Artificial intelligence (AI) has now reached a crucial tipping point in the way U.S. healthcare plans carry out their operations. A study by Everest Group, supported by Sagility, found that 70% of health plans have introduced AI tools to streamline both administrative and clinical activities. Nevertheless, 84% of payer executives say that they have seen limited benefits from these implementations and just 10% have noticed measurable improvements in operations.

The fact that these systems are not aligned points to a fundamental error in the digital transformation of healthcare, namely the belief that simply adding automated tools to the scattered existing infrastructure will automate the current state of chaos instead of enabling operational efficiency.

Healthcare administrative spending in the U.S. is approximately $1 trillion annually, costs that result in part from manual processes, complex clinical reviews, and the lack of systems integration. Although technology frequently functions as a quick fix, achieving true operational efficiency involves some fundamental rework. Before introducing automated tools, health plans should re-engineer their workflows end-to-end to ensure the optimal use of AI. Only by restructuring workflows will health plans harness AI as an intelligence amplifier for human healthcare experts to implement specialized clinical judgment rather than replace it.

For many years the administrative and clinical operations of health plans have worked in isolation. The handling of claims, utilization management (UM), payment integrity, and member services have usually depended on separate platforms, manual transfers between them, and outdated rules engines.

When health plans try to modernize by adding AI models or robotic process automation (RPA) directly onto these disjointed systems, the fundamental problems still exist.

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