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Julie Zhang

Pharmaceutical companies have embraced artificial intelligence in drug research almost universally, yet few company executives expect AI to actually make drugs succeed, according to a Citi survey released on Tuesday.
“The biggest risk to the AI-powered drug discovery thesis is not that AI fails to accelerate discovery,” said John Yung, head of Asia healthcare research at the US investment bank. “The stronger risk is that acceleration does not translate into better drugs or higher probability of success.”
“It’s only through that translation that companies can turn AI-driven speed into profit, and patients into real beneficiaries,” Yung added.
Some 72 per cent of respondents said their companies were either “scaling” or had “fully scaled” AI across research and development, and no company reported having no plans to adopt the technology, the survey found.
Citi Research polled 50 US-based executives responsible for technology strategy in pharmaceutical research and development in June 2026.
Yet that enthusiasm comes with a caveat. Only 24 per cent of respondents expected AI to deliver a significant improvement in drug success probability, while 56 per cent expected only a moderate uplift, “not a wholesale revolution,” according to the survey.
Another 34 per cent said human biology, clinical judgment and execution will remain as bottlenecks, regardless of how much AI is deployed.
The findings suggested “executives are genuinely optimistic [with AI], but they are not naive about the complexities of biology”, the survey noted.


Executives saw the biggest near-term payoff in early-stage discovery rather than in the clinic. Target identification and validation was cited by 70 per cent of respondents as an area where AI was expected to improve success rates, followed by lead optimisation and hit identification and screening.
Most respondents expected double-digit budget increases for AI-related R&D spending over the next 12 months.
Shortening discovery timelines was the leading commercial reason companies sought outside AI partners, with 84 per cent surveyed engaging with external AI companies, the survey found.
Business consulting and market research firm Frost & Sullivan estimated AI could save the industry US$26 billion globally at the drug discovery stage and a further US$28 billion in clinical research – about half of current spending in those phases.
Unlike many US companies in the sector that remain loss-making, several Chinese leaders, such as Shanghai-listed DNA-encoded-library maker HitGen and Hong Kong-listed AI drug researcher Xtalpi were already profitable, according to Citi.
They “should see earnings accelerate as robust demand translates into stronger utilisation and operating leverage”, Yung said.
However, valuations paint a different picture.
Leading Chinese AI drug discovery companies trade at a median price-to-sales ratio – a measure of how much investors are paying for each dollar of a company’s revenue – of 19 times their projected 2026 sales, a steep discount compared with the 93 times commanded by their US peers, according to Citi.


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Biomedicine

Survey finds drug companies planned to scale AI or had already done so, but few anticipated a ‘wholesale revolution’ from the tech


Survey finds drug companies planned to scale AI or had already done so, but few anticipated a ‘wholesale revolution’ from the tech.


As China embraces AI, only 24% of US pharmaceutical execs bet on it for innovation

.css-1c6uqr6{color:inherit;font-weight:inherit;font-size:inherit;font-family:inherit;line-height:inherit;overflow-wrap:break-word;}Survey finds drug companies planned to scale AI or had already done so, but few anticipated a ‘wholesale revolution’ from the tech

Survey finds drug companies planned to scale AI or had already done so, but few anticipated a ‘wholesale revolution’ from the tech