That AI Vendor Deluge? Let's Talk Strategy

Healthcare CIOs, are you feeling the AI vendor flood? It’s moving fast. One day it’s exclusive EHR partnerships, the next it’s radiology AI requesting PACS access, then your core system providers promoting their own AI suites. The potential is massive (Fortune Business Insights projects the market will exceed $504 billion by 2032), but right now? It feels like navigating a complex crossroads of opportunities, with everyone offering their version of the future.

I had multiple vendor calls just last week. Each one claimed they were "the exclusive AI solution" for something critical. Sound familiar?

It’s like approaching an overwhelming interchange where every exit promises paradise. Every vendor claims the fastest route, but where are we actually going? We're encountering promising but overlapping roadmaps and often unclear long-term value. The pressure to act is intense, fueled by hype and sometimes by your board asking, "what’s our AI strategy?" But how do we separate true strategic value from the noise when everyone is selling the future?

I’m hearing a consistent theme from successful peers: disciplined caution. Validate ROI rigorously. Prioritize actual impacts on clinical outcomes, patient experience, and operational improvement. The data is telling. While Snowflake Research found that 92 percent of early AI adopters across industries eventually see ROI, a Bain study shows only 54 percent of healthcare organizations achieve it within the first year. That gap is real and costly. We need solutions to real problems, not just technology searching for relevance.

Ambient AI feels different, though. Many organizations are moving faster there because the value proposition of reducing documentation burden and improving clinician satisfaction is clearer. One CMIO told me, "Delaying ambient might cost us doctors." That feels tangible. Outside of that, it is mostly pilot programs and phased rollouts. Even with projections like Dialog Health forecasting that 90 percent of hospitals will use AI by 2025, the approach remains measured.

And let’s be honest, evaluating these tools consumes resources we do not always have. For those of us deep in application rationalization (raising my hand), adding another point solution often feels like a step backward. Integration is messy with separate logins and clunky workflows within our EHR, ERP, or PACS. I have seen AI "solutions" that unintentionally create more work than they solve.

The organizations finding success are starting with strong internal governance through AI Centers of Excellence, structured evaluation frameworks, and clear success metrics before any contracts are signed. One colleague shared that they reduced their AI vendor list from 23 to 10 simply by using a straightforward impact versus integration matrix. Smart.

So how are you navigating this? What frameworks are helping you evaluate AI while simplifying your tech stack? How are you managing internal expectations and hype?

I am gathering different approaches that work. Please share yours in the comments. Let’s move beyond the hype together and focus on strategic impact by solving real problems, not just chasing trends.

What’s your approach? Has anything delivered measurable value yet? Let’s talk.

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