TP506 – Who Hears the Patient Now

Touch Point Podcast
Touch Point Podcast
TP506 - Who Hears the Patient Now
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In March 2025, Gartner predicted that agentic AI would resolve 80 percent of common customer service problems on its own by 2029. This February, the same Gartner practice predicted that half the companies that cut service staff because of AI will hire people back into similar work by next year, under different job titles. Eleven months apart, same firm.

Healthcare is buying the first forecast right now. Voice AI vendors claim their agents can handle most inbound calls, and the business case that follows fits on one slide. Count the calls. Convert them to positions. Book the salaries as savings. What the slide leaves out is the people who train the bot, test it, listen back to it and pick up the calls it cannot finish. Those roles arrive later, in compliance or quality or IT, and nobody sets them next to the number that got approved.

The question to settle before approval is which project this is. A bot answering a call at two in the morning that would have gone to voicemail is a real gain, and that is a capacity project. A case built on fewer people is a different claim. Chris Boyer and Reed Smith leave that one open, because the honest answer depends on what the organization wrote down when it signed.

The second cost is quieter. A voice agent is built to capture the caller’s intent, confirm it and complete it, which leaves no home for the rest of the call. Texas and California now require providers to tell patients when AI sits in the middle of their care, so more patients will know, and some will start asking for a person before they say anything else. Every AI-handled call also leaves a full transcript, more patient conversation than most health systems have ever held, reported upward as one number about how many calls the bot kept.

Amy Brown of Authenticx names the fallacy directly. Executives like to believe AI means immediate cost reduction, when putting AI in front of patients in a regulated environment is a commitment that takes people to keep it honest. Her company now evaluates AI-to-human conversations, and her read on those is not flattering.

If your access center business case counted the calls the bot will answer and not the people who will read them, you approved a capacity project and called it a savings plan.

 

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