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# AI Agents On Premise vs In The Cloud, Part 3
- URL: https://marginsofcare.com/ai-agents-on-premise-vs-in-the-cloud-part-3/
- Published: 2026-09-24T17:59:20.000Z
- Updated: 2026-09-25T06:36:57.000Z
- Author: Eva Worst

This is a continuation of [Part 1](https://marginsofcare.com/ai-agents-on-premise-vs-in-the-cloud-part-1/) and [Part 2](https://marginsofcare.com/ai-agents-on-premise-vs-in-the-cloud-part-2/).

All that being said, there is a really good reason why hospitals and other care institutions should be thinkering with AI in-house, even if they shouldn’t necessarily be using it in production, and that has everything to do with understanding the clinical needs.

IT departments and clinical departments often work in silos: there is little alignment, little collaboration and little coordination between the two. It’s a well known problem that plagues many companies, not just the hospitals, and the tech way to solve is to build interdisciplinary teams spanning across departments. While this is not a setup that easily fits in the way hospitals operate, there is a work around: let the IT do “innovation”.

What this means is you set up a team of developers and point them to a clinical problem that needs fixing. It’s then their job to understand the requirements - technical and clinical - and come up with a solution. They then get to test their solution and underlying assumptions about the problem in a real-life setting, which unfailingly reveal new insights and lead to adjustments in the approach. This is a highly beneficial and fun way to build internal know-how, which can then be used to make better decisions on whether or not a certain software or AI application actually does the job.

Many of the most successful tech companies are doing internal innovation all the time - think [Google](https://cloud.google.com/executive-insights/everyone-wants-a-culture-of-innovation-report-what-does-it-look-like-report), [Microsoft](https://blogs.microsoft.com/blog/2026/09/17/what-weve-learned-from-microsofts-own-ai-transformation/) or [Apple](https://www.apple.com/careers/pdf/HBR%5FHow%5FApple%5FIs%5FOrganized%5FFor%5FInnovation-4.pdf) \- investing considerable amount of people and resources into projects only to scrap them in 6-12 months later, making it all look like a waste on the balance sheet (and by all means things can easily go too far), but there is a steep learning curve that comes from those “doomed from the start” projects, as well as the crucial customer/user understanding required for making the right calls. This is important in any sector, but especially so in healthcare, given the long-term system commitments and the high-risk work that is done.

And this is exactly what Charite [is getting right](https://www.charite.de/service/pressemitteilung/artikel/detail/charite%5Fstartet%5Fzentrale%5Fki%5Fplattform%5Ffuer%5Fklinik%5Fforschung%5Flehre%5Fund%5Fverwaltung/): they run various pilots with companies as well as with their internal innovation projects, sometimes doing the same thing with a different tool in a different department, gaining deeper understanding about requirements and failure modes. It’s practical experimentation at its best and it will lead to better decisions and better outcomes for both the hospital and the patients.

It’s tempting to dismiss this as innovation theatre, a waste of money or a lack of internal coordination (and it can also be that!) but if done right, it can be an incredible and durable advantage. Time always shows.