Ingram Micro HIMSS Ep#6 How Healthcare Organizations Should Actually Start with AI

Ingram Micro HIMSS Ep#6 How Healthcare Organizations Should Actually Start with AI

📄 YouTube DescriptionEveryone is talking about AI in healthcare — but most organizations are still stuck on where to start, which tools to trust, and how to move from a pilot to something that actually changes day-to-day operations.Recorded live on the floor at HIMSS, this conversation features Austin Montgomery, VP of Partnerships at Prominence Advisors, and Andrew Williams, Director of Data Science — the healthcare data and AI enablement company helping health systems build AI-fluent organizations.Andrew cuts through the hype to explain what AI in healthcare actually means beyond chatbots, why point solutions often fall short, and how the shift from "what you can specify" to "what you can verify" is changing how organizations build and scale AI solutions.🔗 Learn more at prominenceadvisors.com or follow Prominence Advisors on LinkedIn.⏱️ YouTube Timeline0:37 — Introduction — Meet Austin Montgomery and Andrew Williams from Prominence Advisors0:59 — AI is not just ChatGPT — the full spectrum of healthcare AI tools2:13 — Scaling KPI monitoring, anomaly detection, and expert bottleneck removal2:58 — Operating at the top of your license — the north star for healthcare AI3:25 — Myth vs. reality — what organizations get wrong about AI in healthcare3:52 — Point solutions vs. platform approaches — how to evaluate the difference4:56 — UC Davis's Tiger platform — GenAI enabling text exploration at scale6:03 — Building an AI-fluent organization without bottlenecking on data scientists6:28 — What roles and processes does an AI strategy actually need?7:00 — AI fluency as the new literacy — not a job title, a capability8:08 — How process governs the leap from fluency to a portfolio of AI value9:20 — Managing the explosion of AI output with old adoption methods10:18 — Andrej Karpathy's framework — from "what you can specify" to "what you can verify"11:31 — Using LLMs to handle boilerplate and free teams to focus on outcomes12:51 — How to frame getting started with AI for organizations asking "where do we begin?"13:39 — The fine line between a pilot and production — solving end-to-end in a narrow domain14:38 — What comes after the dashboard — anomaly detection, root cause analysis, and natural language query15:55 — From narrow use case to reusable building blocks and scalable frameworks16:25 — Building the muscle for taking AI assets into production for the first time17:09 — Closing remarks and how to connect with Prominence Advisors🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization

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Episoder(289)

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