Albert Bourla rarely makes a major decision alone. The Pfizer chief executive still consults trusted colleagues. Yet he now adds one more voice to the room. That voice never gets tired, never takes offense and often spots angles his human advisors miss.
“A CEO’s job is multifaceted, of course,” Bourla told Accenture CEO Julie Sweet in a recent conversation. “But all CEOs have one common thing, which is they have to make one or two decisions every day, but they are very impactful.” He selects different people for different calls. “I still do that, but I started adding AI.”
The admission, shared on CNN’s “The 1 on 1,” surprised few inside the pharmaceutical industry. It confirmed what many executives already sense. Artificial intelligence has moved from the lab bench into the corner office. And Bourla does not treat the technology as a novelty. He treats it as another experienced counselor. Yahoo Finance reported the exchange in detail this week.
Sixty-four percent of CEOs now say they feel comfortable using AI-generated input for strategic decisions. That finding comes from a global study by the IBM Institute for Business Value. The number signals a quiet but decisive shift. Boards and investors increasingly expect leaders to demonstrate fluency with these tools. Those who cannot may soon appear behind the curve.
Bourla’s personal practice reflects deeper changes at Pfizer. The company has spent years embedding AI across discovery, clinical development, manufacturing and safety monitoring. Results have begun to show. During the race to produce Paxlovid, AI and machine learning helped shrink development from a typical four years down to four months. Computers designed molecules. Scientists synthesized fewer candidates yet recorded higher success rates. Bourla described the episode in a wide-ranging interview with Fortune.
The same acceleration now applies to oncology. More than 40 percent of Pfizer’s annual research and development budget flows into cancer programs. Survival rates for certain bladder and prostate cancers have doubled in recent years. Bourla believes many tumors could one day be managed as chronic conditions rather than acute threats. AI contributes by identifying trial participants earlier, analyzing patient data faster and suggesting protocol adjustments on the fly.
Yet Bourla insists technology alone will not deliver the gains. Culture must change first. After the pandemic, he pushed teams to stop explaining why ideas seemed impossible. “Find solutions,” he told them. The directive echoed across the organization. Employees learned to replace lengthy slide decks that listed obstacles with proposals that solved them. That mindset shift, paired with AI, produced measurable speed.
Pfizer now runs AI-driven tools in more than half of its clinical trials. Data quality checks finish 50 percent faster. Patient recruitment improves because algorithms scan electronic health records for matches that humans might overlook. Regulators have accepted some of these approaches. The Food and Drug Administration reviewed Pfizer’s COVID vaccine data after an AI-assisted process delivered clean datasets in roughly 22 hours instead of weeks.
But the company’s ambitions extend beyond speed. Executives want to raise the baseline success rate of clinical programs, which historically hovers near 10 percent industry-wide. Chris Boshoff, Pfizer’s chief scientific officer, described plans to recruit and embed AI engineers directly into discovery, regulatory affairs, safety, pharmacovigilance and trial execution teams. Their mandate is simple. Measure everything: productivity, speed, cost. Then improve it.
Financial pressure adds urgency. Pfizer posted $62.6 billion in revenue for 2025, a modest decline. Earnings per share came in at $1.36. Guidance for 2026 calls for revenue between $59.5 billion and $62.5 billion. Bourla has labeled the coming year a “key catalyst” for longer-term growth through 2030. The company will launch 20 pivotal studies. It spent $10 billion to acquire Metsera and its obesity assets. AI must help fund that pipeline by driving efficiencies. Pharmaceutical Technology covered the earnings and outlook in February.
Training the workforce represents another priority. Fear of the unknown remains the biggest obstacle, Bourla has said repeatedly. To counter it, Pfizer created an AI Academy that offers structured courses and certifications. Thousands of employees have completed foundational training. The program sets “AI fluency” as an enterprise development goal alongside traditional performance metrics. Every function, every level, must reach a baseline level of competence.
