44% of Travelers Now Ask AI to Book Their Hotel. Aven Hospitality's Readiness Guide Says Most Properties Aren't the Bottleneck — Their Data Is.

Aven Hospitality — formerly Sabre Hospitality, the company behind SynXis, which serves roughly 35,000 hotels across more than 190 countries — published a Hotel AI Readiness Guide built around a specific claim: 44% of travelers now turn to AI assistants to research, compare, or book accommodations. Its core argument isn’t that hotels need to adopt more AI tools. It’s that most properties should fix their underlying data and systems before they do.

The guide offers six evaluation questions spanning guest experience, data management, governance, and technology infrastructure, plus concrete steps for improving property information accuracy and content quality. It also flags the Model Context Protocol (MCP) as an emerging mechanism for making hotel information machine-readable to the AI systems now doing a growing share of travel discovery — a technical detail that matters because “readable by a search engine” and “readable by an AI agent” are turning out to be different requirements.

The readiness gap this addresses is well documented elsewhere in the industry. A Lighthouse survey cited in a separate Hospitality Net roundup found only 10% of hospitality leaders feel fully prepared for AI even though 67% expect it to have a major impact — and, tellingly, more than half of AI-generated pricing recommendations at surveyed properties get overridden by staff, suggesting the bottleneck is trust and governance as much as technology.

Aven’s guide is vendor-authored, not neutral research, but its framing lines up with what independent operators are already building toward: Cloudbeds’ Insights product, launched in July specifically to give multi-property groups real-time, unified data access instead of scattered PMS exports, is the same underlying bet — that the AI layer is only as good as the data foundation underneath it, and that foundation is where the actual readiness work has to happen first.