Artificial intelligence is often pitched as the future of medicine, with promises ranging from diagnosing diseases to discovering new drugs. In reality, one of AI’s biggest near-term wins may be something far less glamorous: tackling the mountain of paperwork that slows down hospitals every day.
Concord Technologies has released a new report, developed with the American Hospital Association (AHA), arguing that AI could help healthcare organizations improve interoperability by automating many of the manual processes involved in moving patient information between systems.
Interoperability has been a buzzword in healthcare for years. Electronic health records were supposed to make sharing information easy, yet hospitals still juggle scanned documents, faxed records, PDFs, emails, and incompatible systems. The report argues that modern large language models are becoming good enough to extract useful information from these unstructured documents without requiring every organization to follow the exact same data format.
According to Concord’s survey of 73 hospital leaders, 64 percent believe AI will accelerate interoperability across the healthcare ecosystem, while only 9 percent disagreed. The report also points to research suggesting AI models can exceed 90 percent accuracy when extracting certain types of healthcare data, although it acknowledges that the survey is based on a relatively small sample and should not be viewed as representative of every U.S. hospital.
One of the more interesting examples comes from WakeMed in North Carolina. The health system handles more than one million incoming faxes every month as part of its contact center operations. It is deploying Concord’s platform in hopes of automatically extracting patient information and routing it into Epic and other systems, reducing the time staff spend processing paperwork and allowing them to spend more time helping patients.
Perhaps the most encouraging aspect of the report is that it doesn’t treat AI as a replacement for healthcare workers. Instead, it repeatedly emphasizes “human-in-the-loop” workflows where employees review AI-generated summaries and validate the results before any action is taken. WakeMed also says one of its biggest hurdles will be convincing staff that AI is there to eliminate repetitive tasks, not eliminate jobs.
That cautious approach is probably the report’s strongest message. Healthcare is an industry where mistakes can have real consequences, so blindly trusting AI isn’t realistic. Human oversight, governance, and transparency will likely remain essential no matter how capable these systems become.
It’s also worth remembering that this is a sponsored report from a company that sells interoperability solutions. While it cites academic research and includes a real-world case study, organizations evaluating AI platforms should look beyond marketing claims and focus on independent evidence, security, integration capabilities, and measurable results.
Healthcare’s AI revolution may not begin with robot doctors or miracle diagnoses. It may start with something much less exciting but arguably more useful: helping hospitals spend less time pushing paperwork and more time caring for patients.
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