Nearly 80% of payers prefer vendor-built AI solutions, survey finds

Nearly 80% of payers now prefer implementing vendor-built artificial intelligence tools rather than developing internal capabilities, a new survey from Innovaccer found.

The survey draws insights from 63 health insurer organization leaders, including regional health plans to national carriers, the healthcare technology and AI company said in a press release. Respondents were polled in mid-December 2025 to mid-January, and include senior and C-suite executives.

Innovaccer CEO and co-founder Abhinav Shashank told Fierce Healthcare that the shift to outsourced solutions reflects the focus of how to “truly operationalize AI.” 

“What we are seeing is an emergence of how do you have platforms that companies can effectively offer that allow for more agentic orchestration,” Shashank said. “Because the reality of it is the technology is going to be a massive addition to how payers operate.” 

Like patients and providers, AI use is surging among payers. Nearly 78% of respondents in Innovaccer’s survey report using solutions to improve care, and three-quarters report “aggressively pursuing or progressively experimenting” with AI in care innovation.

Planned investments further emphasize the shift, with 75% of respondents reporting plans to spend an average of $10 million on AI over the next three to five years. A third of respondents report planned investments of at least $20 million.

However, 86% percent of respondents, said they are not fully ready to operationalize AI at scale. Shashank said the most important aspect of doing so is the “context and data infrastructure” behind solutions.

The survey notes payer data often exists in “legacy systems and silos,” which can limit the pace of AI adoption. Interoperability was the top-reported infrastructure barrier, followed by real-time data access, inadequate data architecture and cloud capabilities.

“Enterprises don't necessarily have the core data infrastructure and context infrastructure to be able to operationalize these AI frameworks at scale today,” he said, adding that companies should “build out” necessary infrastructure. 

Moreover, according to Shashank, the readiness of the industry is “very dependent” on systems having the right data and context infrastructures. 

“If you do not have that data and context infrastructure, most of the efforts and investments in AI are not necessarily going to scale for you as an enterprise,” he said.

RELATED: 

Despite barriers, 44% of respondents report viewing AI as critical to organizational member care objectives and 62% identified deploying AI to support personalized member navigation as “the use case critical to payer success” over the next three to five years.

“A fundamental shift that we are starting to effectively see [is] that instead of people buying AI, people are now trying to solve problems using AI,” Shashank said.