Africa - Latest

If the real question is about skills, mindset, and capabilities, then here's my take: Skills: a Revenue Manager today must think strategically, not just tactically. Revenue management is about defining where the business should go in terms of product and revenue in the next 3–5 years.

A broader skill set — especially in marketing — is becoming increasingly beneficial. Since specialized tasks can now be handled perfectly by AI, commercial roles are moving closer together. This shift makes broad, cross-functional skills more important than ever.

The Revenue Manager we need today looks very different from the one many hotels still have in place. The role can no longer be defined by Excel spreadsheets and static reports. The markets move too fast, the data is too complex, and the opportunities are too big to leave in the hands of manual processes.

When it comes to where our Distribution landscape is headed - it's not even a question. Of course uniting our efforts is the only way to go. Otherwise we'll lose another OTA battle. But there's much more to the world of AI functionalities, it has its tenticles in every part of our tech ecosystem, not distribution alone.

I think we are in danger of running before we can walk here. MCP is Anthropic’s pitch for an open standard to let "agentic AI" bots built on next-word LLMs share data, for example, an OpenAI bot talking to a Gemini bot. Unless you are Marriott or Hilton with hundreds of in-house developers, or a big OTA like Expedia or Booking.com, this really isn’t something you need to worry about.

You could establish your own protocols instead of MCP, A2A, or other widely endorsed standards for agentic interactions. But that would be like creating your own version of HTTP. Not a great idea. The good news is I don't think companies feel the need to change that basic agent-friendly plumbing.

The decisive skill I feel separates a great GM is "managing the balanced scorecard" - enlivening employee engagement, amplifying the guest experience, and ensuring financial stability. Too often, the General Manager confuses what is truly important and relevant to the hospitality business.

For me, the role of a luxury hotel GM is first and foremost that of a balancing act. Depending on the context, whether corporate or private ownership, the GM must be able to adapt and understand stakeholders' expectations. They must be able to deal with ambiguity and create added value.

Strategic foresight distinguishes outstanding luxury hotel general managers from their peers. Empathy empowers a general manager (GM) to understand and anticipate the diverse needs of guests, staff, owners, and partners. In luxury hospitality, emotional connections are crucial; guests often remember how they felt during their stay far more than the details of their accommodations.

It was inevitable that we would move to conversational AI and on-demand UI. The writing was on the wall years ago. Hotels will be caught off guard as OTA AI agents beat them without mercy at the pricing game. It’s time to build a defensive tool.

We will still need beautifully designed websites and flows — but more as validation layers and brand showcases than as discovery engines. OTAs and suppliers will increasingly serve as structured data ecosystems rather than pure UX-driven platforms.

Are we moving to a future - interesting... Though, you remove glossy images and brand (the websites of today), don't we just return to the flat green text screens of travel agents past, but this time operated by AI? Where description and detail was the important asset to capture interest and convert the booking?

Everyone wants the hotel tech stack to be more guest-centric and hopes AI will help to deliver a more personalized experience. This future will be centered around the PMS as the hub for rooms-centric operations and the CRM/CDP for repeat-visit-oriented relationships with guests.A strong connection between these two systems is vital to have the CRM/CDP ingest the most information about guests so that ML has big and accurate data sets by which to recommend segments, retool rates, create suggested packages, A/B upselling offers and so on.But both of these systems are back-of-house.

There is really no difference between preparing data for Gen AI and for other tech tools: structured data must be normalised, deduplicated, and governed, while Gen AI is best applied to unstructured sources like reviews, transcripts, or free-text notes.

AI in hospitality cannot be reduced to a fixed list of use cases, because the technology and its applications evolve too quickly and vary too widely across companies. Each organisation runs on its own mix of operations, tech stacks, data flows, and structures, which means their AI opportunities will always be unique to their context and business challenges.

The age of the hotel brand is ending. For decades, franchises have scaled by selling sameness, consistency over individuality. AI breaks that logic. AI reshapes the vectors of discovery. Instead of guests defaulting to familiar logos or loyalty programs, intelligent systems surface the properties that best match a traveler's needs, preferences, and context.

This is part of a bigger question, I think. As a marketing guy, let me explain it through distribution, using Booking.com as the example. Booking spends billions on advertising, dominates search, builds the user experience that has become the industry template, and runs a multilingual customer service that often outperforms independent hotels.

Yes. It's not limited to franchises and is a pretty long standing clause in agreements. There largely because it was not as prominent a consideration back in the day from a data and technology perspective - harder to get data out of a peice of on premise technology that the owner paid for.