AI in Healthcare: Reflections from Becker’s in Chicago
- Andy Van Pelt
- Oct 7
- 3 min read
Last week’s Becker’s HIT & Digital Health Conference in Chicago was one of those rare gatherings where the hallway conversations mattered just as much as the keynotes. It was less about showing off the latest technology and more about asking harder questions — how do we use AI in ways that actually make healthcare better, safer, and more human?
I came to Chicago expecting to hear a lot about innovation — and I did. But what stood out this year was the tone. The industry is shifting from hype to honesty. The conversations around AI felt more grounded, more thoughtful. We’ve moved past the novelty of what’s possible and into the harder, more important conversation: how to make it work in the real world.
Across sessions and side discussions, there was a clear pattern — leaders are cautiously optimistic. They see the potential for AI to reduce administrative burden, predict risk, improve access, and help clinicians spend more time on patient care. But they also know the foundation has to be right. Without clean, connected data and clear accountability, AI becomes just another shiny object.
The best examples I heard weren’t about futuristic breakthroughs — they were about fixing what’s broken today. Using automation to save staff time. Improving visibility across facilities. Helping clinicians find what they need faster. It’s practical, not flashy. And that’s progress.
What’s also changing is how people think about implementation. The organizations making real strides aren’t waiting for perfect clarity from regulators or a fully mapped return on investment. They’re running small pilots, testing assumptions, measuring results, and scaling what works.
This isn’t about taking reckless risks — it’s about being willing to experiment and learn. In an industry that’s often cautious by necessity, that willingness to try has become a competitive advantage. It’s a reminder that leadership isn’t about having all the answers. It’s about being curious enough to find better ones.
One thread that kept surfacing all week was the importance of trust. Trust in data. Trust between partners. Trust between people and the systems that support them. For AI to be credible in healthcare, it has to feel reliable — not abstract, not opaque. That means more transparency about how models work, where data flows, and how decisions are made.
And maybe most importantly, it means keeping people — clinicians, patients, and the workforce — at the center. Technology can make healthcare faster, but only people can make it better.
By the end of the week, what I heard over and over was less about what AI could do and more about what it should do. How we apply it will shape the next decade of healthcare — not just in terms of efficiency, but equity, access, and trust.
Becker’s continues to do something few events manage: it brings together the full ecosystem — hospitals, vendors, policymakers, and innovators — in one room, to talk about how to move forward together. That collaboration feels more important now than ever.
I left Chicago encouraged. Not because AI will magically fix the system, but because leaders are starting to approach it with humility, urgency, and shared purpose. We’re finally asking the right questions — and that’s where real change begins.
If you attended Becker’s, or you’re leading AI work in your organization, I’d love to hear what you took away from this year’s discussions. Where are you seeing traction — and what’s still holding us back?
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