In a sterile Bristol Myers Squibb lab about an hour north of Boston, scientists in scrubs and hairnets transfer living cells to a 2,000-liter stainless steel bioreactor that grows them for weeks. The goal is to produce proteins that are genetically engineered to attack cells that cause disease.

Tiny variations in heat, light or pH level can stop the cells from growing, causing drug shortages that endanger patients. Typically scientists would have to wait to see what went wrong during that fragile process, but now artificial intelligence is used to carefully monitor important variables — such as temperature and oxygen levels — and alert technicians if there are problems.

Every year the World Economic Forum and McKinsey recognize manufacturers that are on the cutting edge of technology, including artificial intelligence. This year, the Bristol Myers Squibb facility in Devens, Mass., was the only manufacturer in the United States that made the list of 23.

While American companies typically lead in artificial intelligence research and capital investment, U.S. manufacturers often struggle to translate those breakthroughs into productivity gains on the factory floor.

Of the 223 factories that have made the World Economic Forum’s Global Lighthouse Network list since 2018, 14 have been in the United States, while 99 are in China. Of the American ones, four are in the pharmaceutical and life sciences sector.

“China is scaling faster,” said Rahul Shahani, a partner at McKinsey who works with the World Economic Forum on the initiative. He added, “They have technologists in the factories — hundreds of them — while in the U.S. we’re competing for that same talent with Silicon Valley.”

Large American pharmaceutical companies have been a rare bright spot in the use of A.I. Many drugmakers, including Pfizer and Eli Lilly, are investing billions in A.I. and related technologies to accelerate drug discovery and streamline manufacturing. The trend coincides with President Trump’s demands that drugmakers produce more drugs on U.S. soil.

Scientists at the Devens facility use artificial intelligence to discover molecules that can target cancer and other diseases with greater precision. A.I. can comb through data sets from past experiments to identify possibilities that a human might not have considered. Researchers then test those molecules in the virtual world — a process referred to as “in silico.” Only the most promising are tested in a physical laboratory. The company can run multiple “in silico” experiments at a time.

“Drug discovery and bio-manufacturing are definitely areas where A.I. can have the most impact,” said Kyle Chan, a fellow at the Brookings Institution’s John L. Thornton China Center. “These are areas where A.I. has some of the largest advantages over previous approaches given the need to process and synthesize large, complex data sets.”

Still, there’s no guarantee that technological advantages will instantly equate to benefits for patients. The history of drug development is filled with failures, and it is unknown whether molecules identified by A.I. will pass muster in clinical trials.

The Bristol Myers Squibb facility sits on an 89-acre campus where buildings are decorated with portraits of cancer survivors..

Previously, scientists and technicians were never sure why some batches of cells produced a large amount of proteins, while others failed completely. But now A.I. uses information from past batches to identify what variables need to change. For example, if oxygen levels are lower than previous batches, the system will suggest that oxygen be added. If the pH levels are higher than previous batches, it will recommend a fix. It also makes suggestions about the best time to harvest the cells.

These innovations have boosted the volume of drugs produced for clinical trials and commercial use at the facility by about 40 percent, according to a company spokeswoman.

“We are able to now intervene in the batches during the manufacturing process and not have to wait until we get to the end,” said Karin Shanahan, executive vice president, chief supply chain and operations officer for the company.

These innovations have helped stabilize production of Orencia, a drug that treats autoimmune conditions such as rheumatoid arthritis using cells that are extremely difficult to grow. In 2024, manufacturing challenges resulted in a shortage in some parts of the world.

The company is just beginning to use A.I. in its manufacturing process of another drug, Breyanzi, which turns a cancer patient’s own white blood cells into a personalized therapy. Currently, the Devens plant is authorized by the Food and Drug Administration to produce treatments for just 12 patients at a time.

Ms. Shanahan said she hoped that eventually A.I. would increase production of the treatment, often viewed as a last resort for people with blood cancers such as leukemia.

Bristol Myers Squibb has embarked on a series of cost-cutting measures as the key patent for its cancer drug Opdivo expires in 2028. The drug, which uses proteins that have been genetically engineered to target cancer cells, generated more than $10 billion of the company’s $48 billion in revenue last year.

The company is trimming $2 billion in costs by the end of 2027 in addition to $1.5 billion in cuts announced in 2024. More than 1,000 positions are being eliminated, many of them at a research facility in Lawrenceville, N.J., heightening anxiety about A.I.’s taking jobs away in the sector.

At the Semafor World Economy summit last month, Bristol Myers Squibb’s chief executive, Chris Boerner, said the company had a responsibility to use A.I. to further its mission but acknowledged that it could adversely affect some employees.

“We are engaging with those employees to make them more marketable around this technology — with the company or elsewhere,” he said.

The facility in Devens, which was completed in 2009 at a cost of $750 million, wasn’t designed with A.I. in mind. As recently as 2020, employees used Excel spreadsheets for some tasks. Batch records that document every step of production were filled out by hand. But in recent years, the company has prioritized digitizing and automating its processes.

“We needed to make sure that we could formulate our products faster, that we could commercially scale them faster,” Ms. Shanahan said. “And so that’s really what forced us to start to go down that path.”

Overall the company aims to cut the time it takes to bring a drug to market to about six years, from nine, she said.

Other factories that received recognition from the World Economic Forum this year included Yueda Textile in Yancheng, China, which collects sensor data to detect machine maintenance issues before they occur, reducing costs; and Midea, a manufacturer of microwaves and air-conditioners in Thailand that uses A.I. to investigate customer complaints, generating recommendations for corrective action that cut resolution time from months to days.