Survey Says: Pharma’s AI Revolution Hinges on People, Not Just Tech
By Simon Smith , EVP Generative AI, Klick Health
I've spoken with hundreds of pharma and biotech leaders this year about their experiences with generative AI. One thing is clear: while many companies are excited about AI, their adoption strategies vary widely. Some fully embrace it, giving employees widespread access to tools like ChatGPT Enterprise. Others are hesitant, erecting barriers that slow progress. In my conversations, companies that encourage experimentation and sharing of use cases tend to be the most successful.
But are these observations just anecdotal? To find out, we collaborated with the Digital Health Coalition (DHC) to survey a representative sample of senior industry executives. Some survey results confirmed what I've seen firsthand; others surprised me. Here are three of the most interesting findings:
1. Adoption Is Higher than the Knowledge Worker Average
We knew AI adoption was increasing, but pharma can often be a technological laggard. This doesn’t seem to be the case with generative AI. An impressive 95% of respondents use generative AI professionally. Specifically, 17% use it multiple times per day, and 25% use it daily. This surpasses the 75% professional usage Microsoft reported in its May 2023 survey of knowledge workers.
Interestingly, frequent personal use is even higher: 28% of respondents use AI multiple times a day for personal tasks. This suggests that while AI is becoming a critical work tool, it's already deeply integrated into people's personal lives. Tools like ChatGPT are so intuitive that they seamlessly transition from personal to professional use.
2. Use of Established Tools Is Growing
A key takeaway from the survey is that more people are using established generative AI tools for work, whereas many companies previously opted for internal tools that called model APIs. For instance, 31% of respondents reported using ChatGPT professionally, making it the most commonly used generative AI tool in the industry.
This aligns with early adopters like Moderna and Genmab, where AI tools are accessible to everyone, fostering experimentation and rapid innovation. At Moderna, after rolling out ChatGPT Enterprise company-wide, employees created 750 custom GPTs in just two months—including 400 in R&D—for legal and clinical research tools. Similarly, Genmab encouraged employees to engage directly with AI, leading to over 100 custom GPTs and saving an average of 3.5 hours per employee per week.
In contrast, from informally surveying attendees at presentations, some companies see fewer than 10% of employees using generative AI, despite leadership prioritizing AI adoption. These companies often impose barriers—like requiring special access requests or pushing unfamiliar and limited internal tools—that slow adoption and stifle innovation. I think the lesson is clear: Companies that provide easy, widespread access to familiar tools achieve the most success.
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3. People, Not Technology, Are the Biggest Barrier
The survey confirmed what I've observed: people, not technology, are the real challenge. Only 5% of respondents cited high implementation costs as a barrier—a rarity for new technology. Instead, 37% of responses identified issues like lack of skilled personnel, resistance to change, and inadequate education as the biggest obstacles.
This aligns with findings from the Boston Consulting Group (BCG), which noted that 70% of the effort in AI initiatives should focus on people—training, cultural adoption, and upskilling—while only 30% should focus on technology and algorithms. Successful companies like Moderna and Genmab have fully embraced this people-centric approach.
The Takeaway: Experiment, Invest in People, and Expect Improvement
So, what can we learn? Based on my client conversations, DHC survey data, industry case studies, and reports from industries beyond pharma, it's becoming clear that companies succeeding with AI are those that:
So experiment, invest in your people, and expect the technology to improve. This is how many pharma and biotech companies are now achieving widespread impact with AI, and it’s a formula any company can follow.
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