Founder: Turnaround Talk
At the height of the disruption caused by the Covid-19 health pandemic, the South African tourism sector was just about brought to its knees by heavy global and local travel restrictions.
As the country slowly found its feet following this disruption, the tourism sector tried to return to some level of normality. However, significant damage had been done. Many hotels and smaller accommodation providers were forced to close down, and airlines went into liquidation and what was once a massive sector faced significant downsizing.
This sector is still a significant economic driver. What is its future? I recently read interesting insights by McKinsey that discuss the future of artificial intelligence across the tourism value chain. The following is an extract from a McKinsey podcast.
The promise of AI for tourism
Lucia Rahilly: Much of the research for the report drew from interviews with executives at 17 companies across five types of travel businesses. One of those executives is Luca Zambello, CEO of Jurny—an AI-fueled hospitality platform. He says AI will be the new normal.
Luca Zambello: We’re at the very beginning of the hockey stick. Economically, we are at the start of what is potentially the biggest technology disruption that humanity has ever seen.
Lucia Rahilly: So everyone is talking about the disruptive juggernaut that is AI, and particularly gen AI [generative AI]. At a super-high level, and acknowledging that we’re still in early days, what do we expect this to mean for the travel industry in particular?
Vik Krishnan: The travel industry is unquestionably going to be significantly disrupted by AI. Whether it’s gen AI or other forms of AI that have been around for some time remains to be seen. It’s quite clear that if you work through the customer journey and the process of trying to understand where you want to go, where you want to stay, what are the things you want to see, how you want to plan your day-by-day itinerary, gen AI significantly eases the process of travel discovery.
If you then step into what this means for travel suppliers, which includes airlines and hotels and cruises and car rentals and rideshare providers, the promise of AI is very much to help them deliver on the promises, both explicit and implicit, that they make to their customers.
Gen AI significantly eases the process of travel discovery.
What I mean by that is, very often, the expectations of travel are that your flight is on time, your bags get delivered to you safely, you then get to your hotel, your hotel room is available to check into when you get there, and you have a room that provides exactly what you asked for. That baseline expectation is one that many travel companies have historically struggled to meet.
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What AI can do is help airlines ensure that planes are on time. It can help hotels ensure that what they deliver in terms of staffing and the product promise is consistent with what they advertise in their marketing and branding strategies.
Alex Cosmas: Not only is travel and hospitality the world’s largest sector, but it’s actually the most intimate sector. That means the answer for each of us to what a good experience looks like—whether I’m traveling for leisure or for business—is, by definition, fundamentally different. And the promise of AI has been to take the pattern of history, take the pattern of millions, and boil that down to the individual response that is relevant to me as a segment of one.
Nowhere is that promise needed more than in travel, where the experience should be a segment of one. That’s what makes it magical. To be clear, AI is already being applied in the travel sector in spades—specifically, in the operation of schedule assets and the optimized allocation of rooms and crews. That’s been true for decades, and it’s only getting better.
But the customer-facing applications of AI are only now really becoming next-generation. And for the most part, in travel, the best AI applications will largely be opaque to customers, because they’ll still be delivered through the mediums that customers prefer: often through humans, through the front line, through desk agents, through guest agents.
AI is already being applied in the travel sector in spades—specifically, in the operation of schedule assets and the optimized allocation of rooms and crews.
That’s ideally the promise. But the starting point is to say we can’t suddenly expect that customers will prefer to interact through more digital channels than they have in the past. Travel is a very human-centric business. And so the best AI, the best models, will be delivered through traditional channels.
How AI can change travel—for the better
Lucia Rahilly: What kind of value might come from using gen AI in the travel industry?
Alex Cosmas: Our latest estimates suggest that gen AI alone, across sectors, is bound to unlock $2 trillion to $4 trillion of incremental value.
Lucia Rahilly: Wow.
Alex Cosmas: Therefore, not surprisingly, capital is chasing the disruptive sector of AI.
Lucia Rahilly: What are some good examples of products that customers might expect to be using or that might be in the background enhancing customers’ experiences in the future?
Vik Krishnan: Imagine the last time any of you tried to book a trip. You probably started on a search engine such as Google, or you started at an online travel agent such as Expedia, or you started at an actual supplier website if you had some certainty on what airline you wanted to fly or which hotel you wanted to stay at. You probably started with a little box where you put in your destination, you put in your approximate dates, and then you had the search engine present to you a series of results that may or may not have met your needs. Tourism needs to address this.
