The Real Value Equation: How Humans and AI Create and Destroy Value in Pharma

Over the past two years, generative AI has moved far beyond pilots and innovation labs. It is now embedded in the operational core of pharmaceutical companies, influencing how targets are identified, how trials are designed, how regulatory documents are authored, how manufacturing deviations are diagnosed, and how commercial strategies are built.

Yet in boardrooms and leadership offsites across the industry, the dominant questions remain curiously shallow: How many hours will AI save? How many functions can we automate? How fast can we scale it across the enterprise?

The far more strategic question is one most company are still avoiding: How exactly does value get created and destroyed inside our organization, and how will AI fundamentally shift that equation?

If this question is not answered, AI risks becoming a high-speed accelerator of the wrong behaviors. It may improve surface efficiency while quietly eroding the deeper human capabilities that underpin regulatory success, scientific credibility, and durable trust with physicians, patients, and payers.

To understand this balance, leaders must look through the lens of the Human–AI Value Matrix (Figure)—a framework mapping where AI genuinely enhances enterprise value and where it threatens to erode irreplaceable human contributions.

The Human Value Engine Inside Every Pharmaceutical Company

Despite its technological sophistication, the pharmaceutical enterprise is fundamentally human.

Humans create value through scientific insight, the ability to detect weak signals, challenge prevailing assumptions, and mentally integrate biological, clinical, and commercial complexity into coherent decisions. The most impactful breakthroughs rarely emerge from computation alone.

They arise when scientists connect anomalies, take intellectual risks, and interpret messy data with intuition and experience. Humans also create value through judgment under uncertainty.

Drug development decisions are rarely made with perfect information. Choices about trial design, dose selection, patient populations, endpoints, or risk-benefit framing depend on experience, contextual reasoning, and an understanding of how data will be interpreted in the real medical and regulatory world.

Beyond science, humans create value through what might be pharma’s most underestimated asset: relationship capital. Medical affairs professionals build trust with key opinion leaders over years.

Market access teams navigate payer priorities shaped by economics and policy. Regulatory professionals build credibility with agencies whose expectations are evolving constantly. These are not transactional relationships; they are ecosystems of trust.

Humans also create value through ethical restraint, the ability to recognize when not to cut corners, when to delay, and when to prioritize patient safety or scientific rigor over speed. That human instinct protects reputations, prevents crises, and strengthens long-term license to operate.

Finally, humans create value through strategic and narrative creativity. Commercial leaders, lifecycle strategists, and corporate development teams do not simply analyze markets, they frame them, constructing meaning around science, value, and unmet need.

How Humans Also Destroy Value

But value creation is only half the story. Human systems also destroy value, often invisibly.

• Scientific bias leads teams to over-invest in weak hypotheses.
• Poor coordination between clinical, regulatory, and CMC groups leads to inconsistent assumptions and costly rework.
• Sloppy documentation triggers regulatory delays.
• Poorly handled payer negotiations damage long-term access.
• Internal politics distort portfolio decisions.
• Siloed thinking multiplies errors.

What makes this dangerous is not that these errors occur, but that they often happen quietly, unmeasured, and over time. AI enters into this fragile system as a force amplifier.

Done right, it can reduce some human-driven value destruction. Done poorly, it can accelerate it.

The Human–AI Value Matrix as a Strategic Lens

The Human–AI Value Matrix provides a way to understand these dynamics. One axis reflects value created by AI: speed, automation, pattern recognition, scale, and analytical power.

The other reflects value potentially destroyed by AI: loss of judgment, erosion of trust, weakening of expertise, and degradation of institutional memory.

This creates four strategic zones:

1. Augmentation Zone: High AI value with minimal erosion of human capability.
2. Automation Zone: AI replaces low-differentiation tasks with limited risk.
3. Risk Zone: AI threatens high-value human functions like judgment, trust, or creativity.
4. Low-Impact Zone: Minimal strategic impact either way.

The leadership challenge is not aggressive AI deployment everywhere, but intelligent placement within this matrix.

Where AI Genuinely Enhances Pharmaceutical Value

AI’s most powerful role is not replacement, it is expansion. In drug discovery, AI enables exploration of biological space at a scale that human cognition cannot reach.

It allows teams to generate, test, and refine hypotheses faster and more comprehensively. In clinical development, machine learning improves trial feasibility modeling, enrollment forecasting, and dropout predictions, enabling smarter protocol design and risk mitigation upstream.

In regulatory affairs, AI improves the speed and consistency of drafting and cross-checking massive documentation, freeing experienced professionals to focus on strategy, positioning, and agency interaction. In manufacturing and CMC, predictive analytics identify deviations, process drift, and root causes more efficiently than traditional statistical approaches.

