Not All Hotel Automation Should Be AI, Says the RPA Vendor Standing Next to the AI Booths at HITEC

Not every hotel workflow needs AI, according to RobosizeME Chief Revenue Officer Sean Anderson, speaking to Hospitality Net ahead of HITEC 2026. His argument is specific, not a blanket skepticism: for defined, repeatable back-office tasks — loyalty point reconciliation, OTA invoice matching, rate parity checks — robotic process automation is cheaper, more reliable, and easier to audit than an AI-based tool, and when automation touches core hotel systems, the data sovereignty, privacy, and PCI-compliance guarantees “simply have to be in place” in a way freeform AI introduces risk around.

It’s a useful counterweight to a separate governance framework Mews laid out the same month. Mews’s “earned autonomy” model has agentic AI expand its scope in a hotel only as it demonstrates reliability, starting every deployment in a human-in-the-loop mode where staff approve proposed actions before the system acts on its own. Mews’s emphasis on “decision transparency” — showing why an agent recommended a specific room assignment, say — is a solution to a problem RobosizeME’s argument sidesteps entirely: RPA doesn’t need to earn trust through explainability, because a rate-parity check or invoice match has one correct answer and no judgment call to explain.

That’s the actual dividing line hoteliers should be drawing, and it isn’t AI-versus-no-AI. It’s judgment-versus-rules. A workflow with a single correct output and an audit-trail requirement is an RPA problem even when a vendor is happy to sell it as an AI one. A workflow that requires reading a guest’s preference history or handling an edge case RPA can’t script for is where the earned-autonomy model actually applies. Buying the wrong tool for either job is how a hotel ends up with automation that’s either needlessly expensive or needlessly unaccountable.