In my last post, I reflected on how far healthcare has come, from my dad’s era when everything was paper-based and reactive, to today’s world of wearables, digital records, virtual visits, and advanced medical science. It’s been an incredible journey. But as I said then, we’re not done. We’re just entering one of the most exciting chapters yet, with AI taking center stage.

AI is quickly becoming one of the most powerful tools we have to improve care, ease the load on clinicians, and make the whole experience better for patients. Of course this moment didn’t just happen. It’s built on earlier milestones, like digitizing health records and making data interoperable. Those changes gave us access to information at scale. Now, AI is helping us make sense of all this information and put it to work in smarter, more personalized ways. That said, we’re still in the early innings with AI. Just like with the internet, mobile phones, and other earlier technologies, we’re seeing AI move through phases of development and adoption.

A book I recently read, Agentic Artificial Intelligence, offered a helpful way to think about AI’s evolution. It breaks things down into five levels, from basic rule-based automation (Level 1) all the way to fully autonomous systems (Level 5). In between, you see AI gaining cognitive abilities, learning to reason with human input, and eventually functioning autonomously within defined conditions.

This framework helped me reset some of my expectations, but it also got me more excited about where things are headed, especially in areas where there’s a lot of high-quality data, decisions need to happen fast, and there’s a big reputational or clinical impact.

To make this real, I think about how I personally manage aspects of my health using my Garmin watch. It tracks everything from heart rate and movement to oxygen saturation and sleep patterns. Beyond its tracking capabilities, it also interprets the data and provides personalized insights. It can tell me how stressed I am, how well I slept, how ready I am to exercise, and even estimate my “health age.” In mapping Garmin’s capabilities to the AI framework, it has moved beyond Level 1 (automating) and is analyzing and offering relevant guidance (Level 2). I share this as a simple example and glimpse of how AI is becoming helpful in daily life.

In clinical settings, one of the biggest challenges is the administrative burden on clinicians with considerable documentation, fragmented records, and systems that don’t talk to each other. AI is starting to make a difference here too.

Take the company, Navina, for example. Its platform pulls together data from multiple sources and gives clinicians intelligent, timely recommendations right inside their existing workflows. That’s huge. It means better and faster decisions, and the ability to improve outcomes and quality scores by tapping into both clinical and non-clinical data. If we apply the AI levels to what Navina is doing, it starts at Level 1 by automating the retrieval of structured data, like lab results and medication lists. It then moves into Level 2 territory by analyzing unstructured data (physician notes, patient histories, clinical trends) and transforming this info into clear, actionable summaries. At Level 3, Navina begins to demonstrate reasoning capabilities, surfacing the most relevant clinical insights to help clinicians focus their time and make faster, more informed decisions, all while keeping human oversight in place, which remains essential in any healthcare setting. At Level 4, the platform takes another leap forward by auto-generating complete, compliant documentation, reducing administrative burden even further.

What makes Navina stand out is how well it fits into how clinicians already work. They don’t have to change their process. Instead, they get an AI assistant that flags suspected patient conditions, cuts the busywork, improves documentation, and frees up more time to care for patients. With nearly 98% adoption among users, the impact speaks for itself.

On the patient side, AI is already more present than many people realize. If you’ve asked a chatbot a health question or gotten a message in MyChart that explains your lab results in plain language, that’s AI at work. Those are examples of Level 2 (and even some Level 3) capabilities, helping people understand their health in ways that feel less intimidating and more empowering (something we could all use).

One of AI’s greatest strengths is its ability to pick up on things we might otherwise miss. Like spotting a subtle change in a scan, picking up a pattern in lab results, or tracking health data over time, AI can help catch issues earlier and lead to quicker, more accurate diagnoses.

It’s also changing how we approach research. By combing through massive data sets, AI can help identify which treatments are working, match the right patients to the right therapies, and predict how someone might respond to a specific drug. That’s a big step toward personalized medicine that is actually personalized.

I recently got a glimpse of what Level 4 might look like in the real world. It was a prototype hospital room where a robot delivered medical supplies autonomously to a nurse. It’s a controlled use case, but it’s a signal of what’s to come. Exciting stuff.

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Ultimately, the real promise of AI isn’t just in the technology but in what it enables for people. It gives clinicians more time with patients. It gives patients clearer answers and greater confidence. It helps care teams work more collaboratively. And it moves the system closer to what we all want, which is care that’s simpler, more affordable, and centered around the individual.

Of course, we need to move forward thoughtfully and responsibly. But if we get this right, AI could turn decades of health data into something much more powerful … wisdom that actually improves lives. We’ve come a long way from the days of paper charts. Digitizing records was a huge leap. Now, with AI, we’re moving from collecting data to understanding and using it.

As someone who’s spent years in this field, I’ve never been more hopeful. The technology is real. The momentum is real. And most importantly the benefits are starting to reach the people who need them.

Thanks for reading. I’ll keep sharing stories and perspectives as we navigate this exciting new chapter in healthcare innovation.