CHTA's New AI Guide Skips Capabilities and Goes Straight to Workforce Protection — Bias Audits, Vendor Scorecards, an ROI Calculator

The Caribbean Hotel and Tourism Association, representing 32 National Hotel Associations and more than 1,000 members across the region, released the “AI Workforce Transformation Guide for Caribbean Hospitality” — the third entry in its AI Guidebook Series. What’s notable is the framing choice: rather than another primer on what AI can do, CHTA built the guide around what AI does to the people already doing the work, pairing conceptual grounding with an ethical AI charter, a bias audit protocol, a vendor scorecard, a pilot plan, and an ROI calculator. CHTA President Sanovnik Destang put the stakes plainly: AI’s value “will ultimately depend on how our industry uses it to support its people and strengthen its businesses.” A preview is public; the full guidebook sits behind the CHTA member portal.

That workforce-first framing tracks with where analyst research has been pointing. Gartner’s four shifts shaping the future of work name workforce amplification, not automation, as the throughline enterprises need to plan around — Gartner projects that by 2029, 30% of employees laid off due to AI replacement will need to be rehired, often at higher cost, and warns that treating automation as the point rather than the means is “the greatest mistake” of the early AI era. A vendor scorecard and bias audit protocol are exactly the kind of guardrails that framing implies a workforce-protective AI rollout needs — tools most individual hotel owners have no practical way to build themselves.

It also continues a pattern from AAHOA’s new procurement marketplace, published the day before: a major hospitality trade association building structured AI adoption tooling — governance-minded, ROI-conscious — for member properties that individually lack the scale to develop it. AAHOA did it for procurement; CHTA is doing it for workforce risk.

For Caribbean hospitality specifically, where labor markets and regulatory context differ meaningfully from the U.S. and Europe, a regionally-specific bias audit protocol is a harder-to-find resource than another general AI explainer — and a more useful one.