is expanding its collaboration model:

• Big tech partners provide foundational capabilities.
• Startups offer agility, specialized tools, and emerging ideas.
• Academic institutions bring cutting-edge research and scientific rigor.
• Venture capital networks help the company anticipate where innovation is heading.

“We’re spending more time with startup organizations,” he explains. “Even having sessions with some of the venture capital groups that we have built connections with. It’s incredible what we can learn from each other.”

He adds that collaboration extends across the pharmaceutical sector itself, where companies often share learnings despite competing in the market: “We’re not against each other so much as we are against disease. We do find a lot more collaboration within our industry.”

Experimentation as a strategic muscle

Although AstraZeneca maintains a strong “buy before build” philosophy, Dummann says AI presents a unique opportunity to create custom solutions when needed.

“A lot of the things that you can do with AI are not that complicated,” he notes. “The model is already dealing with the complex.”

His team is increasingly comfortable experimenting, iterating, and building lightweight tools and agents — a mindset shift he views as essential.

“We don’t need to have the perfect answer and spend six months getting the perfect decision of where we should step first,” he explains. “Let’s just take the step and try and learn.”

He believes this experimentation culture will define which companies lead in the next era of AI-powered transformation.

Where AI is heading

Looking ahead, Dummann sees transformative potential far beyond AstraZeneca’s internal operations.

“Each of us needs to think about the industries we’re in,” he says. “Healthcare, in general, is the ripest opportunity for AI to transform from what today is probably more sick care.”

He envisions a future where patients, providers, systems, and AI agents interact seamlessly — improving screening, detection, and prevention.

“The better we can get cancer screening early, the better chance we have of mitigating the effects of it,” he explains. AI, he believes, can help unite clinical research, healthcare delivery, and patient engagement into a more sustainable, efficient system.

“It’s not just data,” he says. “It’s how AI and data and transformation can really bring this end-to-end industry together.”

The potential impact is both professional and deeply personal: “I like waking up every day thinking about patients and how we can help people. Or selfishly, how can I help prevent a problem that I may have by getting early screening?”

For Dummann, the next chapter of AI is already taking shape — and accelerating faster than most realize.

“We just haven’t put all the pieces together yet, but that’s happening, and it’s happening faster than we think.”

CDO Magazine appreciates Brian Dummann for sharing his insights with our global community.