Operational AI Transforms Healthcare Workflows, Not Just Tasks

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Healthcare organizations are rapidly adopting AI to automate individual tasks like generating summaries, drafting responses, and surfacing recommendations. However, this approach only optimizes isolated tasks and does not redesign the core operating model. To truly transform healthcare operations, AI needs to be embedded into enterprise infrastructure to run workflows end-to-end, even when a step stalls or data is incomplete. This shift towards "Operational AI" is already underway at leading health systems, enabling automatic progression of referrals, eligibility verification, scheduling, documentation, and more, rather than relying on manual coordination by staff.

Why it matters

Most healthcare organizations have more manual work than staff to perform it. While AI promises to take on more autonomous work, many current AI initiatives only accelerate individual tasks rather than redesigning the underlying operating model. To achieve the full potential of AI in healthcare, organizations need to move beyond isolated task automation and embed AI-powered workflow orchestration directly into their enterprise infrastructure.

The details

Operational AI platforms are now running workflows end-to-end across key healthcare domains like Access, Engagement, Intake, and Payment Capture, saving millions of staff hours and coordinating hundreds of automated workflows within the EHR and other systems. This shift enables referrals to progress automatically, eligibility to be verified, outreach to be initiated, scheduling to occur, documentation to update, and care to be delivered without relying on manual coordination by staff. Organizations that treat AI as a standalone feature will continue optimizing at the margins, while those that embed AI into enterprise infrastructure will be able to redesign how work advances across the entire healthcare journey.

• Healthcare organizations have long had more manual work than staff to perform it.
• In recent years, health systems have rapidly adopted AI to automate individual tasks like generating summaries and surfacing recommendations.
• Over the past 2 years, Operational AI platforms have been deployed at more than 50 health systems to run workflows end-to-end across key domains.

What’s next

As healthcare organizations continue to invest in AI, the next five years will be defined by whether they treat AI as a standalone feature or embed it into their core operating model and enterprise infrastructure. Those that take the architectural approach of Operational AI will be able to redesign workflows and advance work continuously across the patient journey.