US Pharma Marketing
Why healthcare marketing will be built by people and powered by AI
For the past few years, the conversation in biopharma organizations has centered around the promise of AI efficiency. This promise generated a groundswell of AI pilots that started to tackle a long list of activities which the Big Consulting giants had deemed worthy of trying. In recent months the conversation has started to shift meaningfully for at least two reasons that we see.
First, there is “pilot fatigue.” As pilot tools have mushroomed, our clients (commercial, digital, and AI leaders) have been bombarded with tens—if not hundreds—of AI tools that all promise to nail one hyper-specific use case. The poster child, of course, being the ability to “streamline” medical, legal, and regulatory processes. Business and technology leaders are overwhelmed.
At the same time there is starting to be a reckoning around the real costs of AI solutions. A year ago, a cornucopia of bespoke AI software that was relatively cheap—not unlike a deeply discounted Cheesecake Factory menu—drove a seemingly endless pipeline of projects and trials. Recent changes to pricing of AI software, for example Microsoft’s announced changes to a usage-based pricing model for Cowork, are triggering a reckoning around the costs of AI. There is also a growing realization that the bill for the hundreds of billions of CapEx being sunk into AI hardware and software by the frontier model companies and the hyperscalers will come due in the not-so-distant future.
What’s becoming clear is that these two factors—pilot fatigue and cost concerns—are driving a conversation around mindful prioritization of areas of focus that will deliver measurable impact and a quest for fewer strategic partners that can support organizations end-to-end. Organizations are realizing that unlocking the full potential of AI means going beyond a tool-based approach and rethinking how AI changes how the work gets done altogether.
This belief shaped our development of Real Chemistry ANATOMI, a human-led, AI ecosystem purpose- built for the full healthcare commercialization lifecycle, designed around a simple idea: technology should amplify human expertise, not replace it. The goal isn’t automating people out of the process. It’s helping people contribute where they create the most value.
The organizations that succeed in this next phase of the AI journey will take a similar approach, making the most of their people, AI, and the systems that bring them together.
The AI-Human Continuum
One of the biggest myths organizations still grapple with is AI as an either-or proposition. Either AI replaces people or people remain in control and AI becomes another productivity tool.
Reality, as it often does, sits somewhere in the middle. I think about the future of work as a continuum, with intelligence on one side and judgement on the other. At one end are tasks that are almost entirely intelligence driven, which increasingly belong on autopilot.
In the middle is co-pilot mode, which I believe will become the dominant model across healthcare marketing and communications. AI helps gather and process intelligence, speeds up synthesis, and accelerates execution of first drafts. Humans contribute judgment, creativity, and strategic direction that turn the first drafts into quality, compliant final deliverables. At the other end are areas where human expertise remains essential. Strategic counseling. Reputation management. Brand building. Crisis communications. The moments where context, judgment, and relationships matter more than raw intelligence.
What’s most interesting about this AIhuman continuum is where most of the work lives across the spectrum.
Our own analysis of the healthcare commercialization landscape showed that most of the work (60%) takes place in the middle co-pilot zone, 20% remains fully human, and less than 20% will be in autopilot mode. This breakdown is fitting given the highly regulated nature of healthcare and the huge premium placed on information accuracy and regulatory compliance. Organizations that get that balance right will create more value—for their customers and their people—than those focused solely on automation.
Context Is Becoming the Competitive Advantage
As AI integration becomes more prevalent, another trend appears. One that I believe will separate tier-one healthcare partners from the rest of the pack: access to AI tools and solutions is no longer a differentiator; context is. With commercial AI solutions being available widely, context becomes the moat.
By context, I mean the proprietary data drawn from decades of deliverables, and human experience that wraps around AI at any given organization. The same model can deliver very different outcomes depending on the information, expertise, and assumptions surrounding it.
Healthcare is a perfect example. In our industry, successful commercialization depends at a foundational level on several factors: clinical benefit, scientific differentiation, patient journeys, healthcare professional attitudes and behavior, regulatory requirements and constraints, market access dynamics, and competitive landscape. At a higher level, there is company-specific context—history in the chosen therapeutic category, conservative or aggressive, digital leader or fast follower, science-driven or commerciallydriven, and of course company culture.
At the highest level is the context around individual company leaders—whether commercial or medical their desires, hopes, and dreams. AI can process information at an extraordinary scale, but it is some years away from being able to fully understand the numerous decisions and contradictions that inherently arise from the complex interplay of market, company, or leader contexts. This is the contextual judgment that healthcare professionals and marketers develop through years of lived experience.
“One of the biggest myths organizations still grapple with is AI as an eitheror proposition. Either AI replaces people or people remain in control and AI becomes another productivity tool. Reality, as it often does, sits somewhere in the middle.”
That’s why I believe the future belongs to organizations that possess the right combination of contextual factors that will make AI work harder and smarter to deliver better results for clients and, ultimately, for patients.
The Real Opportunity Still Lies Ahead
AI will continue to transform healthcare marketing, and I believe the best performers will be the ones who most effectively move from AI adoption to integration.
But in the end we must always keep people, real people, at the center. Technology can create intelligence at scale, but it’s people who create meaning from it.
That’s why I remain optimistic about the future. Healthcare has an opportunity to become the proving ground for this next phase of AI, showing how trusted systems, healthcare-specific context, and human judgment can work together to create better decisions and better outcomes. The organizations that become tomorrow’s market leaders won’t be the ones that replace people with AI. They’ll be the ones that use AI to elevate what people do best.