Why Healthcare Is Ahead of the Curve in AI Adoption

Last weekend, I stood at the finish line of the MDI Marathon in Bar Harbor and watched my sons complete a race they had trained for over many months. The preparation was grueling, the race itself was a struggle, and the finish brought both exhaustion and joy.

Two things struck me in that moment. First, these apples did not just fall far from the tree, they rolled down the hill, jumped the fence, and started growing in an entirely different orchard. Second, I realized that a marathon is the perfect metaphor for healthcare’s adoption of AI. Training takes discipline, persistence, and more than a few blisters. The race itself demands stamina and adaptability. And crossing the finish line delivers the ultimate mix of exhaustion, relief, and proof that something hard, maybe even a little crazy, is absolutely possible.

Why Healthcare Is Ahead of the Curve

Healthcare is often labeled a “slow adopter” of technology. EHR rollouts took decades, interoperability has been a perennial struggle, and even simple digital tools have historically lagged. Yet in AI, something different is happening.

• A recent AMA survey found that two-thirds of physicians now report using AI-enabled tools, a jump of 78% since 2023.
• Menlo Ventures & Bain’s 2025 Healthcare AI Index shows 22% of healthcare organizations have deployed domain-specific AI. An amazing 7× increase in just one year.
• Forbes reported that 27% of health systems are leading with AI adoption, compared with only 9% of companies in other industries.
• In revenue cycle management, a Waystar study found providers using AI saw double-digit gains in cash acceleration and denial reduction.
  

Healthcare can’t afford to sit out the race. And what’s remarkable is that our industry, long criticized for being slow to adopt, is now out in front. That’s not an accident. It’s the result of endurance, grit, and a recognition that the stakes are simply too high to lag behind.

Five Ways AI Is Creating Advantage

1. Mapping the Patient Journey AI connects fragmented data across the continuum — from the accident scene to emergency transport, from hospital care to recovery, and finally to billing and settlement. Seeing this journey as one story reduces delays, prevents denials, improves cash flow, and ultimately creates a smoother experience for patients and providers alike.

2. Driving Specialization and Consolidation Not all claims behave the same. Motor vehicle accidents and workers’ comp claims are complex, document-heavy, and often contested. AI helps identify and route these cases at scale, enabling specialized management. Over time, this specialization leads to consolidation: fewer organizations handle them, but with sharper expertise and stronger results.

3. Boosting Clinician Productivity Ambient documentation, predictive coding support, and decision-assist tools free up clinicians to spend more time with patients and less time buried in the EHR. AI helps reduce burnout while allowing medical staff to operate at the top of their license.

4. Reducing Administrative Costs Revenue cycle, scheduling, utilization review, denial management, and prior authorization are loaded with manual work. AI-driven automation cuts out friction, lowers administrative overhead, and accelerates processes that historically consumed countless hours and dollars.

5. Improving Patient Outcomes Beyond finance and operations, AI enables predictive analytics, early detection of risk, personalized care plans, and faster intervention. By integrating insights across the continuum, providers can deliver more proactive, outcome-focused care.

Looking Forward

Like a marathon, adopting AI in healthcare is demanding and sometimes exhausting, but worth the effort. The discipline to train, the commitment to run, and the satisfaction of finishing strong are all part of the journey.

And in this case, the finish line means proving that healthcare can move faster, adopt smarter, and lead with resilience. I’m proud of our industry for embracing this challenge, for showing the endurance to push through and the grit to prove that even a historically slow adopter can surge ahead when it matters most. We know we can do hard things.

At GoSB, we’re bringing this AI-enabled approach directly to one of the most challenging areas in healthcare finance: accident-related claims. To learn more about how specialization and automation can turn complexity into opportunity, follow our page at go-sb.com and request more information here.

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