LAS VEGAS — Top executives from major U.S. technology companies gathered at this year's HLTH conference, pledging to lead the next wave of innovation in healthcare artificial intelligence.

AI products launched by companies such as Google, Microsoft, Amazon, GE HealthCare, and NVIDIA claim to help healthcare systems solve a range of issues, from reducing documentation time to optimizing operating room scheduling. Tech executives said they have moved beyond the early iteration of AI tools, which were oftenpoint solutions, and are now offering platform-based solutions that can be tailored to the needs of individual healthcare systems.

"We are truly at an inflection point," said Sally Frank, Microsoft's global lead for health and life sciences.

However, as tech companies pitch their products to healthcare systems and providers, executives are divided on how to responsibly deliver new technology to the industry and whether clinicians are equally ready to use these new tools.

"Any evaluation we do at the foundation model level is just a first draft," said Greg Corrado, senior research director at Google and co-founder of the Google Brain team. "It really needs to be led by healthcare systems that are willing and able to do research on the ground, and not every healthcare system can do that."

Tech companies emphasize platform approach

Tech companies are positioning themselves as partners to healthcare organizations in AI development, offering deep expertise in product development and testing.

Yet tech executives at HLTH were cautious, saying they rarely tell healthcare systems how AI should be applied.

"Google is not a healthcare provider, and we don't want to be a healthcare provider," Corrado said.

The executive said AI use cases should come directly from healthcare systems. Tech companies are like semiconductor chip manufacturers—they produce resource-intensive, high-value raw materials—in this context, large language models—which the healthcare industry then applies, Corrado analogized.

"The technology we develop should enable healthcare organizations to envision and build their own future in this space," he said.

Google has partnered with healthcare organizations such as Cleveland Clinic and Community Health Systems to pilot technologies ranging from a healthcare-specific cloud platform to document tools that search electronic health records.

Other tech companies, including Microsoft, have launched similar collaborations encouraging healthcare systems to customize their own AI solutions.

This commitment "opens the door to going beyond 'out-of-the-box' tools solving 'direct use cases'," said Keith Hettich, Microsoft's vice president of product marketing for health and life sciences.

In October, Microsoft said it would make it easier for healthcare systems tobuild their own AI tools directly. The company is also using generative AI to help healthcare systems organize unstructured data as well as imaging and medical image data, enabling customers to "build their own copilots, their own AI agents," Hettich said.

Bill Fera, principal at Deloitte, believes healthcare systems may favor such tools over earlier products.

"I think as people become more familiar with building and operating their own, the hyperscalers and platform players will take over this space," Fera said in an interview. "There will be a shift from applications to proprietary platforms."

Robust testing demands raise accessibility concerns

In healthcare, tech companies say they are currently focused on helping systems cope with information overload. Executives said their ability to process vast amounts of data in written form and images helps shorten the time providers spend reviewing records orscheduling patients for critical surgeries.

But different AI applications require varying levels of human oversight.

Currently, tech companies at HLTH agree that all healthcare AI should have human oversight. Some companies are focusing first on administrative AI tools because they require less oversight. At GE HealthCare, for example, a scheduling tool may require less oversight than a tool that assists with cancer treatment.

"We think these areas can adopt AI very quickly because they are not directly tied to clinical decision support," said Abu Mirza, general manager of digital products and global senior vice president at GE HealthCare. "They are not directly tied to decisions about someone's surgery. That's where AI can really get started."

However, Google's Corrado said that when AI approaches clinical decision points, more rigorous testing is necessary.

AI "hallucinations"—where models produce answers unsupported by source text—have drawn widespread attention.

But Corrado believes omissions deserve equal attention. Omissions occur when AI fails to cite relevant information in its answers. In some ways, omissions are harder to test because they require a comprehensive review of often lengthy medical records.

However, Microsoft and Google executives said not every healthcare system has the resources or expertise to rigorously test cutting-edge technology.

According to Hettich, Microsoft hasconnected healthcare systems seeking to use AI, allowing more advanced systems to provide resources and knowledge to smaller systems before deployment. The alliance includes more than 15 hospitals and healthcare systems, including Providence, Advocate Health, Boston Children's Hospital, Cleveland Clinic, CommonSpirit Health, and Mount Sinai Health System.

Microsoft provides voluntary testing guidelines for users of its AI products.

"We give them guidance and technology so you can build visibility and transparency into the system... It's a bit like, 'Hey, here's how we build this, here's how we think about responsible AI,'" Hettich said.

According to the executive, Microsoft also benefits from the exchange of information. While Microsoft offers its perspective on how to implement AI, the exchange is two-way. He said engagement with leaders from some of America's top healthcare systems helps build trust in Microsoft's products and establish credibility.

Hettich believes this broad spirit of collaboration is relatively new. He thinks it can help smaller healthcare providers access new technology and serve as a "catalyst" for broader adoption of generative AI in healthcare systems.

Google, however, doesn't just recommend that healthcare systems test its AI—the company almost mandates it.

Corrado said clinical feedback is integral to Google's testing process, so far the company has only worked with healthcare systems that have a certain level of "maturity" in AI and share its values on model testing.

"I think those healthcare systems that want to buy ready-made solutions—maybe they should wait. They should wait for the technology to mature and stabilize," the researcher said. "I don't think in any [healthcare] context there is an evaluation framework mature enough that you can just deploy the technology... Nothing is set in stone. You have to put it in a real environment, evaluate how it performs in actual use, and adjust accordingly."