Small hospitals risk falling behind as RCM AI adoption splits
NEW YORK, UNITED STATES — A new survey of more than 200 healthcare decision-makers finds AI adoption in revenue cycle management (RCM) accelerating sharply — and raising concerns that smaller, resource-constrained providers are getting left behind, Oliver Wyman reports.
RCM AI adoption surges across systems
Oliver Wyman‘s 2026 Healthcare RCM Survey found 63% of healthcare organizations have integrated AI-powered automation into revenue cycle workflows.
Eighty percent of health systems are actively exploring, piloting, or implementing generative AI for RCM — a 38-percentage-point increase in under two years.
But only 20 to 40% of organizations report enterprise-wide deployment across the full revenue cycle value chain.
The gap between broad adoption and deep implementation tracks closely to organizational size and technical infrastructure. Academic medical centers and large regional systems are better positioned to cross it. Local and rural hospitals often are not.
The Oliver Wyman survey found 92% of respondents agreed “there are no-regret AI investments to pursue” across the revenue cycle — with top use cases including ambient documentation, clinical documentation improvement (CDI), coding automation, and electronic prior authorization (ePA).
Lagging adoption carries financial consequences
Providers that have moved furthest in AI deployment are reporting gains that smaller hospitals cannot yet match.
The survey found accuracy reaching 90% or higher in specific clinical domains for capturing clinical complexity — and up to nearly 46% reductions in coding time for complex cases.
Hospitals that cannot close those efficiency gaps face growing pressure on already-thin margins.
Seventy to 90% of decision-makers expect to increase spending on AI-enabled RCM capabilities over the next three years.
For local and rural hospitals — already operating with fewer staff, tighter budgets, and legacy technology infrastructure — that trajectory compounds existing disadvantage.
The providers least able to fund AI investment are the ones with the most to gain from it.
The Oliver Wyman survey covered providers across the full care spectrum — from local and rural hospitals to academic medical centers and multi-state health systems.
That breadth makes the adoption gap visible. The technology is spreading fast. Not everyone can capitalize on it.
The healthcare outsourcing sector — a multibillion-dollar industry covering revenue cycle management, medical coding, prior authorization, and claims processing — provides one route for smaller providers to access AI-powered RCM capabilities without building the infrastructure in-house.
For rural hospitals and independent practices navigating a technology investment cycle they cannot fully fund, outsourced RCM is a direct path to the efficiency gains the Oliver Wyman data now quantifies.
