AI has shifted from a side topic to a central theme in the biopharma world. Over the past year, multibillion-dollar AI collaborations have become routine, chipmakers have found new demand in drug research, and industry events have turned into forecasting sessions about how machine learning might reshape the lab.
To get a reality check, Endpoints Signal, a data and insight service created by Endpoints News, asked its readership how AI is affecting their actual work. The survey explored where the technology is helping, where it falls short, and how views differ among researchers, corporate leaders, and the investors who support them.
The responses paint a mixed picture. Many report that the current influence of AI is limited or inconsistent, even after years of investment. More than half of the 441 participants described the present impact as modest or negligible. Only a small minority (15%) said the technology is transforming research at this stage.
Several argued that venture valuations are being inflated without a scientific basis. Others said AI steals attention from companies more likely to produce real therapies. A few shared frustrations that internal AI assistants cannot access essential data, leaving them more like toys than tools.
However, beneath those complaints sits a sharp divide. 50% of the respondents say they rely on AI regularly, from hit identification models to language systems that draft regulatory files. Those who work with AI regularly report noticeable shifts in their daily routines, and that experience shapes their overall optimism.
Opinions start to align when respondents look ahead. Approximately 75% anticipate that AI will significantly reshape drug research and development by 2030, while 12% believe the shift could occur within three years.
Their confidence is influenced by recent moves from major companies, including Eli Lilly’s effort to build a large Nvidia-powered research computer and the OpenFold3 project, which brings together companies like AbbVie and Takeda to pool protein data. Billions of dollars have also been invested in licensing deals and AI-focused ventures.
Experience appears to be the key driver of enthusiasm. Among those who work with AI often, nine out of ten expect development and discovery to look entirely different by 2030.
Many note that machine learning is not new to life sciences, pointing to earlier generations of tools such as QSAR models. That long history, they say, offers a more grounded view than the hype often associated with modern language models. Researchers and executives are particularly confident about future progress, while investors remain the most cautious group.
Despite widespread concerns about computing shortages, respondents said hardware is not the real choke point. The largest barriers, according to the survey, involve translating models into real biological outcomes (43%) and securing high-quality datasets (31%). Integrating AI with established workflows ranked a distant third at 13%.
The survey also asked respondents who they thought might benefit most as AI spreads. Large pharmaceutical companies have the advantage of size, deep clinical datasets, and the ability to purchase new platforms as fast as they appear.
Even so, many respondents believe that technology companies entering healthcare could claim the software and infrastructure layers that others rely on. They note that in many industries, newcomers with stronger engineering capabilities tend to disrupt incumbents who operate under older constraints.
The survey also points out that the clearest dividing line is not job title but how often someone uses AI. Heavy users see faster progress, fewer integration issues, and a clearer path to transformation. Lighter users see more friction and more uncertainty about meaningful returns.
When the quantum computing solutions being developed by D-Wave Quantum Inc. (NYSE: QBTS) and other companies hit the market, the biopharma industry could experience additional disruption in the years to come.
NOTE TO INVESTORS: The latest news and updates relating to D-Wave Quantum Inc. (NYSE: QBTS) are available in the company’s newsroom at https://ibn.fm/QBTS
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