AI as the Input, Not the Answer: When Human Strategy Still Leads

Previously, we explored why AI alone isn’t enough to drive strategic decision-making in pharmaceutical commercialization. In this follow-up, we examine how human insight becomes essential when facing challenges with no clear precedent or with high competitive intensity, where strategy must go beyond the data.

Why Human Strategy Still Matters in Pharma’s AI Era

AI is playing an increasingly important role across pharmaceutical commercialization, helping teams accelerate insight generation, optimize operations, and synthesize complex data. With the right inputs, AI can enhance how decisions are made. However, when it comes to solving problems that don’t have a clear precedent, it quickly becomes clear where AI limits lie.

At Putnam, we believe AI is a valuable enabler, but not a substitute for strategic thinking. When the stakes are high and the answers aren’t obvious, strategy must be fundamentally human-driven. That difference often defines whether a plan is just efficient, or truly innovative.

Analog Research and AI: Two Tools Built on Precedent

For decades, Putnam has helped clients understand and apply lessons from analog research. It is a foundational tool helpful for identifying what has worked before and where pitfalls may lie. But over time, we have consistently found that, while analog research is often essential, it is rarely enough.

At its core, analog research looks to the past. It draws on historical examples and comparable situations to help inform strategy. In that way, it shares a key characteristic with AI. Both depend on precedent. Both rely on available data. And both are ultimately limited by what has already happened.

This means they are powerful for framing hypotheses, but less helpful for identifying ideas that break new ground. Whether launching a therapy with no commercial reference point, or navigating a new pricing model, success depends on more than pattern recognition. It requires strategic creativity.

One-Two Punch: Pairing Analog and AI for Strategic Insight

We see analog research and AI not as competing tools, but as complementary ones, each powerful in its own right, but even more effective when used together. Together, they provide a foundation of evidence and structure that helps Putnam and client teams start from a smarter place.

For example, AssetNav, a tool part of our proprietary InizioNavgator suite brings together structured data on assets in development. When integrated with message / positioning analysis and financial reports, we can begin to understand how companies are positioning their assets in real time and implications on share and revenue. This pairing helps us surface early patterns in market behavior and help inform go-forward strategies for both existing competitors and new market entrants.

But just as importantly, this analysis often sparks new lines of inquiry into questions that data alone cannot answer – for example, questions about what hasn’t been said, what may resonate differently with emerging decision-makers, or what strategic moves haven’t yet been tested. That’s where our teams dig deeper, applying judgment, pressure-testing ideas, and engaging directly with external stakeholders to shape strategic recommendations that are not just well-informed, but also truly differentiated.

In this way, analog research and AI provide the foundational inspiration, but human insight provides the strategy.

Strategy Without Precedent Demands Human Judgment

Our work supporting the early commercialization of cell and gene and radioligand therapies highlights this need clearly. These were challenges where analogs offered limited guidance, and success depended on strategic creativity grounded in rigorous thinking and stakeholder insight.

Specifically, we helped clients navigate several such precedent-limited situations by developing innovative commercial strategies, including:

• Launching the first CAR-T therapies, where we worked with manufacturers to define entirely new delivery models, including strategies to establish effective referral networks, design site certification frameworks, and prepare institutions to manage complex care coordination and reimbursement.
• Pricing the first gene therapies in the U.S., where we supported manufacturers in creating novel pricing and value frameworks that reflected durability of effect, uncertainty in long-term outcomes, and the disruptive nature of one-time treatments.
• Commercializing radioligand therapies (RLTs), where we helped companies address market education, site readiness, and delivery model design for a modality that crossed traditional specialty boundaries.

In each of these cases, the right path wasn’t something that could be pulled from an analog database or modeled from precedent, it had to be created. Our role was to help our clients build those new paths with confidence and clarity.

Standing Out in Competitive Pharma Markets By Going Beyond The Precedent

Even in areas where precedent exists, relying too heavily on it can be risky. In crowded categories, any obvious strategic move based on historical insight is likely already on competitors’ radars. Success in those situations requires ideas that go beyond what the data would naturally suggest.

That is why our approach combines precedent-based tools like analogs, AssetNav and AI with structured internal debate, deep discussion with client teams, facilitation of cross-functional collaboration, and targeted primary research with a wide variety of relevant external stakeholders. We push our teams and our clients to explore new angles, challenge assumptions, and think creatively, because that is what it takes to find differentiated solutions. In a world where there is ever-increasing pushes to leverage AI, ensuring inclusion of the human element can serve as a meaningful competitive differentiator.

A Human-Driven Model, Informed by AI

AI is a valuable part of our toolkit. It allows us to move faster, see patterns more clearly, and build a stronger foundation for strategic thinking. But it has limits, especially in cases where the answer does not yet exist.

We view AI, like analog research, as an input, not a driver. For breakthrough strategies, we rely on people who can frame the right questions, consider multiple perspectives, and apply judgment to nuance that data cannot capture.

If your team is facing a challenge that requires new thinking, Putnam is ready to help. We combine decades of experience with a forward-looking mindset to help our clients lead in complex, competitive markets. Contact us.