The biopharma industry stands at a crossroads where artificial intelligence promises to revolutionize everything from drug discovery to patient care. But technology alone won’t deliver that transformation. Nishtha Jain, an award-winning executive with over 15 years leading digital transformations in AI, biopharma, and digital health, has built her career around a simple question that cuts through the hype: “Does this help people?”
Start With Purpose, Not Technology
Here’s where most companies go wrong. They fall in love with the technology before they figure out what problem needs solving. Jain flips that around completely. “AI should always begin with a human problem—a scientist trying to shorten a discovery cycle, a clinician trying to improve clinical trial design, or a patient seeking faster diagnosis,” she explains. Sounds obvious, right? But walk into most biopharma companies and you’ll find AI projects that started because someone thought the technology was cutting-edge.
That single question drives everything she does: “Does this help people?” It’s not about whether AI can do something. It’s about whether it should, and whether anyone will actually benefit from it. Across research, clinical development, medical affairs, and patient care, she’s seen AI become what she calls “a trusted partner in discovery.” But only when teams know exactly what they’re trying to accomplish.
Break Problems Into Smaller Testable Parts
Large-scale AI projects tend to die slow, expensive deaths. Jain’s answer? Don’t start big. “We must break problems into smaller testable parts. AI thrives on iteration. Pilot fast, learn fast,” she says. Instead of launching a massive transformation that takes two years to show results, test something small next week. The learning matters more than the outcome. “Every model you train, every experiment you run should teach you something—not just about the data, but about decision making as well,” she points out. That’s the shift most organizations miss. They treat AI as a calculator that spits out answers. But it’s really teaching teams to think differently about their work.
Create An AI-Ready Culture
You can have the best AI tools money can buy. Doesn’t matter if your team won’t touch them. Jain has watched this play out enough times to know where the real work happens. “Create an AI-ready culture. That means encouraging curiosity, celebrating experiments that don’t work the first time, and providing a safe space for teams to learn together,” she explains. Most executives nod along to this advice, then turn around and punish the first team whose pilot fails. Forcing people to use AI through company mandates? That’s the fastest way to waste money. “Adoption doesn’t happen through mandates. It happens through mindset,” Jain says. When teams feel safe to experiment, they start finding uses for AI that nobody planned for. That’s when real transformation happens.
All the conference talks focus on AI’s capabilities. What it can do, how fast it works, how much money it saves. But she cuts straight to what actually matters. “AI adoption is indeed the biggest challenge.” Not the technology. Not the data. Getting people to change how they work. That challenge shapes her vision for where biopharma needs to go. “Imagine a biopharma world where AI accelerates innovation. That’s the future I believe in—one where AI helps us amplify human intelligence rather than replace it,” she says. The difference between amplifying and replacing isn’t just semantic. It determines whether your team sees AI as a threat or a tool.
Jain has a theory about how innovation actually happens. It’s not about pushing harder or spending more. “If we can align people, process, and purpose, innovation will follow naturally,” she explains. Get those three things pointing in the same direction, and the breakthroughs start coming on their own. Her work shows what that looks like in practice. Scientists shortening discovery cycles. Clinicians designing better trials. Patients getting faster diagnoses. The technology enables all of it, but it only works because someone started by asking what people actually needed. That’s the lesson most companies are still learning the hard way.
Follow Nishtha Jain on LinkedIn for insights on human-centered AI and digital transformation in biopharma.
