We’ve all been at the same conferences. We’ve all heard the same pitch: This AI will transform! This AI will revolutionize! This AI will change everything!
Maybe some of it will, but as I walk tradeshow floor after tradeshow floor, I can’t help but notice something else quieter, but far more telling.
Everyone’s talking about AI. Almost no one is talking about what it takes to actually make it work.
Not in pilots, not in press releases, but in real, clinical, system-wide production.
That’s why I, along with 16 other experts across healthcare, academia and technology, wrote BRIDGE.
The Blueprint for Resilient Integration and Deployment of Guided Excellence isn’t a strategy deck. It’s a boots-on-the-ground framework born from the frustrating reality that clinical AI is still largely stuck in proof-of-concept purgatory.
Why? Because we don’t lack ambition, but we often lack a plan. BRIDGE aims to fix that.
The Real Cost of Real AI
If you’re sitting in the C-suite wondering why AI hasn’t transformed your operations yet, let me be direct: it’s not your team’s fault, but it might be your framing.
Deploying a production-ready clinical AI solution isn’t a feature drop. It’s a capital investment. A single solution can cost north of $200K to implement. A full-scale deployment? That’s seven figures – conservatively. And that’s before you account for regulatory compliance.
It sounds daunting, but it’s also predictable if you know where to look. BRIDGE lays out those costs, timelines, and resource needs in plain language. No fluff. No jargon. Just the facts you need to plan responsibly and lead effectively.
Models Don’t Save Lives. Solutions Do.
One of the most common, and costly, misconceptions in healthcare AI is the belief that a model is a solution.
It’s not.
A model generates data. A solution generates outcomes.
Algorithms alone don’t scale, because they don’t integrate, navigate workflow complexity or clinical nuance. Without thoughtful design, native integration and a clear focus on the end user, they remain code sitting idle.
BRIDGE draws a clear distinction: a solution happens when model output is delivered, understood and acted on within the clinical workflow. That’s where outcomes change.
We call it Radically Integrated Transformation, a principle that demands aggressive integration into EHRs, PACS and mobile platforms, while respecting the way clinicians actually work. Anything less creates friction. And friction kills adoption.
Trust Isn’t a Buzzword. It’s Built Case by Case.
Trust in clinical AI is built – or lost – one interaction at a time. It’s not judged in aggregate; it’s judged in the moment, by the end user, with every case.
That’s where the Goldilocks Principle comes in.
If an AI tool fires too infrequently, clinicians may forget how, or why, to use it. If it fires too often, even accurately, it risks becoming noise. Either scenario erodes confidence.
Perceived value is tightly linked to how often a solution appears, how well it performs when it does, and how intuitively it fits into the clinical environment. A low-prevalence use case with a single visible error may feel like a 33% failure rate. That’s not a math issue; it’s a perception issue – and perception drives trust.
BRIDGE urges healthcare leaders to evaluate not just clinical need, but also disease prevalence, user context and workflow orchestration. The best implementations strike a balance: common enough to stay relevant, rare enough to preserve impact and always embedded in environments that reinforce confidence.
Trust isn’t built by being flawless. It’s built by being just right – visible, useful and dependable when it matters most.
Validation Never Ends
AI isn’t static. It evolves, or it degrades. That’s the nature of drift. Pretending otherwise is a liability.
In healthcare, where the stakes are life and death, performance must be continuously validated, not just benchmarked. BRIDGE champions iterative validation modeled after Quality Improvement principles. Because if your model’s performance slips and no one notices, you’re not innovating – you’re gambling.
Regulation Is Coming for Us All
The FDA. HIPAA. HTI-1. ISO. EU AI Act.
If your AI plan doesn’t include a legal and compliance roadmap, it’s incomplete.
BRIDGE doesn’t just list regulatory hurdles, it provides practical guidance for navigating them, including how to use model cards and documentation practices to reduce liability. It encourages early alignment between innovation, clinical and legal teams, because you don’t want to start that conversation after a potential problem arises.
Culture Change Is the Hard Part. But It’s the Most Important One.
Changing technology is hard. Changing people is harder. Yet, you can’t do one without the other.
Deploying AI at scale doesn’t just mean upgrading infrastructure. It means reshaping how clinicians work, how teams communicate and how your institution thinks about care delivery. That kind of transformation doesn’t come from a product launch. It comes from culture.
Too often, culture is dismissed as the “soft stuff.” In reality, it’s infrastructure. It’s what makes everything else stick.
AI will require new workflows, new training and new expectations. If your people aren’t part of that evolution, if they don’t trust the tools or the process, you’ll stall before you start.
That’s why BRIDGE is more than a technical framework. It maps what true cultural transformation looks like – from communication and training to clinical engagement and governance.
Because, in the end, the only thing harder than building something new is getting people to use it. Culture is what makes adoption possible.
What Comes Next
I don’t know if AI is our next HITECH moment, but I do know it won’t be if we keep mistaking models for strategy and pilots for success. We need the infrastructure – technical, operational, regulatory, and cultural – to make clinical AI real.
That’s what BRIDGE offers.
This blog only scratches the surface. The full framework goes deeper: into use case design, validation protocols, trust calibration, integration architecture, reimbursement modeling, regulatory navigation, governance structures and much more.
The future of care delivery is coming into focus. The question is: will we be ready when it arrives? Downloading the BRIDGE Framework is a great place to start.
