When we talk about bias in healthcare AI, the conversation almost always starts — and ends — with data. We scrutinize training sets, audit algorithms, and develop fairness metrics. But there’s a different kind of bias that flies under the radar: deployment bias. And it’s just as dangerous.
Even the most well-trained, carefully calibrated AI model can reinforce inequity depending on where and how it’s deployed. To be clear, the AI in question here refers to systems that analyze clinical data, like patient images, recordings, and medical histories, not administrative tools like transcription or scheduling assistants. Too often, advanced tools are first introduced in urban, well-resourced health systems — facilities with strong digital infrastructure, ample staff, and tight institutional feedback loops. Meanwhile, rural hospitals, community clinics, and safety-net providers are left waiting. Sometimes years.
But here’s the deeper issue: deployment bias doesn’t just affect who benefits from AI — it also affects how future AI gets trained. If AI tools are mainly rolled out in wealthy urban centers, the data they generate will reflect those populations, workflows, and outcomes. That data then feeds the next generation of models, creating a feedback loop that further marginalizes underrepresented communities. In other words, where we deploy AI today determines who gets represented in tomorrow’s algorithms.
This isn’t just a rollout timeline issue. It’s a reflection of a deeper gap in how we think about innovation. The very communities that could benefit most from clinical decision support, diagnostic augmentation, or remote monitoring tools are the last to get them. Not because the technology isn’t ready, but because we assume the infrastructure isn’t. That assumption is its own form of bias. A June 2025 scoping review of U.S. rural health research found only 26 peer-reviewed studies on AI tools in rural settings —14 focused on predictive models and 12 on infrastructure. Not a single study examined generative AI in real-world rural deployment, and half highlighted insufficient data and analytic capacity as a major barrier to development and validation. A July 2025 article on ‘A Growing Divide in AI‑Enabled Care’ noted that AI remains ‘concentrated in metropolitan academic centers, leaving rural communities behind.’ It pointed out that rural hospitals face infrastructure limitations, and few AI projects move beyond design to real-world use in these areas.
I’ve spent much of my career focused on increasing access to care, particularly in places where healthcare is hours away, not just down the block. That work has shown me how transformative technology can be, but only if it reaches the people who need it most. We can’t claim AI is democratizing care while limiting its reach to ZIP codes that already have the best access.
Bias in deployment isn’t malicious. But if we don’t name this bias and account for it, we risk reinforcing a two-tiered system where AI sharpens outcomes for some and does nothing for others.
Equity has to be built into the deployment strategy from day one, not treated as a future retrofit. That means prioritizing inclusion not only in the data but in the delivery, and recognizing that inclusive deployment is the foundation for inclusive datasets. Because ultimately, where we choose to deploy AI sends a message about whose health we value, and whose data we consider worth learning from. And for those of us building healthcare’s future, that choice should never be an afterthought.
Photo: Klaus Vedfelt, Getty Images
Dedi Gilad is CEO and co-founder of TytoCare, transforming the primary care industry by bringing doctor’s visits into the home with remote physical exams that provide affordable, always-on, and accessible primary care for all. TytoCare works with healthcare insurers and providers to provide better access to primary care virtually, with a handheld exam kit that connects users with a clinician for a medical exam and telehealth visit no matter where they are.
In the decade since co-founding the company, Mr. Gilad has led the launch and establishment of TytoCare as a major player in the telehealth market. Under his leadership, the company has built partnerships with nearly 250 major healthcare players across the world. Mr. Gilad and TytoCare have been recognized as a leader in the telehealth market, with awards from ATA, Fast Company, MEDICA, Forbes, and more, and have established a track record of improving access to healthcare and better telehealth adoption and results than other solutions on the market.
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