What we’re imagining in a future with gen AI or AI in general is that you start with something much more free-form and say, for example, “I’m looking to plan a trip with my family to New Orleans for a week in October. Can you help me find a hotel that has a pool for my seven-year-old and is within walking distance of the French Quarter?”
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Wouldn’t that experience be much easier in terms of trying to figure out where you want to stay and what you want to do, as opposed to getting a list of a thousand hotels in an order that may or may not meet your specific preferences and what you actually want out of that trip? It is one of the most obvious examples wherein customers can see a real difference in what gen AI can do to help them with the travel discovery process.
Alex Cosmas: The other application of AI that I’m excited about is this: every customer gives tells. They drop digital breadcrumbs of things they like and don’t like when they bounce off of the page of a dot-com when they’re shopping; when they abandon a cart; when they return less frequently to search; when they arrive on a page only to check a single itinerary on a single day, on a single fare, rather than browsing for 20 minutes.
All of these are small tells that we as consumers provide travel brands. And so the ability to record, “I actually know what Alex is keen on in general and frankly less keen on and less likely to convert on,” and turn that into relevant offers is really important.
AI is only part of the answer for tourism
Lucia Rahilly: Where are we in terms of companies really embracing the use of this next-gen AI and other related technologies?
Alex Cosmas: We’re pretty far down the path of companies both embracing traditional AI and experimenting with gen AI. Very few of the airlines, hotels, cruise lines, and suppliers that I’ve interacted with are not already embracing deployment and actively experimenting with advanced tech. It’s only going to grow.
But there is risk. More is not always better. Faster is not always better. There’s a bit of, let’s say, a cautionary tale that we’ve learned from other sectors, which is that first off, AI is only part of the answer.
I like to say it doesn’t matter if you got the answer right if you got the delivery wrong.
The digital-delivery mechanism is how I go about delivering the answer: a mobile app, a push notification, an e-commerce experience, a kiosk, digital signage, or data just given to the front line. Those mechanisms are as equally important as or, I’d argue, even more important than the predictive and gen AI models behind them.
I like to say it doesn’t matter if you got the answer right if you got the delivery wrong.
Vik Krishnan: To build on Alex’s point about getting the delivery wrong, many of you listening have probably been on an airplane in the last year. How many times have you experienced the outcome of landing, pulling toward the gate, stopping short on the tarmac somewhere, and it turns out the gate’s not available yet. This is a tourism nightmare. Therefore, you have to wait for the other aircraft to taxi out, so your plane can then pull into the gate.
The reality is that putting together an operational execution plan involves data from so many different sources that aren’t necessarily pulled together in a large model. So it doesn’t necessarily enable or unlock this type of orchestration. And this is where AI can be enormously helpful.
There are companies out there that try to understand turning an aircraft, which is the process of essentially getting it from arrival to departure for the next flight. That involves actions both above the wing—for example, getting passengers off and onto the plane, getting the aircraft catered—and below the wing—for example, getting bags on and off the plane.
It involves refueling aircraft. It involves a number of other maintenance-related and ground-handling-related activities that many consumers don’t see. All of that is an extremely delicately orchestrated ballet that happens at an airport every single day, while involving multiple third parties and several different suppliers. It involves a fuel provider. It involves a ground handler. In some instances, it involves a different gate agent than the airline itself. That orchestration requires data and communication of very, very large volumes of information.
There are companies out there that are now saying, “We can actually identify when, during an aircraft turn, something didn’t happen according to schedule.” In other words, that catering truck didn’t pull in three minutes after arrival as it was expected to, which induced a delay. And that delay then allowed for a replanning of the entire turn process, so as to deliver an on-time departure. AI has an extremely large role to play in helping deliver on that promise in a way that suppliers have historically struggled to.
Creating a credible economic growth reform agenda
It will be interesting to see how tourism operators capitalise on AI in the future.
Many industry participants in the tourism sector have leveraged the power that technology offers in marketing and managing bookings. However, this is the tip of the iceberg. More must be done to embrace technology to the extent that it will have a meaningful impact on companies and the industry.
The next five to ten years will be a massive learning curve for parties in the tourism sector.
Lucia Rahilly is the Global Editorial Director and Deputy Publisher of McKinsey Global Publishing;
Alex Cosmas is a Partner at McKinsey;
Vik Krishnan is a Partner at McKinsey.
