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Upstarts · 2 min · Jul 23, 2026
IBM Watson lost trust by promising more than it could deliver
Shiv Rao
Shiv Rao says Watson understood healthcare's opportunity but got ahead of what its products could do.
In this episode
Full analysis- 31:32Abridge challenged Microsoft with a conversation-first vision4 min
- 27:00Clinical notes connect care delivery to healthcare payment3 min
- 43:21A difficult IVF journey shaped Abridge’s mission3 min
- 12:04Abridge used UPMC funding and data to build its early AI5 min
- 23:20Abridge started with providers to build a three-sided network3 min
- 40:25Abridge routes work between in-house and frontier models3 min
- 17:00Abridge moved from a consumer app to enterprise for scale3 min
- 20:07IBM Watson lost trust by promising more than it could deliver2 min
“they just got so far ahead of their skis in terms of what they were saying they could do”
Shiv Raoat 21:29 · Upstarts
Takeaways
- Rao credits Watson with recognizing healthcare's potential.
- He says overpromising eroded trust across the industry.
- Abridge emphasizes shipping working products, not just demos.
About this segment
Shiv Rao says Watson understood healthcare's opportunity but got ahead of what its products could do. He says Abridge ties announcements to products ready to ship soon to protect trust.
Shiv Rao is cofounder and CEO of Abridge; practicing cardiologist.
Co-founded Abridge, which brings context and understanding to medical conversations, and practices as a UPMC cardiologist.
Alex Konrad, Host · Founder & editor, Upstarts Media
Ran Forbes' Midas List for ten years and co-created its Cloud 100 list; founded Upstarts in 2025.
From “Abridge’s Shiv Rao: Taking On Microsoft To Cure Doctor Burnout With AI”, Jul 23, 2026. Watch the full episode
Answers “Is AI overhyped?” See all 11 answers
Thanks. We'll look at and fix what's off.
Transcript
Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.
- 20:11
and demonstrated results it was like game on i remember in that pre uh chat gbt era um when i was at forbes uh our health editor and i looked a lot at ibm watson we were trying to understand why it had shown so much promise and gotten a lot of exciting kind of announcements to be doing some of this work to digitize and improve the health system. I even remember seeing a demo where they showed an x-ray and like scans and pre-LLM AI was going to help with a diagnosis.
- 20:40
It feels like a lot of that wasn't realized until this most recent era. Why was that looking back? I mean, what they got right is healthcare, huge, huge market. And the market has a labor addiction. One out of five Americans works for healthcare in this country. Health systems can't hire people fast enough to get all the jobs done. There are tons of jobs that nobody wants to do. No human wants to do.
- 21:05
So it's the perfect opportunity for AI to assist and to automate as much as possible. Our concept is like, do it to bring the people closer together. And if you think about it, the people who matter most in healthcare are all of us as patients and then our care teams. And if you can do that, you can refactor how healthcare is experienced, how it's paid for. I don't know that IBM Watson didn't recognize at a high level, huge market, huge opportunity.
- 21:32
Where they went wrong is like they just got so far ahead of their skis in terms of what they were saying they could do and the products that they could bring to market. We all ended up in the industry paying for it because it eroded trust. Like you sell these huge stories and then you don't deliver, it really comes back to bite you. So now we're at this moment, though, like even at this keynote that we just had, it was like everything that we're going to demo for you is going to be ready for you in a matter of weeks.
- 22:02
We're going to make sure that the industry understands like you don't need to like we're not shipping slides like we're shipping real product. And you're going to be able to on all your clinicians, your patients are going to be able to benefit from it in a way that like, you know, IBM could never promise. These days you can chat with AI about almost any business problem.