Key takeaways

  • AI is starting to have a major impact across industries, but in travel, the implications are especially deep, as the technology is likely to alter the commercial structure.

  • Framing this phenomenon as strictly positive or negative is the wrong approach.

  • For industry participants, the key is to proactively anticipate and adapt to the likely evolution and the new business models it will yield.

  • AI is not merely a tool that will enable travel industry players to do what they already do, only better; it will also empower entirely new forms of competition.


 

Few topics are garnering the level of attention that artificial intelligence (AI) is these days. But in the travel industry, the vast majority of that attention is focused on individual applications and the introduction of new capabilities. Surprisingly little discussion is taking place around how AI could fundamentally alter the travel industry’s commercial structure.

Yet there are already tectonic shifts taking place in travel due to AI. Based on conversations we’ve been having with dozens of travel’s most senior executives, we have observed notable changes in the way these leaders are starting to think about business models and competitive dynamics. We also see a pattern emerging, and have identified three distinct trend lines and related impacts that AI innovations could drive for the industry. For convenience, we have given each a name:

  1. The Goldilocks Opportunity
  2. The Netflix Effect
  3. Travel-as-a-Service 

The Goldilocks Opportunity: AI-enabled improvements to the traveler experience will drive the most meaningful disruption to the middle of the market.

Many consumer-facing innovations have historically been adopted at the high end of the marketplace before trickling down (through more efficient production) to lower tiers and, in some cases, becoming commonplace. There are many well-understood examples of this phenomenon in markets such as cars, consumer electronics and fashion. In travel, however, we believe that rather than impacting the luxury end of the market first, AI will have a more immediate impact on mid-tier operators. For example, AI might allow a mid-tier player to generate personalized services and concierge-style amenities, replicating offerings similar to what upper-tier providers currently use their more expensive labor models to deliver.

As luxury travelers already have every wish granted to them, they are unlikely to see much of an improvement in their experience if AI is introduced. At the budget end of the market, consumers will continue to receive stripped-down service because low-cost producers win in that segment. At both ends of the spectrum, AI will translate into lower-cost delivery that will either be captured as margin by suppliers or passed along to the guest in savings, the degree to which will depend on the strength of the individual brand.

Where the impact of AI will be felt most deeply is in the middle tier of travel, as it will enable service providers in that category to create a proliferation of new models by making different cost trade-offs. As AI will afford significant improvements to quality, the most acute effect might be felt as some budget travelers can now justify a modest trade-up to the middle to exploit a more significant quality differential. Conversely, some companies that offer high-end services today may have to work much harder to justify their price premium (see Figure 1).

The Netflix Effect: Value chain participants with the broadest sets of consumer data are best positioned to win.

For companies that provide travel-related services to consumers, the more data they have, the more valuable their offerings. Much like other data-driven businesses such as media and search, this creates a kind of virtuous cycle: The smarter and more compelling a company can make its offer by using data provided to its “machines,” the more business it will drive and the more market share it will gain, which will in turn generate even more data. In travel, an obvious area of focus would be booking services; the more data a booking service has, the better it will be able to anticipate and offer consumers deals that are personalized just for them (see Figure 2).

We anticipate such a data-driven virtuous cycle creating a huge opportunity for online travel agencies (OTAs) in particular, especially as regulators crack down on the tech giants’ ability to indirectly observe the behavior of consumers. OTAs are in a different position, as they are not solely reliant on “stalking” to observe behavior — many customers are willing to give information about themselves in return for more personalized travel suggestions. OTAs also follow guests across their entire travel journey, so if those guests are willing to store their preferences and profiles in exchange for more convenience and more relevant suggestions (and potentially, loyalty points), the agencies could have access to the richest set of traveler data possible. But to make use of that data, it will be incumbent on those scale players to implement effective AI.

Scale is definitely a major factor in this race; however, AI will also create new opportunities to counteract the traditional winner-takes-all scenario among travel service providers. Other business models and challengers, including smaller players, could carve out parts of the market so long as their prediction and personalization offers are better than those of well-established operators within defined niches.


How Will AI Affect the Travel Industry?

The promise of AI cuts across multiple industries and travel is no exception. The difference is that the potential impact and disruption for the travel industry will be much greater than expected.

How artificial intelligence revolutionizes the travel industry


Travel-as-a-Service: AI will bring about expanded use of themed subscriptions and ‘clubs’ for booking travel.

Among the areas where smaller players have the opportunity to make the biggest impact using AI is in the emerging model of Travel-as-a-Service. While AI will help online travel agencies better serve the DIY travel shopper, it will also empower the “do it for me” (DIFM) traveler segment with the ability to let the “machines” shop for them. AI-empowered consumers will no longer have to decide, in the moment, whether the deal before them is the best for them. Rather, consumer-focused AI solutions — much in the way a trusted traditional travel agent would have done 20 years ago — will know and understand a consumer’s many priorities and be able to act on the person’s behalf to find the best options.

Once DIFM travelers are convinced that the AI machine works as advertised, some of them will stop booking each trip independently and instead subscribe to one or several theme-based travel clubs that are focused on particular travel missions and contexts. The club will learn, over time, about those travelers’ preferences, get better and better at presenting them with salient solutions, and increasingly become their go-to trusted source for specific travel interests and needs (see Figure 3).

A club with this kind of insight would also be in a great position to partner with other brands and service providers to make related offers in adjacent spaces, opening up a new revenue stream and, at the same time, enhancing their value in the eyes of the club’s members.

Conclusion

AI is starting to have a major impact across industries, but in travel, the implications are especially deep, as the technology is likely to alter the commercial structure and have important second-order effects on competitive dynamics. Framing this phenomenon as strictly positive or negative is the wrong approach. For industry participants, the key is to proactively anticipate and adapt to the likely evolution and the new business models it will yield. AI is not merely a tool that will enable travel industry players to do what they already do, only better; it will also empower entirely new forms of competition. It would be a major mistake to underestimate both the opportunity and the risk that this inflection point presents.

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