AI in 2025: Hype, Reality & Hope in Healthcare

Madaket Health’s Eric Demers offers insights on AI in 2025: hype, reality, and hope in the healthcare sector. This article originally appeared on Solutions Review’s Insight Jam, an enterprise IT community enabling the human conversation on AI.

AI seems to be on everyone’s lips these days, and that’s a problem. When progress doesn’t match expectations, no matter how inflated they may be, enthusiasm begins to deflate. In 2025, we’ll see that play out further as AI slides deeper into Gartner’s “Trough of Disillusionment,” creating frustration across industries, particularly healthcare.

A Steep Financial Entry

Exploring and deploying AI consumes remarkable amounts of time and money, so it’s usually those with deep pockets who can afford this game, especially in healthcare. Still, we’ll see larger medical institutions push ahead with AI development. Right now, the Mayo Clinic is applying AI to historical labs to produce data that is minable and impactful. Though fewer in number, healthcare will produce a number of AI applications expected to boost patient health and provider finances.

Dealing with Disruptive Data

Training AL algorithms effectively requires a major overhaul in data quality across industries. There’s data stuck in silos, old data, corrupt data – and it’s very pervasive. This causes disruption and strangles AI initiatives. It’s become such a critical area that analysts are building teams to follow it.

That said, this is the year healthcare does a data overhaul, realizing disruptive data undermines care quality and finances. Due to healthcare system complexity in the U.S., it’s going to take time for AI to gather the data it needs to be effective. Still, expect better data availability for AI to consume in the year ahead. This will produce impressive success stories in mainstream business. Healthcare, though, will see far fewer wide-scale AI implementations, starting as a drip and turning into a decent flow by year’s end.

Greater Alignment

Healthcare providers and insurers (payers) have had a longstanding data alignment problem. Processes are often done manually and in varied ways. Not surprisingly, it’s widely believed that 50% of provider directories are inaccurate, impeding care as patients move through health systems.

Payers are claiming a new, dynamic approach, which is merely streamlined spreadsheets. The thing is, there are data management and exchange tools that enable automation and provide data updates already – and AI is being harnessed in these solutions, too. Greater alignment has been a long time coming. The good news is that this is an area in which healthcare will see tremendous improvement coming its way.