A Surgeon-CMO Makes the Case for AI in Perioperative Care, With Caveats

A guest article by Qventus CMO Dr. David Atashroo argues that AI-driven automation in perioperative care has moved from theoretical promise to a practical patient safety obligation. The piece outlines what a concrete execution strategy should look like for health systems trying to operationalize AI in surgical workflows.

Why it matters

The argument that AI in perioperative care has crossed from theoretical to obligatory is a significant claim, and it deserves careful unpacking. Surgical care operations involve layered human coordination, time pressure, and consequences that compound quickly when things go wrong. If AI tools can reliably reduce variability in scheduling, case preparation, and post-operative monitoring, that is genuinely meaningful. But reliable is doing a lot of work in that sentence.

The challenge with vendor-adjacent commentary, even when written by credible clinicians, is that the framing tends to move from possibility to obligation faster than the evidence base supports. That does not mean the argument is wrong. It means health system leaders should be asking for specificity: which failure modes does this address, what does the human oversight layer look like, and how do we measure whether the AI is actually improving care rather than just adding a new layer of process.

What to watch

Whether health systems that have deployed AI in perioperative settings can demonstrate measurable safety and efficiency outcomes independent of vendor-reported metrics.