Pharma Commercialization in the Age of AI and Active Patients

We’ve entered a new era of customer engagement in healthcare. A recent Bain survey reveals that globally, about half of patients advocate for a specific treatment, regardless of therapeutic area. And around a quarter of healthcare professionals (HCPs) globally say that patient requests inform their treatment decisions. When it comes to using AI-based tools for information about treatment, more than half of patients say it’s valuable, and nearly one-third of HCPs say they do so frequently.

Pharma companies have already reshaped their commercial models to address post-pandemic shifts—namely, the tightening HCP access as well as an overload of evidence and information. But just as they are finding their stride—moving toward more personalized omnichannel HCP engagement with more mature tech stacks and marketing engines—the landscape is shifting again, right under their feet.

This time, change is coming from both sides of the prescription pad. Patients’ and HCPs’ expectations are evolving, requiring pharma companies to rethink their commercial models once again. In particular, they will need to respond to three pivotal shifts: the rise of patient-led medicine, the next evolution of customer-friendly HCP support, and the role of AI as the new gatekeeper of information.

Shift No. 1: The rise of patient-led medicine

Patients are no longer passive recipients of care.

Among younger patients, the shift is even more pronounced.

Along with patients taking an active role in their care, we are also seeing a shift to more explicit consumer behaviors, although those behaviors differ by region. For example, in Europe, local pharmacists are the No. 1 most frequently used and valuable source of treatment information. In Asia-Pacific, patients most frequently use search engines, social media, and ChatGPT.

In the US, direct-to-patient platforms such as LillyDirect and NovoCare are gaining traction. While these platforms are still nascent, early adoption is strong, with 25% of US patients trying them and liking the convenience.

To be clear, a doctor’s recommendation is still the most crucial factor in treatment selection. However, across geographies and therapeutic areas, HCPs recognize that patients are advocating for specific treatments more often—and they are more open to it. In fact, 21% of HCPs say that patient preference is extremely important in treatment decisions, up from 16% in 2022.

In the US, we also see this openness in a heightened sensitivity to patient-centric factors, especially when it comes to a patient’s ability to afford medication.

Shift No. 2: The next evolution of customer-friendly HCP support

HCPs still want pharma to make it easy for them. But what that means is evolving and depends heavily on geography.

US providers also see offering materials on drugs’ cost benefits or economic merits to HCPs or patients as one of the most important roles a pharma rep can play.

Shift No. 3: The role of AI as the new gatekeeper

Patients and HCPs alike are turning to AI for information—sometimes intentionally through tools such as ChatGPT, and sometimes unintentionally through AI-generated search results.

AI-powered features in clinical decision support tools (e.g., UpToDate) are increasingly influencing HCP decisions by providing robust diagnosis and treatment recommendations. 

Even so, the breathtaking speed of adoption points toward a future in which AI plays a more prominent role.

Patients see several benefits: AI tools provide fast, clear, judgment-free answers that pull from multiple sources and compare options. While there are still concerns about reliability, accuracy, and specificity of answers, usage is climbing fast.

At the same time, patients and HCPs still rely heavily on search engines. HCPs cite search engines as their second-most frequently used source, slightly behind journals but ahead of peers. They say search engines are as influential as sales reps in prescription decisions. For patients, search engines are the most used source of information outside of their doctor.

However, search engines increasingly surface AI summaries that reduce clicks to actual pharma-owned content. A recent Bain survey of more than 1,100 US consumers found that 80% rely on these zero-click results for at least 40% of their searches. And biopharma-related search terms’ click-through rates have declined from 32% to 27% over the past year since AI summaries started appearing.

This has massive implications for pharma companies. Search engine optimization (SEO) isn’t enough. Future leaders will invest in AI optimization, understanding that the question is not whether AI will shape perception but rather whose data and narratives the models will surface first.

What this means for pharma’s commercial model

Responding to these trends will take more than layering onto existing sales and marketing models. It will require a full transformation of the commercial model, one that rethinks how companies engage with and meet the needs of both HCPs and patients. Winners will focus on a few key capabilities.

• Differentiate on patient experience. Leaders will design an elevated, end-to-end experience that includes (not sidesteps) the patient to build lasting loyalty. This requires more consumer-centric, data-based capabilities. It’s not just about understanding patients at an ethnographic and psychographic level but also as consumers who expect ease, transparency, and relevance in every aspect of their lives.
• Redefine HCP value. It’s time to go beyond customized messaging to deliver value through more tailored, locally relevant clinical practice engagement and support. This means shifting from a focus on empowered field sales reps to a focus on empowered multidisciplinary teams across sales, medical, access, and patient services. Field sales reps will still play a vital role, not only conversant in on-label claims but also in access and patient support. But the true differentiator will be multidisciplinary teams that come together regularly to anticipate and address HCP needs in a coordinated, personalized way.
• Evolve your digital strategy, marketing capabilities, and tech stack. As AI reshapes content consumption and click-driven search declines, pharma companies can prioritize earned engagement and AI-first SEO strategies. Digital leaders will also develop a specific plan for AI-based clinical decision support tools, including monitoring how emerging tools are drawing from clinical data and ensuring that scientific evidence is primed for discoverability.

Scaling this model requires new enterprise-wide discipline and ways of working, especially as needs evolve differently across portfolios and geographies. For instance, traditional annual budgeting won’t cut it: Agile funding approaches are necessary to deploy resources distinctively and dynamically. Similarly, pharma companies can redesign their sourcing and vendor ecosystem with a bias toward speed and flexibility.

The pace of HCP and patient behavior change is faster than ever. The winning model of the future will turn today’s disruptions into durable advantage.