Zocdoc Innovation, Technology & Agility

What is the unique story that you feel your company has with AI? If you were writing about it, what would the title of your blog be?
I’d title our blog “Human Outcomes, Machine Support.”
At the forefront of the AI revolution is how it’ll impact us as humans — how will AI affect jobs, redefine productivity or alter our sense of self? Zocdoc, a company built around patient experience, sits at a unique intersection of AI and human care.

Our journey with AI is just beginning, but already it’s reshaped our business. Our first major endeavor with AI expanded our healthcare scheduling expertise to America’s highest-volume scheduling channel: the phone. We launched Zo, an AI phone assistant that instantly schedules appointments 24/7 using natural, conversational language. This initiative, championed by Chief AI Officer and co-founder Nick Ganju, aims to remove friction from the phone, help patients seamlessly schedule care and soon order prescription refills, get referrals and handle other needs.

Looking beyond one feature, we’re building AI fluency across the company. From recurring AI knowledge shares to active Slack channels, we’re cultivating a culture that’s curious and responsible. Yet, we’ve never lost sight of the patient. The drive to give power to the patient is what makes Zocdoc a unique and inspiring place to shape the future of healthcare.

What are you most excited about in the field of AI right now?
The open source space excites me the most right now. Having this technology in both the hands of big tech companies as well as tinkerers expands the breadth and depth of what can be accomplished. Yesterday, my fellow engineers and I were the builders; today every person reading this is a builder. When the number of people able to build and design increases exponentially, the rate of progress becomes breathtaking.
This AI technology doesn’t just make development accessible, it changes the foundation of how we interact with machines. For decades, we had to think like computers to build with them. Now, machines are learning to think more like us. Language has become the interface. That shift opens the door to collaboration between technical and non-technical minds in a way we’ve never seen — doctors designing patient flows, researchers automating insights, creatives prototyping ideas in real time. The barrier to creation isn’t just lower; it’s dissolving. While companies like OpenAI and Anthropic are leading the way, it enables non-technical people across practices to stand on those shoulders and imagine what’s next.

How do you learn from one another and collaborate?
The surprising thing is: learning AI itself isn’t the hardest part. With so many resources available — blogs, videos and courses — and with the tech rooted in natural language, the basics are more accessible than ever. The real challenge was diving into unfamiliar domains needed to make AI useful in the real world.

For instance, building an AI phone assistant requires a great deal of engineering, architecting and designing. For a team of highly skilled engineers, it’s not an insurmountable task with our existing skill set. However, learning about voice UX was an unforeseen complication that I didn’t realize would be a hurdle. Design a framework that will be robust and low latency? Not a problem. Figuring out how to phrase a certain question so that the fewest number of people are confused by it? My team and I had to start from square one.

That’s why continuous learning is part of our daily workflow. We spend time not just building, but sharing learnings, mistakes and insights. This cross-disciplinary learning is becoming the new normal in AI work. Success isn’t just about understanding models, but understanding the real-world systems and human contexts it interacts with.