Healthcare & Interoperability
Thought LeadershipBy now, it should go without saying that AI will be a dominant theme at any healthcare conference, and HLTH 2025 was no exception. On the first day of the conference, which drew more than 12,000 attendees, the chief physician executive of the American Hospital Association joked that his panel discussion had to hit a required quota of 67 AI mentions.
Healthcare organizations are clearly embracing AI to streamline operations from the back office to the front desk to the exam room. But the way that companies are talking about AI—or not talking enough about it, in some cases—says a lot about the state of innovation in the industry today.
Here’s what I took away from my conversations and observations at HLTH 2025.
1. AI is solving every problem…but we’re not sure exactly how.
Our senior product marketing manager, Ben Judge, who attended HLTH with me this year, took a few photos of the showroom floor that revealed undeniable similarities.
“Everyone was talking about the power of AI,” he observed across all the exhibitors. “It’s clear that the entire healthcare ecosystem is embracing AI as the key to future innovation, efficiency, and problem-solving.”
This universal excitement is fantastic, yet it also presents a challenge for healthcare decision-makers. With so many platforms claiming to use AI to “increase efficiency” and “solve healthcare’s largest problems,” the sheer volume of similar messaging can create ambiguity. When hundreds of solutions promise to “improve efficiencies, save time, or increase revenues,” it becomes difficult for organizations to discern which platform offers the best solution for their needs.
When I asked many companies what problem they solve in healthcare, they didn’t have a specific use case. The question was pushed back to me to answer what problems do I have. No longer is AI a technology looking to solve a problem, as it was a few years ago. For today’s health technology companies, simply claiming to use AI is no longer enough. They must clearly articulate what problem they solve, precisely how they solve it, and the measurable outcomes they deliver.
I felt more confident in our solutions and positioning after the ambiguous messages on the floor of HLTH. Our products stand out because we have a clear promise about what they do and how we improve efficiency for healthcare organizations: We use intelligent data extraction, an AI-powered approach that transforms unstructured documents, such as faxes, scans, clinical notes, diagnostic images, and medical charts, into structured, actionable data. Using natural language processing (NLP) and machine learning (ML), we are unlocking valuable, insightful information that can help accelerate patient treatment across the continuum of care.
The industry standard for AI typically focuses on post-OCR workflows. However, as the leading digital cloud fax company and eFax® provider, we understand the foundational challenge: unstructured data trapped in scanned images and PDFs.
Manual review and data entry of this information is the root cause of delayed patient care and the inefficient use of clinical staff.
Our difference is expertise in conquering this complex, unstructured data problem at the source. Once we have structured the data, we can then apply our AI solutions to improve existing workflows or seamlessly inject the clean, structured metadata into our customers’ operations.
2. Data transformation is the missing link in workflow automation.
Innovators are leveraging AI to streamline crucial healthcare workflows, from better referral management, prior authorizations and insurance eligibility to revenue cycle management and ambient scribes. The industry is in agreement that AI is essential for efficiency gains.
However, a fundamental challenge remains: we must recognize the vast amounts of unstructured data.
Unstructured data, like forms (some handwritten), physician notes, scanned documents, clinical summaries, images and faxes, still makes up an estimated 80% of the healthcare data being shared today. While many new solutions are excellent at manipulating structured data (neatly organized spreadsheets and database fields), true, scalable transformation requires the ability to ingest and process the vast ocean of unstructured information.
The translation of unstructured documents into structured data can’t just be an afterthought—especially in healthcare where accuracy, privacy, and efficiency are paramount. The translation of unstructured documents into structured data can’t just be an afterthought—especially in healthcare where accuracy, privacy, and efficiency are paramount. Data transformation is our core focus. Our Clarity technology, for example, uses intelligent data extraction to process unstructured documents, then maps the data to various fields within an EHR or other system of record through our Conductor integration engine. It is a fully automated solution.
Plus, because our AI model is trained specifically on healthcare documents, it uses robust contextual understanding to extract data more intelligently than a generalist AI model like ChatGPT can, delivering insights that are far more accurate and actionable than basic data translation.
3. The future is uncertain.
While the AI noise was as loud as ever at HLTH this year (perhaps to the point of ad nauseam), the overall vibe of the conference was much quieter and lower energy than usual, due in part to the government shutdown and the headwinds of the Medicaid cutbacks leading to uncompensated care. No one really talked about how technology can help after the One Big Beautiful Bill Act (OBBBA) was signed. I suspect we will hear more during the ViVE and HIMSS conferences next year, where policy conversations and solutions are more present than at HLTH.
We are all united in the goal of leveraging technology to enhance patient care and streamline complex operations. To fully realize this potential, the industry must embrace two key accelerants:
- Technology vendors must provide more clarity around the capabilities of their tools to improve specific healthcare workflows
- Many of these solutions need funding to materialize, which enhances the need for an ROI.
By the time the next healthcare conference kicks off, we hope to see more of the energy we’ve seen in past years, with more concrete answers about how the industry will solve real problems—from inefficiencies in daily workflows to policy and deadlines for regulations.
As exciting as the innovations at HLTH seemed, it’s clear that we still have a lot of work to do to solve healthcare’s biggest problems.
