Healthcare’s AI returns are already knocking on back office doors, and Bessemer’s new ROI Scorecard says it’s only a matter of time before they get to clinical workflows.
ROI arrived twice as fast as expected. According to the survey of 226 healthcare execs, AI returns are typically showing up within 12 months, averaging 3.5x and beating expectations in 40% of use cases.
- That’s especially big news since most buyers underwrote 24-month paybacks, meaning that orgs still modeling that assumption are underinvesting against their own results.
The back office leads the pack. Revenue cycle management topped every measure, with 4x ROI and two-thirds of provider execs actively running semi- or fully autonomous agents.
Here’s the ROI breakdown by use case:
- Provider revenue cycle: 4.0x
- Payer claims: 3.4x
- Payer provider network: 3.3x
- Member engagement: 3.2x
- Provider front office returns: 3.1x
- Provider clinical: 2.9x
Automation leads straight to attrition. One of the most surprising stats was that half of orgs have already reduced headcount as a direct result of AI, or plan to within six months.
- Reductions currently average 8% to 13% of the affected functions, which are a mirror image of the AI returns.
- Among providers reporting cuts, 73% named revenue cycle and medical billing, which posted both the highest AI return and AI autonomy.
The three-year forecast is already here. Last year, 84% of execs expected AI to transform clinical treatment decisions within 3 to 5 years. A year later, 71% say it already has.
- As always, trust is the biggest barrier for clinical AI. Nearly half of respondents (46%) trust AI to support clinical decision-making, yet 77% override the AI’s suggestions more than half the time.
Most of the value still lies ahead. Execs expect “materially more” AI returns to be realized over the next 12 months, and the leading indicators can apparently already be seen in empty back office cubicles.
- Over half of next year’s incremental AI investment will go toward deployment: 35% to scaling proven use cases and 20% to integrating them into existing workflows, versus 13% for infrastructure and 11% for foundation model licensing.
The Takeaway
While most of these surveys hint at where the AI puck is heading, BVP just showed where the return already is. Turns out it’s the exact same places that provider orgs are already cutting staff.
