Building Biotech's Future: The Strategic Imperative Of AI Integration

By Samina Bari

Small and mid-cap biotechs face a fundamental strategic choice that will determine their survival in this new world of business. How will they compete against well-capitalized incumbents while operating on a fraction of their resources?

The default response has been to replicate Big Pharma's organizational model at a smaller scale: Hire the same functional roles, follow the same workflows, and hope that leaner operations somehow translate into a competitive advantage. This approach is failing. Copying a model designed for billion-dollar budgets and thousand-person teams doesn't work when you're operating with $50 million in Series B funding and a team of 20.

Yet, despite existential pressures where companies measure runway in months, biotech leaders continue to organize themselves as miniature versions of legacy pharma. The industry talks endlessly about innovation in science while maintaining strict orthodoxy in operations.

The Missed Opportunity Lies In Strategic AI Integration

AI is already transforming highly regulated industries. In aerospace manufacturing, an industry with safety standards as rigorous as drug development, AI-driven systems have revolutionized production workflows, achieving dramatic reductions in manual labor while maintaining regulatory compliance. These aren't pilot programs. They're deployed at scale, delivering measurable productivity gains.

Recent studies demonstrate that purpose-built AI systems deliver transformative results that generic tools cannot match. In one rigorous analysis, specialized AI platforms enabled 84% of users to successfully complete complex technical documentation, compared to just 30% using generic AI tools. These systems reduced overall task completion time by more than half while simultaneously improving quality.

AI integration is not merely augmenting existing work processes but may have the potential to reshape the nature of collaboration and expertise in organizational settings.

Studies of AI adoption in highly regulated manufacturing environments show that purpose-built AI systems enable workers to breach traditional functional boundaries — with technical specialists producing more commercially viable solutions and commercial professionals generating more technically sound proposals when AI is integrated into their workflows.

This reveals a critical principle: AI's value multiplies when it's purpose-built for specific domains and integrated into actual workflows, rather than deployed as a stand-alone tool.

The biotech industry acknowledges AI's potential but still confines it to isolated experiments. These fragmented efforts miss the fundamental opportunity to deploy AI as a strategic operating system that transforms the entire development continuum.

The Advantage Of Building Vs. Retrofitting

Large pharmaceutical companies face a retrofitting problem. They must integrate AI into decades-old organizational structures, legacy IT systems, and entrenched processes. Even when leadership commits to transformation, execution stalls in endless pilots and experimentation cycles.

Small and mid-cap biotechs face a different situation entirely. They're not retrofitting, they're building. Every hiring decision, every workflow design, every capital allocation happens in real time. This is their strategic window.

When a CEO decides whether to hire three people for IND preparation or one senior expert supported by AI-driven documentation systems, that choice compounds. When leadership designs clinical development workflows from scratch, they can embed AI as foundational infrastructure rather than retrofit it later. 

Beyond Productivity: Competitive Velocity

Consider the standard IND preparation timeline. Traditionally, this requires multiple team members spending weeks aggregating data, drafting sections, and formatting submissions. AI-driven documentation systems collapse this timeline from weeks to hours for initial draft generation.

To be clear, this doesn't eliminate the need for regulatory expertise. Subject matter experts remain essential for accuracy validation and regulatory judgment. But AI eliminates the manual aggregation and initial drafting that consumes disproportionate time and capital.

The strategic impact isn't just efficiency, it's velocity. Submitting an IND three weeks earlier means entering clinical development sooner. Reaching key milestones faster often triggers financing tranches and partnership terms. In an environment where companies measure runway in months, weeks matter.

Research on product innovation demonstrates that innovation teams lose 33% of their time to documentation and searching for information instead of actual innovation work. When AI handles these routine cognitive tasks, experts can focus on strategic judgment and complex problem-solving.

The Holistic Integration Imperative

Current discussions about AI in biotech suffer from narrow framing. The focus remains on specific technical applications such as chemistry, medicinal biology, regulatory affairs. These applications deliver value, but thinking of AI as a tool for individual departments misses the transformative opportunity.

The strategic approach is holistic integration across the entire development continuum: from early discovery, preclinical research, IND preparation, clinical development, and regulatory submissions, to manufacturing scale-up, market access strategy, and pricing analysis. At each stage, AI can handle workflow acceleration, documentation, data synthesis, and process optimization.

This doesn't mean eliminating functional expertise. Regulatory experts, CMC specialists, and clinical development leaders remain essential. But when AI manages routine cognitive labor — including data aggregation, document formatting, and initial synthesis — these experts can focus on what AI cannot replicate: strategic thinking, nuanced judgment, and complex problem-solving.

The result is a fundamentally different operating model. Instead of building large teams of mixed seniority, biotechs can build smarter, more nimble teams of exceptional talent supported by AI-driven systems. Instead of accepting traditional timelines as inevitable, they can compete on velocity, getting much-needed medicines to patients faster while allowing them to increase time in market, resulting in higher revenue potential. 

Recent field experiments show that individuals working with AI can achieve performance levels comparable to traditional two-person teams, while AI-enabled teams demonstrate a higher likelihood of producing exceptional, top-tier solutions. Moreover, AI helps professionals breach functional silos, enabling technical specialists to produce commercially balanced solutions and commercial professionals to generate more technically sound proposals.

This is how small biotechs can actually compete against well-capitalized incumbents, not by doing the same things with fewer people, but by operating under an entirely different model.

The Leadership Challenge

This transformation requires courage from boards and executive teams. It means questioning assumptions about organizational design that the industry treats as immutable.

The geopolitical context adds urgency. China has aggressively embraced AI across biopharma operations while the U.S. industry waits for comprehensive guidelines or for large companies to establish standards. But emerging biotechs don't need permission to operate efficiently.

The companies that will lead the next decade won't just have better science; they'll have superior operating models. They'll move faster, manage capital more efficiently, and hit milestones sooner, all while maintaining full regulatory rigor.

The Path Forward

The future belongs to biotechs willing to build differently. Not incrementally different but fundamentally different.

For patients waiting for new therapies, this matters immensely: every month saved in development timelines, every dollar of capital preserved for additional programs, and every efficiency gain that allows companies to reach commercialization. These directly impact patient access to innovation.

As a venture and private investor and board member, I'm encouraging every company I work with to embrace this transformation, not because it's trending, but because it's the responsible path forward. The biotech industry talks constantly about its commitment to innovation. Now is the time to demonstrate that commitment beyond science to operations.

The question facing every emerging biotech is: Will you build for the future, or replicate the past?

About The Author:

Samina Bari is a human-centered corporate strategist, board member, investor, and best-selling author, known for her role in landmark biopharma acquisitions and advising CEOs and boards on governance, risk, and reputation. She champions women’s leadership and impact, and her portfolio spans strategic board roles, investment, speaking, published thought leadership, and start-up AI technology.