By Eric Demers, CEO, Madaket Health

In 2025, healthcare, and the world, will see AI slip further into Gartner's "Trough of Disillusionment." When progress can't keep pace with hype, expectations turn into frustrations. Advancements are being made. However, they aren't the head-turning, flip-a-switch, and watch-the-results-pour-in examples many envisioned and extolled. And in healthcare, which is typically wary about adopting new technology, developments will come even slower.

Slow but steady success

Businesses worldwide are in a mad dash to claim they have AI under the hood. The truth is, few do, and in healthcare, the number is even smaller - but no one wants to seem like a laggard. Greater use cases will emerge in mainstream business, putting earlier adopters in a good position to capitalize by year's end. Healthcare, however, will see just a trickle of successful implementations, but they will steadily increase over time.

Further, because healthcare in the U.S. is so complex, it will take AI tools a while to accumulate the necessary data and come up to speed. In 2025, healthcare will see improved access to data to feed the "AI machine" properly, which will then open the technology up to meaningful applications that produce impactful results.

Too rich for our blood

AI research and implementation is very expensive and time-consuming. Institutions with vast resources - technical, operational, and financial - will be the only ones in healthcare able to afford a seat at that table. But these large medical centers and health systems will investigate true, AI-powered solutions, and get results. Mayo Clinic, for instance, is turning AI on its historical lab results for minable data that could impact the future of healthcare.

While the examples may be fewer than in other industries, healthcare will see some strong applications that illustrate how AI can help produce better health and financial outcomes.

The data do-over

Significant improvements in data quality are needed for training AI algorithms. There currently exists siloed data, gaps in data, outdated and dirty data - bad data is everywhere. Across industries, even in healthcare, this topic is gaining momentum. Analyst firms are mobilizing and establishing research swimlanes on the issue. With healthcare realizing how bad data impacts both quality of care and revenue, we'll see a growing data do-over to nail down this disruptive issue, once and for all.

Time to align

There are significant challenges with data alignment between payers (insurers) and healthcare providers. Much of the process is still done manually and in disparate ways, ranging from fragmented versions of data intake forms shared via email to faxes and even phoned-in records. Its estimated provider directories are about 50% accurate, which makes it difficult for patient care to go through the system as intended.

Payers and providers must be in sync so patients get the care they need. This means using tech to ensure they're at the right place at the right time, and that costs are as expected. Payers are trying an "innovative approach" that streamlines spreadsheets. This is antiquated. There already exists advanced data management and exchange tools for automation and ongoing, real-time provider data updates. AI is already being used here, too.

The time to align is long overdue and it's here that we'll see healthcare make real progress in 2025.

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ABOUT THE AUTHOR

Eric Demers is the CEO of Madaket Health. He believes we can transform healthcare delivery through the power of data and interoperability. With more than 25 years of global healthcare experience, Eric has built and scaled leading technology and service companies, from early stage to Fortune 100. He is highly sought-after for speaking and consulting on international health, having advised global entities and governments on critical issues facing healthcare. A growth-minded leader, Eric has founded three companies and exited two. Eric previously served in strategy-focused executive roles at IBM, Accreon, MEDecision and Orion Health. He is a graduate of Brandeis University and The George Washington University School of Medicine and Health Sciences.