Why Pharma’s AI Strategy Must Evolve
AI is everywhere in pharma. Companies are running pilots, testing AI in sales, marketing, and market access. Some are seeing results; many are not. The industry is at a breaking point.
Over the last year or so, AI has been treated as an experiment—promising but not critical. That mindset is shifting as AI is now creating genuine business outcomes not only in drug discovery but also in commercialization. Companies that move beyond pilots and fully integrate AI are changing how drugs reach the market and those that do not now run the risk of falling behind.
Why AI Is Not Moving Fast Enough
The issue is not that AI is not funded or popular—it’s focus. Companies are treating AI as a collection of one-off projects rather than a strategic business initiative.
Departments run initiatives in isolation, marketing, sales, or market access, without integrating efforts. Data remains locked in silos, limiting AI’s ability to deliver insights across the organization.
Meanwhile, leadership continues to ask: Where is the value?
The solution is simple—AI will not be able to fulfill its potential as a series of fragmented pilot projects. Those companies that have incorporated it into their commercial functions are seeing real improvements in efficiency, engagement, and market outcomes.
AI Is No Longer Just Theory
This shift is already happening, with the fastest-moving companies embedding AI into three critical areas:
- Sales & Marketing Execution
AI is helping sales teams identify the right healthcare providers, personalize marketing messages, and optimize engagement in real time. Broad, onesize-fits-all campaigns are losing relevance. - Market Access & Adaptive Pricing
AI is analyzing real-world data to refine pricing strategies, predict reimbursement hurdles, and adjust market access approaches in real time. - Intelligent Compliance Automation
AI is reducing the burden of regulatory reporting, compliance monitoring, and administrative tasks, allowing teams to focus on high-value work.
Companies that connect these efforts, rather than running AI in silos, are gaining a competitive advantage.
Scaling AI: What Needs to Change?
For AI to become a true business driver, pharma companies need to take these critical steps:
- Stop Treating AI as a Side Project
AI works best when integrated across commercial teams, not as isolated experiments. - Tie AI to Business Outcomes
If AI is not increasing revenue, reducing costs, or improving efficiency, it is just another digital initiative without direction. - Fix the Data Problem
AI is only as good as the data it learns from. Many companies still struggle with fragmented systems that prevent AI from scaling.
The AI Breaking Point Is Here
AI is no longer a future concept—it’s already shaping the present. Companies integrating AI into their commercial strategies are transforming the industry, while those who delay are falling behind.
The real question isn’t whether AI will redefine the industry, but who will lead the change and who will be left playing catch-up.
