The healthcare AI world will likely undergo another year of rapid transformation in 2026, colored by fast-moving experimentation and adoption, according to a report published this week by Bessemer Venture Partners.
“This has been, since ‘21, one of the most exciting times in our industry. There is an reinvigorated interest and excitement about the role that technology can play in healthcare. Before, we were very limited in terms of what we were capable of with technology, and therefore we needed to use people — which made a lot of these models really hard to scale. And I’m hoping that in 2026, we can really start to see the impact of technology for better engagement and view of a patient,” said Sofia Guerra, partner at Bessemer, during an interview on Thursday.
Below are four of the boldest predictions from the venture capital firm’s report.
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Payers will play AI catch-up
Providers’ rapid adoption of AI could push payers to accelerate their own use of administrative AI tools.
So far, most successful healthcare AI companies have focused on providers, especially on administrative layers like revenue cycle and payments, Guerra pointed out.
Providers have been more willing to test and adopt these technologies, while payers have faced headwinds, such as escalating compliance requirements, and are only now beginning to reconsider partnerships with startups rather than building solutions entirely in-house, she stated.
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In Guerra’s view, 2026 could be a turning point in how payers deploy AI tools and engage with AI startups.
Clinical AI adoption will grow
Bessemer’s report predicts a rise in clinical AI applications, mainly for triage and assessment, and with human clinicians in the loop. The firm also thinks that CMS will launch new programs to establish billing codes for clinical AI.
Guerra noted that CMS has been vocal about its efforts to leverage AI to expand access and improve care. She highlighted the potential for AI-driven diagnosis, remote patient monitoring and longitudinal care, but emphasized the need to navigate regulation and reimbursement models like CPT codes and CMS experiments.
The report also pointed out that cash-paying patients will accelerate the adoption of clinical AI faster than any reimbursement code, as these consumers are typically motivated by convenience, faster access and the promise of more accurate or personalized care.
This clinical AI adopting among cash-pay consumers can take the form of AI-powered primary care visits, second opinions on imaging or subscription-based health AI coaches that track wearable metrics and flag risks.
Health AI data infrastructure will become a new category
Health AI data infrastructure could emerge as a nascent category in the digital health world, according to Bessemer’s investors.
“For a long time, we’ve seen many attempts to build interoperability startups or horizontal healthcare-specific infrastructure companies in this space. They struggled to really reach scale or capture value because they have limited types of buyers,” Guerra explained.
But today, demand is rising for tools that can access and transform healthcare data in a HIPAA-compliant way, both from healthcare organizations and external AI labs seeking unique datasets, she stated.
She thinks the key questions for 2026 are whether this demand is sustainable and whether independent healthcare-focused companies can capture meaningful market share, or if large horizontal players like AWS, Snowflake and Anthropic will dominate the space.
There will be a new class of AI-powered value-based care companies
A wave of AI-first value-based care companies is poised to emerge and grow, Guerra argued.
She sees two types of companies: established tech-enabled or value-based care businesses using AI as a tool, and entirely new AI-first companies built from the ground up.
The AI-first model focuses on engaging patients through digital tools, triaging their needs and providing a holistic view of care at scale — rather than relying on human coordinators, she explained. Guerra said that launching such companies will require a new type of entrepreneur with deep healthcare expertise, as this approach differs from simply adding AI to existing, scaled operations.
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