Technology

Yes, the existing piping is not ideal. Remember, a bunch of hotels in Europe still use Booking.com as their booking engine, because there's no piping at all (no booking engine of their own, or their PMS is premise-based and lacks APIs).

Yes, outdated ARI plumbing is a huge immediate obstacle, but it isn't the only one.Legacy hotel systems rely on slow, cached data and one-way connections that frequently crash when AI agents try to make real-time bookings. However, even if the technology is fixed, bigger business problems remain: hotels fear losing customer relationships and revenue margins to AI intermediaries, and payment liability for AI errors remains unclear.In short, while the technical pipes are broken, the deeper issue is a lack of trust, clear business models, and secure payment systems for autonomous bookings.

The main impediment isn’t tech plumbing; it is inherent in the concept of “agentic AI” itself. It is based on Gen AI LLMs, which are probabilistic, next-best-word engines. They have no “real-world” models, eg understanding higher / lower, before / after, logic, distance, numbers. They mimic very well. Super for wordsmithing and unstructured data / document analysis, poor for most everything else.

Having a human at the helm, not just in the loop, is key to setting AI agents' goals, limits, and escalation triggers, and then to being able to watch the audit trail for anomalies.First, delegate commercial tasks that already operate on written rules, reserving human judgment for those that don't.These tasks go first because the limits are already written.

Hotels have increasingly adopted AI for data analysis and recommendations, yet decision-making and execution remain largely manual. The next leap is moving from AI-powered insights to autonomous action, with humans focusing on governance, strategy and exceptions.In Revenue Management, agents can monitor demand and adjust rates, inventory and restrictions autonomously.

We've seen that significant revenue opportunities, both from groups and leisure guests, exist inside reservation teams' Outlook inboxes, but they often lack the time and capacity to systematically manage them.I think one of the first things hotels should delegate to AI agents is managing these opportunities from the initial inquiry all the way to a booking, although that is very hard to do correctly and responsibly.AI agents should be able to understand guest requests, check availability and rates, prepare relevant offers, and proactively follow up if the guest, travel agent, or whoever made the inquiry doesn't respond.