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A 4-part framework for buying AI that drives outcomes

A practical guide for healthcare purchasers.
By Akin Oyalowo, MD, MS, and Nupur Srivastava, SVP of Product
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Healthcare organizations are moving fast on AI. Consumers are already turning to general-purpose AI for everyday health questions, and 75% of U.S. health systems are running at least one AI application. But speed isn't the real risk here — direction is.

What are we racing toward? Providers, payers, and the vendors supplying them are gravitating toward use cases where the financial pull is strongest and the ROI is fastest, not necessarily where patients and purchasers stand to gain the most. Will this create efficiency? How quickly will this pay off? These aren't the most important questions.

The question that matters most is: What's the net impact of this AI within the payment model, workflow, and population where it's deployed?

We've been on both sides of this question. One of us (Nupur) is an engineer and executive who has spent the last decade building and shipping clinical AI. The other (Akin) is a gastroenterologist who spent years at the bedside before advising health systems and carriers on strategy, and now sits across the table from the employers and health plans deciding where to allocate budget.

This vantage point has taught us that everyone at the table, buyer or builder, needs to get sharper on how we evaluate AI solutions. As a buyer, you need a framework to separate tools that genuinely move outcomes from tools that just move money around.

Start by focusing on four key principles:

  • Start with the mechanism, not the model. Require a one-sentence, verifiable explanation of how a tool actually works — not a category like "improves navigation."
  • Be clear on financial incentives and objectives. Ask who benefits financially if the AI works exactly as intended, and evaluate near-term and long-term ROI separately.
  • Assess workflows, not features. Ask for the click-by-click workflow, and pressure-test what happens when the AI doesn't know the answer.
  • Move faster with better judgment, not more process. Tier your AI portfolio by risk and govern each tier differently, rather than putting every tool through the same review.

The goal isn't to move faster or slow down. It's to know exactly what you're deploying, why, and who's accountable when it matters most.

About the authors
Akin Oyalowo headshot
Nupur Srivastava headshot