What Had Us Talking in 2025: The 9 Most Interesting Articles We Read

We share a lot of articles in Slack. Most earn a quick “👍” or “👀” and fade into the scroll. A few, though, spark real conversation. Looking back at what Radineers discussed in 2025, a clear pattern emerges. 

These pieces may come from different publications and perspectives, but together they tell the same story about where healthcare — and radiology in particular — is headed. Here’s what stood out.

Burnout Is Not a Side Effect, It’s the Problem

In a Becker’s Hospital Review roundup of what healthcare technology needs to improve fastest, one comment cut through the rest. Andrew Kim, MD, Baylor Scott & White’s Director of Physician Informatics, called out physician burnout as a direct drag on outcomes, productivity and the workforce itself.

What made that notable wasn’t that burnout came up — it was how often it came up. Multiple leaders in the same article pointed to it as the primary constraint on care delivery. At this point, burnout isn’t a downstream issue, it’s the system failing in real time. That reality is changing how technology gets evaluated. If a tool doesn’t clearly remove friction from a clinician’s day, it’s not getting the greenlight. 

AI Strategy Is Growing Up

The VA’s published approach to AI adoption reads less like a vision statement and more like an operating plan — heavy on governance, validation and scalability, but light on experimentation for its own sake. The same shift showed up in NVIDIA’s 2025 State of AI in Healthcare survey. 

Most organizations aren’t debating whether to use AI anymore, they already are. The real questions now are whether it works reliably, delivers measurable impact and fits into real clinical workflows without creating new problems. This is what a maturing AI strategy looks like: fewer pilots, less hype and much higher expectations.

Why Ambient AI Keeps Coming Up (and Why That Matters)

When Becker’s Hospital Review asked healthcare leaders where they’d place a single bet this year, ambient AI and listening technologies came up again and again — cited by 16 different institutions. That’s not a coincidence.

Ambient AI is getting prioritized because it solves a very specific, very expensive problem: documentation burden. It doesn’t ask clinicians to practice medicine differently or learn a new workflow, rather it fits into the one they already have. In an environment defined by staffing shortages and burnout, high adoption, clear ROI and immediate relief is a rare combination. That’s why ambient AI keeps rising to the top of these conversations.

Accuracy in the Spotlight

A PBS NewsHour segment on hallucinations in AI-generated medical transcripts didn’t reveal anything shocking from a technical standpoint but that wasn’t the point. What mattered is that this problem has crossed into the public spotlight. When national investigative journalism starts scrutinizing AI errors in clinical documentation, the era of black box AI ends. 

Healthcare is entering a phase where visibility equals accountability. If AI-generated content becomes part of the medical record, then accuracy, auditability and traceability aren’t optional features — they’re foundational to governance. Building systems that can be questioned and verified are the cost of entry.

AI Isn’t Replacing Experts — It’s Exposing Bad Narratives

Two New York Times articles landed with our team for similar reasons: one on developers using AI to write code, another on radiologists at Mayo Clinic working alongside AI. Both quietly dismantle the same tired argument. The most effective use of AI isn’t replacement — it’s enhancement.

Developers who use AI aren’t worse at their jobs; they’re faster and more productive. Radiologists using AI aren’t less essential; they’re better supported and less burned out. AI handles the mechanical work so humans can focus on judgment and nuance.

Financial Pressure Is Forcing the Issue

UnitedHealthcare’s move to cut radiology reimbursement rates was controversial, but it wasn’t surprising. Payers are under real margin pressure, and radiology has been absorbing cuts for years when adjusted for inflation. When the largest commercial insurer moves to “align” rates downward in the name of affordability, others tend to follow. 

That reality makes efficiency and defensible value non-negotiable. Technology alone won’t fix reimbursement pressure, but ignoring workflow, productivity and cost structure is no longer viable. The margin for inefficiency is disappearing, and radiology is feeling it first.

Radiology Is Still the Testing Ground for Clinical AI

Nearly 1,000 FDA-cleared AI-enabled radiology products now account for roughly three-quarters of all medical AI authorizations. Radiology’s dominance in FDA AI approvals isn’t a victory lap — it’s a stress test. The next phase isn’t about proving AI can work in radiology; it’s about proving it’s worth using every day. 

A Note on Momentum

It’s been meaningful to see Rad AI recognized externally — from our Series C extension with leading health systems, to making TIME’s list of top healthtech companies, to partnering with RSNA Ventures to bring peer-reviewed knowledge directly into radiology workflows.

What matters most, though, is alignment. The themes showing up across the industry — reducing burnout, prioritizing workflow and designing AI as a partner — are the same principles guiding our work.

What This Means Heading into 2026

If 2025 made anything clear, it’s that healthcare is done being impressed. 

The next year will reward AI that actually reduces burden, survives scrutiny and fits real workflows. Everything else will quietly disappear. Radiology will keep leading this shift, because the profession has zero patience for wasted time.

The articles that sparked conversation among Radineers weren’t always optimistic, but they were honest. And right now, honesty – not hype – is the most reliable signal we have of where this industry is headed.

Interested in a monthly summary of what has us talking? Sign up for our newsletter.