Athenahealth embeds AI to overhaul healthcare workflows
MASSACHUSETTS, UNITED STATES — Athenahealth is fundamentally re-engineering its flagship athenaOne platform with embedded artificial intelligence to solve long-standing healthcare inefficiencies.
The company announced a pilot of a new AI model for interoperability aimed at ambulatory care practices, a move designed to streamline clinical workflows and revenue cycle management by contextualizing vast amounts of disparate data directly within a provider’s daily operations.
Athenahealth recently ranked #38 in the OA500 2025, an objective index of the world’s top 500 outsourcing companies.
AI tackles long-standing interoperability roadblocks
The initiative centers on deploying a Model Context Protocol (MCP) server on the athenaOne platform’s APIs. This technical foundation is crucial as it standardizes communication between various AI models and the core electronic health record (EHR) system.
The goal is to break down data silos that have historically plagued healthcare providers, creating a seamless flow of information.
This architecture is composed of real-time processing and incoming data consisting of other EHRs, other hospitals, other registries, other payers, and data aggregators.
Being used in the context, such knowledge can be converted into actions and integrated into the clinical workflow to give the providers a rich, longitudinal patient history at the point of care without altering applications.
“We are building the future, using intelligent interoperability to methodically break down the walled gardens that have constrained independent practices for more than a decade,” said Bob Segert, chairman and chief executive officer at athenahealth.
“By layering custom-built, AI-enabled solutions onto our industry-leading approach to interoperability, we’re making the promise of interoperability a reality.”
AI tools target administrative and clinical burdens
Beyond interoperability, athenahealth is rolling out a suite of specific AI-driven tools designed to alleviate significant administrative burdens.
These enhancements include next-generation Document Services that utilize machine learning to read over one billion pages of faxes received by practices annually, automating a traditionally manual and error-prone task.
Another feature, Intelligent Summaries, will soon enter alpha testing to provide clinicians with quick overviews of complex patient records.
Further innovations in testing are ChartSync for improved data alignment and Chart Assist, an AI-enabled assistant for physicians that is currently in alpha. The company has stated that additional capabilities focusing on the revenue cycle and patient engagement will be unveiled soon.
“Rapid advances in AI are now allowing us to reimagine the clinician and practice experience, solve previously unsolvable problems, and bring back the human side of healthcare,” said Segert, noting the shifting focus from paperwork to patient care.
This builds on the company’s established leadership in interoperability, having been the first to implement the Trusted Exchange Framework and Common Agreement (TEFCA) across its eligible customer base—an effort recently recognized by the White House.
