Large Healthcare Organizations Build Their Own AI Tools Instead of Buying
Major healthcare organizations are increasingly developing AI tools internally rather than purchasing solutions from health tech startups, according to discussion at the Digital Healthcare Innovation Summit in Boston in April.
The shift reflects a broader calculation among large health systems: building custom AI may offer more control and lower long-term costs than relying on external vendors that could change pricing, get acquired, or shut down.
Why healthcare systems are building in-house
Healthcare organizations have the technical talent and infrastructure to develop AI tools tailored to their specific workflows and patient populations. Off-the-shelf solutions often require expensive customization anyway.
Building internally also reduces dependency on startups. A health system that develops its own tools controls the roadmap and avoids vendor lock-in.
The tradeoffs
In-house development requires sustained investment in engineering teams and data infrastructure. It's slower than buying an existing product, and mistakes cost more.
Smaller health systems lack the resources for this approach and will likely continue buying from vendors. The build-versus-buy decision depends on organizational size and technical capacity.
Learn more about AI for Healthcare and Generative AI and LLM technologies that health systems use to develop custom solutions.
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