What the paper studied
Research on AI in hospitality is growing quickly, but very little of it looks at how specific companies publicly report on introducing AI. The authors argue this reflects a broader problem: without a structured approach to AI deployment, stakeholders have limited visibility of how hotel companies are managing the associated risks.
Using an interpretivist, inductive approach, this exploratory paper combines a narrative synthesis of the literature with case examples of how four major hotel groups are introducing AI: Hilton Worldwide Holdings, Marriott International, IHG Hotels & Resorts and Wyndham Hotels & Resorts.
Key findings
- AI touchpoints. The paper identifies the main process touchpoints where AI is affecting hospitality operators.
- Challenges and downsides. It outlines the key challenges and potential downsides of AI deployment, including data privacy violations, algorithmic bias and operational disruption.
- A GRC framework. Drawing on the case examples and the literature, the authors propose a structured Governance, Risk and Compliance framework rooted in ISO/IEC 42001, the international standard for AI management systems.
- Auditable by design. The framework is presented as a practical and auditable pathway for mitigating AI risks, aimed at both researchers and hotel operators running AI change projects.
Why it matters for hospitality
As AI spreads from guest messaging to pricing and back-office work, owners, investors, regulators and guests will increasingly ask how hotel companies govern it. Anchoring AI governance in ISO/IEC 42001 gives operators a recognized, auditable structure instead of ad hoc policies, and treating AI as a governance, risk and compliance question places it alongside risk and compliance processes hotels already run.
Practical takeaways
- Map where AI touches your guest-facing and operational processes before deciding where governance is most needed.
- Treat AI deployment as a governance, risk and compliance matter, not only a technology project.
- Use ISO/IEC 42001 as a reference point for structuring AI management.
- Look at how the large groups publicly describe their AI programs as a benchmark for your own reporting.
Limitations
This is an exploratory, interpretivist study, and its case evidence covers four large international hotel groups, so it may not reflect the situation of independent or smaller operators. The paper was posted as a preprint and has not yet been peer reviewed.