The potential is clear, but the path is not trivial. According to the report, the main barriers to scalability are lack of expertise (62%), absence of a clear strategy (51%), and technological integration challenges (45%). In operational terms, this means many groups live with AI “islands” that aren’t sufficiently interconnected with their stack: PMS, RMS, CRM, booking engine, or marketing tools act as silos, hampering full data leverage and robust governance. It’s no coincidence that the real level of dependence on AI scores an average of 4.7 out of 10: adoption exists, but AI is still perceived as complementary rather than a core pillar of the business model.
Today, the greatest perceived value lies in business intelligence and guest communications. The former makes it possible to visualize performance, detect demand leakage, and fine-tune pricing and distribution with greater precision; the latter speeds responses across owned and third-party channels, reduces wait times, and maintains brand consistency. Looking ahead, personalization and ancillary sales attract the strongest bets: experiences, upgrades, and dynamic services orchestrated by models that combine preferences, travel context, and price elasticity promise to boost RevPAR and NPS without necessarily increasing operating costs.
To turn momentum into sustainable results, the study suggests a pragmatic agenda. First, consolidate a corporate AI strategy that sets measurable goals—incremental revenue, time savings, satisfaction—and priorities by use case, avoiding scattered projects. Second, strengthen capabilities: build mixed business-tech teams who understand both hotel processes and the capabilities and limits of the models. Third, design for integration from the start: open APIs, data governance, and security and compliance criteria that allow frictionless scaling. Finally, measure and iterate: tightly scoped pilots with clear hypotheses and KPIs to decide what to scale, pause, or replace. In essence, this is the line advocated by the report’s authors: transform fragmented data into an organization-wide asset and move from retrospective reporting to real-time action.
Competitive pressures are mounting. Demand is more volatile, distribution more complex, and labor costs higher. In this context, automating the repetitive to free teams from low-value tasks is not just about efficiency: it’s an opportunity to reinforce genuine hospitality at the moments that matter. AI does not replace the guest experience, but it can anticipate needs, propose relevant alternatives, and ensure every interaction—human or digital—is more fluid and memorable. Hotel groups that scale wisely—aligning strategy, talent, and integration—will be better positioned to capture growth and loyalty in the new lodging cycle.
The picture painted by the report is as promising as it is demanding: an industry that has already embraced AI at scale, but needs to raise the bar on technological maturity. If 2025 is the year of moving from testing to production, leadership will come from those who turn automation into a measurable competitive advantage, with solid data governance, impact metrics, and a guest-centric vision. That is the challenge—and the opportunity.
