KEY TAKEAWAYS
• AI adoption is now exponential, creating a narrow window for pharma leaders to reposition with intent
• AI medical reasoning now exceeds human baseline standards, reshaping how knowledge and decisions are accessed
• AI is projected to free up 20–40% of capacity, forcing a strategic choice: efficiency alone or innovation acceleration
• Customer behavior has already shifted, with patients and HCPs operating in an AI-enabled reality
• Early results show real impact, with Pfizer reporting 40% reductions in drafting of content timelines
The pharmaceutical industry is facing what Alex Condoleon characterizes as a defining moment of strategic tension — one shaped not by resistance to change, but by a growing awareness that the pace of opportunity has accelerated. “There is a restlessness around us,” Condoleon explained. “Restlessness—I think it’s such an interesting word. It’s this energy because disruption is around us, but it’s also a tension and it’s a question about how are we meant to act right now.” That restlessness reflects a sector that recognizes both the scale of possibility created by artificial intelligence and the responsibility to deploy it thoughtfully within an industry built on evidence, trust, and patient impact.
As Chief Medical Affairs Officer of Medical Engagement & Impact at Pfizer, Condoleon framed the moment not as a critique of healthcare’s deliberate nature, but as a recognition that the environment has shifted. “To not move right now is to run the risk of being left behind. And we sort of get it, right? We get it. There is a velocity of change going on which is something we have not seen before.” This velocity is what distinguishes the current wave of technology from prior innovation cycles. “In five days, 1 million users. In two months, 100 million users” he noted, referencing ChatGPT’s adoption trajectory. “Fast forward to today, and OpenAI is now disclosing that they have 800 million people a week on their platform.” Comparisons such as Instagram, Netflix, and Facebook took years to reach that scale. The difference is not simply speed, but the way exponential adoption has become the new baseline for transformative technology.
This acceleration creates a new leadership challenge, not because healthcare has moved incorrectly, but because the context around it has changed.
“We know that in healthcare we often move at the pace of bradycardia,” Condoleon observed. “Now we’re going to have to measure up the speed of technology with the speed that we think of moving.”
The opportunity lies in aligning healthcare’s rigor with digital velocity — not abandoning caution, but learning how to operate with momentum and responsibility at the same time. Medical affairs teams accustomed to multi-year planning cycles now see technology evolve in months. Commercial engagement models refined over decades are being complemented by the rapid emergence of tools that change how information is accessed, interpreted, and acted upon.
The acceleration is not only about adoption, but also sophistication. Condoleon shared how rapidly large language models have advanced against medical knowledge benchmarks. GPT-3.5 scored just above the sixty-percent pass threshold on the US Medical Licensing Examination less than three and a half years ago. GPT-4.0 consistently scored around ninety percent. Early reports suggest GPT-5 may exceed that. “For the first time in human history we have a technology, not specifically trained on medical content and knowledge and information, that is consistently scoring above the human standard theoretically to become a physician in the US,” he emphasized. This progression fundamentally expands what is possible in information access, decision support, and clinical reasoning — not as a replacement for clinicians, but as a powerful augmentation of human expertise.
Crucially, this is not a future-state discussion. Patients and healthcare professionals have already integrated AI into their daily behaviors. Condoleon cited recent IQVIA HCP data showing “46% who are using ChatGPT for medical or scientific information, 23% on Gemini, 21% on Copilot”. Another Bain reports shows “60% of HCPs are regularly using large language models of some sort to seek information at times of their need, and 70% of patients are using LLMs at diagnosis.” This adoption occurred in just a few years, signaling a mainstream shift rather than isolated experimentation. Patients now arrive with better-formed questions. Clinicians have access to synthesized information in real time. The opportunity for pharma is to evolve engagement models to maintain relevance in this new phase of Gen-AI adoption for medical and scientific information.
Condoleon provoked that this environment demands a strategic reframe. “Maybe we’re in a period where rather than ‘business as usual’, our challenge is to work out how to lead through ‘business unusual’ … a period where momentum matters more than mastery,”. The implication is not to abandon rigor, but to recognize that learning now happens through action. The organizations that thrive will be those willing to experiment responsibly, build capability while deploying it, and treating curiosity as a competitive advantage rather than a risk.
Approached the right way, AI’s exponential advancement represents a significant opportunity for productivity and reinvestment. Condoleon referenced recent McKinsey research projecting that “in the life science sector, between 75 and 95% of roles will have AI agents next to them, and that that will free up 20 to 40% of capacity in the organization.” How that capacity is used will shape the next decade. “If we view these latest technology approaches as just being a way to outsource cognition, we’re going to deploy these technologies, we’re going to downsize workforces, and in doing that we’re not going to have discovered any new drugs,” he cautioned. Efficiency alone is not the prize. The real opportunity lies in augmenting human potential and redeploying time and talent toward higher-impact work.
Condoleon described an alternative path centered on value creation.
“I think the opportunity to think about [is] how we augment human potential with technology—flip that script—it’s a question of can we drive productivity in order to redeploy human effort in ways that have bigger impact?”
That redeployment could mean tackling harder discovery challenges, advancing personalized medicine, deepening scientific dialogue, or elevating standards of care. Pfizer’s early deployment results suggest the value creation path is achievable with concrete evidence reported in their 2024 Annual Report. “With content we were seeing a 40% reduction in timelines for first draft, a 15% overall timeline reduction to manuscript development,” Condoleon reported. “That means information is getting to the medical community sooner, and that means that information provides better clinical practice.”
In another example, Condoleon noted an AI collaboration that was initiated with Veeva over a coffee conversation. It led to a draft proposal within two weeks, and AI summarization features introduced industry-wide just a few months later. As a result, field medical teams now spend less time preparing for engagements and more time deepening scientific conversation.
Underlying this shift is what Condoleon described as co-intelligence — a concept articulated by Wharton professor Ethan Mollick — where human and AI capabilities are woven seamlessly into daily workflows. “Are you embedding AI in absolutely everything you do?” Condoleon challenged. The advantage does not come from access alone, but from fluency. Teams that worked with AI tools daily achieved dramatically better outcomes than those using them occasionally. Organizations must move beyond viewing AI as an occasional productivity boost toward treating it as a fundamental capability that requires cultivation.
That capability scales most powerfully when innovation is democratized. “When you give these tools to the front line where the friction is higher, where the urgency is greatest, they’re going to come up with ideas more brilliant than what anyone in the organization can think,” Condoleon emphasized. Frontline teams understand pain points leadership never encounters. Empowering them to experiment enables hundreds of parallel improvements to emerge simultaneously. Competitive advantage shifts from centralized planning to connected learning.
In that context, leadership is less about having the answers and more about creating the conditions for learning at speed. “I think today is not about worrying about being a leader. I think today it’s about worrying about learning fast,” Condoleon said. The opportunity window is open. Customer behavior has already changed. Technology continues to accelerate. The organizations that capture this moment will be those that translate restlessness into readiness.
Condoleon returned to where he began — with restlessness — not as a flaw, but as a signal.
“Boldness is our response to restlessness. It’s going to take courage. It’s going to be a very painful period of transformation”
he acknowledged. Yet the alternative — incremental movement in an exponential environment — carries greater risk. The companies that choose momentum over mastery, democratize innovation, and redeploy capacity toward advancing healthcare value will define the next era of pharmaceutical leadership. In healthcare’s digital dawn, restlessness is not a warning sign. It is an invitation — to act, to learn, and to lead boldly.
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