For the full research report from Bessemer Venture Partners, go to “The Healthcare AI Adoption Index” on bvp.com.

The healthcare industry is undergoing a once-in-a-generation shift at warp speed. The transition is being propelled not by regulation—as was the case with the gradual migration to electronic health records (EHRs)—but by a shared sense of urgency and strategic conviction among payers, providers, and pharmaceutical companies.

Just two and a half years after the launch of ChatGPT, artificial intelligence (AI)—and especially generative AI—has gone from experimental curiosity to boardroom priority. It’s dominating executive agendas as leaders explore how the technology will radically reshape healthcare diagnosis (Dx), delivery, and management, as well as drug discovery and development.

Bain & Company, Bessemer Venture Partners, and Amazon Web Services (AWS) surveyed more than 400 senior leaders across payers, providers, and pharmaceutical companies. The goal was to unpack how healthcare buyers are adopting AI, what “jobs to be done” they are prioritizing, and where the greatest opportunities—and challenges—lie. We provide our assessment of the current state with the AI Dx Index, which can help healthcare companies and investors accurately assess the industry’s AI transformation.

The state of AI: Adoption, roadblocks, and development

Healthcare leaders are confident in AI, and they’re backing it up with real investment. Of healthcare executives surveyed, 95% say generative AI will transform the industry. A slight majority (54%) of respondents are already seeing meaningful return on investment (ROI) at their organization after their first year of generative AI implementations.

But it’s still early days. To determine where AI is making inroads and where it’s headed, we identified jobs to be done across payers, providers, and pharmaceutical companies. We found only 45% of AI applications have moved beyond the ideation or proof-of-concept (POC) stages. In addition, the path to scale is complex: Only 30% of completed POC projects have made it into production.

Providers appear to be the furthest along, with 35% of their POCs in production, while pharmaceutical companies lag with only 24% of POCs in production. One illustration of a fast-moving provider use case is AI-powered ambient scribes for clinical documentation support. Of providers surveyed, 30% are deploying them systemwide, and another 60% are piloting or implementing them.

So, why are so many organizations stuck in the experimentation stage? Even as enthusiasm runs high, key roadblocks are slowing progress from pilot to scale:

• Security concerns top the list for more than 50% of respondents across sectors.
• Lack of in-house AI expertise is the second biggest issue, especially for pharmaceutical companies.
• Costly integrations—especially for payers—create friction.
• Data readiness remains a major pain point, particularly among pharmaceutical companies, where 47% of respondents cite it as a top obstacle.

Budget, however, is not a primary constraint. According to those we surveyed, 65% of AI projects are funded centrally, and most respondents say they have sufficient budget to scale.

What will the AI development landscape look like in the future? Unlike the EHR wave, where vendors drove much of the change, today’s AI innovation is happening in-house. In fact, more than half of all AI development is internal, and only 15% of solutions are currently being built by start-ups. Thus, this era is defined by codevelopment, where internal teams and external partners collaborate to embed AI deeply into existing workflows.

The AI Dx Index: A guide for navigating the ecosystem

Given the speed of evolution in the market, we developed the AI Dx Index, a data-driven framework that evaluates the current adoption of and prospective opportunities related to AI use cases. The goal is to help healthcare companies prioritize focus areas when buying. Our index considers three dimensions:

• Opportunity score: Is there opportunity for AI improvement? Does the job cause a significant pain point? How manual is the effort?
• Adoption score: Where are organizations on the adoption curve?
• Development strategy: How are companies currently approaching these use cases? Who is working on a solution: start-ups, internal teams, or tech incumbents?

Based on our survey data, we position AI use cases on an index where the y-axis is the opportunity score and the x-axis is the adoption score. As AI adoption accelerates, these use cases will move along the maturity curve. With that, the opportunity often narrows, as organizations solve problems and the amount of manual work decreases.

Buyers can use this assessment as a navigation tool. They can benchmark progress to assess how their AI adoption compares with peers’ and to identify mature, scalable solutions. It can also help healthcare IT (HCIT) companies identify high-pain-point, low-automation use cases where they can gain traction early. From the assessment and our broader experience, we’ve identified some key lessons for both parties.

How buyers can navigate AI

For buyers, the deluge of AI pitches and management of dozens of AI initiatives can feel overwhelming. Three key principles can help.

• Foster a culture primed for AI adoption through storytelling, change management plans, and grassroots adoption.
• Establish strong ecosystem relationships, including a range of tech incumbents and start-ups, to form a nimble, adaptive, and responsible AI strategy.
• Make AI adoption a competitive advantage by developing tech where differentiation matters, scaling tools across the organization, and maximizing the value of proprietary data.

How HCIT companies can win

In the current environment, HCIT companies need to stand out from the full ecosystem that includes buyers’ internal teams. To break through, leading HCIT companies will take five steps:

• Pick the right entry points and expand using the AI Dx Index.
• Prove ROI quickly to avoid POC limbo.
• Shift from traditional sales to codevelopment.
• Reimagine a complex workflow from end to end, touting domain expertise over tech novelty.
• Align the business model to delivered value, especially by measuring clear, attributable ROI.

The road ahead: AI codevelopment

AI in healthcare is no longer theoretical. It is growing and transforming the way organizations diagnose, deliver, and manage care. But success won’t come from simply buying tools or launching isolated pilots. Many of those early-stage projects, of course, will fall short. Instead, the winners in this next wave will be the organizations that:

• embed AI deeply into workflows;
• deliver clear and measurable ROI;
• build trust with C-suite decision makers; and
• solve complex problems from end to end, rather than just automating tasks.

Our AI Dx Index is designed to help healthcare buyers and HCITs on this path to success. They can identify the most promising use cases, targeting the greatest pain points, most nascent solutions, and highest-potential transformation. Over time, the gap between hype and real value will narrow, as the industry moves beyond the inflection point and into its future.

About Bessemer Venture Partners

Bessemer Venture Partners helps entrepreneurs lay strong foundations to build and forge long-standing companies. With more than 145 IPOs and 300 portfolio companies in the enterprise, consumer and healthcare spaces, Bessemer supports founders and CEOs from their early days through every stage of growth. Bessemer’s global portfolio has included Pinterest, Shopify, Twilio, Yelp, LinkedIn, PagerDuty, DocuSign, Wix, Fiverr, and Toast and has more than $18 billion of assets under management. Bessemer has teams of investors and partners located in Tel Aviv, Silicon Valley, San Francisco, New York, London, Hong Kong, Boston, and Bangalore. Born from innovations in steel more than a century ago, Bessemer’s storied history has afforded its partners the opportunity to celebrate and scrutinize its best investment decisions and also learn from its mistakes.

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