Bourla completed the same foundational course himself. “I saw huge difference in my ability,” he noted in a Pfizer publication. The experience convinced him that personal engagement with the tools matters more than top-down mandates. Colleagues now use internal chat platforms and peer networks to share successful prompts and workflows. The goal is not to replace judgment but to sharpen it.
Partnerships multiply the effect. Pfizer expanded its agreement with Saama Technologies to integrate AI across the research and development portfolio. It joined the Ignition AI Accelerator with NVIDIA and Singapore-based organizations to optimize discovery, manufacturing yields and stakeholder coordination. A collaboration with Boltz, PBC focuses on biomolecular AI foundation models. Each deal brings specialized talent and computing power that would take years to build internally.
Analysts watch these moves closely. Some question whether AI will truly deliver novel medicines or merely speed up existing processes. Early AI-designed molecules have reached Pfizer’s review stage. Bourla confirmed the company has evaluated its first fully AI-generated candidate. He wants Pfizer at the forefront of the technology rather than chasing competitors.
The stakes are high. Pharmaceutical margins face pressure from patent expirations, generic competition and demands for lower drug prices. Any tool that compresses timelines by months or years can add billions in net present value. A single successful oncology drug can generate peak sales well above $3 billion annually. Multiply that across a pipeline strengthened by AI and the financial case becomes obvious.
Investors have taken notice, even if they cannot always trace the connection. Many hold Pfizer shares inside broad healthcare or technology funds without realizing how deeply AI now influences executive decisions. Those decisions shape capital allocation, acquisition strategy and clinical priorities. They ultimately affect earnings and stock performance. The IBM study suggests this pattern will only spread. CEOs who once viewed AI as an IT project now see it as a strategic co-pilot.
Bourla draws a clear line. AI does not replace human accountability. It supplies additional perspectives. When he feels lingering doubt about a choice, he queries the model, then tests its output against his own thinking and the counsel of colleagues. The process resembles a rigorous debate with an exceptionally well-read participant that never tires.
That approach may soon become standard. Other pharmaceutical leaders have begun public experiments with similar tools. The difference at Pfizer lies in scale and integration. From the CEO’s desk to the bench scientist’s workstation, AI has become part of daily operations. Training programs ensure adoption does not remain limited to a few power users.
Challenges persist. Data privacy, regulatory acceptance and the risk of over-reliance on flawed models require constant vigilance. Bourla acknowledges these issues without letting them paralyze progress. He points to the COVID programs as proof that thoughtful application can deliver results under intense scrutiny.
Looking ahead, Pfizer expects AI to help unlock insights from the massive datasets generated by its existing medicines and vaccines. Real-world evidence, wearable devices and electronic health records contain patterns no human team could fully analyze. Machine learning models already flag potential safety signals earlier than traditional pharmacovigilance methods. They also suggest new indications for older compounds.
The company’s second annual AI Festival brought together employees, external experts and hands-on labs. Attendees left with greater confidence and concrete ideas. Such events reinforce the cultural transformation Bourla seeks. Curiosity replaces fear. Experimentation becomes routine.
In oncology, timing is everything. A few months saved in development can mean the difference between a patient receiving a therapy or not. AI now helps match the right patient to the right trial with greater precision. It compresses the time from hypothesis to first-in-human study. These gains compound across dozens of programs.
Bourla remains optimistic. He believes many cancers could transition from life-threatening diseases to manageable chronic conditions within the next decade. AI will not achieve that outcome by itself. It will, however, provide the speed and analytical power necessary to test more hypotheses, fail faster on the unproductive ones and advance the promising candidates with confidence.
The CEO’s own use of AI for his most consequential decisions offers a window into this future. What begins as a personal productivity hack can scale into organizational advantage. Pfizer aims to prove the model works at the highest level of the industry. Other companies will watch closely. So will the investors whose portfolios quietly ride the outcome.
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