In commercial and market access functions, AI improves forecasting precision, competitive scenario modeling, and demand planning, supporting better strategic decisions.

In these cases, AI strengthens human decision-making rather than displacing it. This is the Augmentation Zone of the matrix, where sustainable value is created.

Where AI Should Replace Tasks, But Not Capabilities

Some functions are highly repetitive, low in strategic differentiation, and ideal for AI automation. These include literature screening, data cleaning, pharmacovigilance triage, CRM documentation, protocol boilerplate preparation, and standardized reporting.

Replacing these tasks with AI does not erode critical human value, instead, it frees specialized professionals to focus on judgment-heavy, high-impact work. This corresponds to the Automation Zone of the Human–AI Value Matrix.

Where AI Risks Destroying Value

The most dangerous errors occur when organizations begin automating functions rooted in judgment, trust, and tacit expertise. Regulatory strategy requires contextual interpretation of nuanced agency expectations.

Scientific exchange with physicians relies on credibility and authentic human engagement. Manufacturing quality decisions often depend on experiential intuition from seasoned operators.

Market access negotiations involve psychological, institutional, and political dynamics that no algorithm fully captures. When AI displaces rather than supports these functions, companies experience capability dilution.

Their systems become faster, but their minds become shallower. Their outputs increase, but their judgment weakens.

This is the Risk Zone of the matrix, where long-term value destruction outweighs short-term productivity gains.

CNPV as a Case Study in Why Human–AI Balance Matters

The emerging FDA Commissioner’s National Priority Voucher (CNPV) is a useful example of why this balance matters. Unlike traditional priority review incentives, the CNPV concept is tied to drugs that serve national interests, such as supply chain resilience, biodefense, pandemic preparedness, or critical health priorities.

These assets will operate under intense regulatory, political, and societal scrutiny. For such programs, over-automating judgment-heavy functions is not just a business risk, it becomes a reputational and public trust risk.

Under this scenario, AI must operate firmly in the Augmentation Zone of the matrix, strengthening scenario modeling, risk simulation, supply chain visibility, and regulatory preparedness, while human accountability, oversight, and judgment remain non-negotiable.

The CNPV simply illustrates what will likely become true across pharma more broadly: As societal stakes increase, the value of human judgment increases, not decreases. AI cannot replace that; it can only support it.

Invisible Risk: Capability Atrophy

One of the greatest long-term dangers of AI is not job loss, but capability erosion.

If junior regulatory professionals rely entirely on AI to draft narratives, they never learn how to construct them. If analysts always accept algorithmic outputs, they stop questioning assumptions.

If manufacturing teams defer to dashboards rather than their senses, they lose tacit process knowledge. Over time, an organization may appear more productive while becoming strategically weaker.

And when a true crisis arises, a major safety signal, a regulatory standoff, a quality failure, or a national priority program under pressure, the human capability to respond may no longer exist.

Ten Strategic Questions for Pharma Executives

Every AI initiative should begin not with a technical plan, but with strategic reflection:

1. What unique human value does this process create today?
2. What human capability could erode if AI replaces this workflow?
3. Does AI enhance judgment or merely accelerate output?
4. How does this affect our trust with regulators, payers, physicians, or patients?
5. Which functions must remain deeply human regardless of automation?
6. Are we redesigning processes or simply digitizing inefficiencies?
7. What long-term capabilities might be weakened by this change?
8. How do we maintain institutional knowledge alongside AI adoption?
9. Does this strengthen or weaken cross-functional coherence?
10. Are we building human–AI complementarity or just cost efficiency?

These questions transform AI from a technology deployment into a corporate architecture decision.

Conclusion: AI Is the Amplifier, Not the Strategy

AI will change the speed of pharmaceutical development. It will transform how knowledge flows through organizations. It will elevate efficiency across functions.

But it will not replace judgment. It will not generate trust. It will not create ethical restraint and it will not substitute for scientific intuition.

Those remain deeply, irreducibly human. The future of pharma belongs to leaders who recognize one truth clearly:

Humans are the source of value. AI is the amplifier. Lose the human, and you lose the value no matter how advanced the technology.

About the Author

Thani Jambulingam Ph.D. is a professor in food, pharma and healthcare at Erivan K. Haub School of Business, Saint Joseph’s University, Philadelphia. He is a pharma and healthcare strategist and his work focuses on AI-enabled decision frameworks, emerging technologies, and commercial strategy.

Pavitra Velan is a healthcare consultant, specializing in Global Patient Analytics & AI Solutions at IQVIA Inc. Her works focuses on using machine learning to identify patterns in real world patient data enabling a deeper understanding of patient diagnosis and treatment journeys. She supports data-driven decision-making across the healthcare ecosystem by translating complex analytics into actionable insights for life sciences and healthcare stakeholders.