In the year 1900, the average life expectancy was 47. A century later, it was 77 globally. Whether or not we extrapolate this trendline linearly, exponentially or asymptoticly, what we do know broadly speaking is that this increase was a result of technological advances. With artificial intelligence already anticipated to increase medical care in a variety of ways, it’s reasonable to expect this technology to help propel life expectancies even further. But what does that mean for hotels?

First and foremost, as people live longer, they will have more good years to travel, thus increasing the customer lifetime value of the average guest. But there’s a critical asterisk in any conversation about this purported longevity revolution, one where hotels will play a significant role in the near future. The scientific research around longevity is increasingly showing that there is no magic pill or panacea that will prolong human life. Rather, the best approach requires habitual lifestyle changes including but not limited to curbing alcohol consumption, eating nutrient-dense foods, varied forms of exercise, quality sleep and chronic stress reduction.

The role that many hotel brands will play is thus one of preventative healthcare, inspiring and consistently helping people through their wellness programming to live better and adopt healthier habits, and, dare we mention, charging a pretty penny to guests for this service.

Alas, the challenge like many other operations comes back to labor. Wellness practitioners have both a particular set of skills and an innate compassion for their guests that makes these team members constantly in short supply. In order for hotel brands to commercialize wellness in a labor-light manner and beyond traditional spa services, technologies like the latest in machine learning become instrumental for future revenue generation.

It’s one thing to nonchalantly throw the word ‘AI’ around, but what does this implementation actually look like on a case-by-case basis? Enhancing a wellness program through AI in 2023 likely comes down to automating various tasks and optimizing workflows so that the existing teams can be as productive as possible. Hence, rather than start with some grandiose application, let’s consider six cases that show how AI may already be churning behind the scenes to improve existing operations, and then branch out into the more futuristic.

Use Case #1: Dynamic availability and dynamic pricing. The first term describes the machine learning process of using past data to optimize a wellness center’s time-based inventory so that the highest profit margin treatments are assigned to the most popular timeslots throughout the week. Similarly, while every hotelier is familiar with dynamic pricing for rooms, this too can be adroitly deployed for other profit centers with the granular yielding controlled by an AI, should the hotelier desire to go this route.

Use Case #2: Automated marketing and bookings. What good is a wellness center if no guest knows about it? What good is a friendly receptionist at the spa entrance if this person is always on the phone with guests trying to remotely book treatments or learn about the services available? Where AI will help is in helping practitioners refocus on the guest, with things like promotions handled through various system connections, automatically generated marketing content and contextual A/B testing withing ecommerce channels.

Use Case #3: Staff and guest scheduling. Unlike hotel rooms, some wellness centers must be very careful to throttle visitor occupancy so that guests aren’t discouraged by treatments being unavailable due to specialized practitioners being off duty. As an aside, the rise of thermal circuits in North America work differently, more like amusement parks that rely on day passes and small groups coming for a social element. Looking beyond dynamic availability to help reorient around high-margin treatments, AI will come to the rescue in a form similar to what’s been to housekeeping, with flexible and predictive team scheduling that optimizes for both guests’ needs as well as each practitioner’s requested hours.

Use Case #4: Personalized guest wellness itineraries. At this point the word ‘personalized’ may be all but synonymous with ML-driven in terms of how pattern prediction towards a specific goal can help to guide service delivery. In the near future, a conversation about what the guest’s wellness goals for their visit will act as the starting point for personalized offerings, using ML from past guests and A/B testing to improve over time what treatments will work best for a guest’s stated goal. Such AI can also incorporate any health data provided to come back with suggested multi-activity itineraries for the guest to then authorize. Right now, these types of wellness circuits or individualized programs are largely done manually through the setup of spa packages, but AI can take this to a hyper-personalized level that takes into account how certain treatments may affect the guest’s bio-individual composition – that is, the effect based on their goals as well as their body composition, basic diagnostics or stress levels.

Use Case #5: Functional nutrition. Right now, nutrition is still a bit like the Wild West, with some proponents of veganism as the best way to eat and others now extolling a nose-to-tail, ancestral diet as the way to go. It’s confusing, especially as we don’t have nearly enough data to definitively pinpoint the best possible diet, while at the same time there’s the matter of ‘functional genomics’ which is a fancy way of saying that different people will live healthiest by eating different foods. To sift through the noise of one’s genome, one’s epigenome (which genes are turned on or off) and other blood markers, AI is quickly becoming capable at computing the multitude of this bio-individual data to arrive at specific recommendations for modifying any dish to optimize nutritional benefits while still remaining within the framework established by the guest’s stated goals. This use case, albeit futuristic, works swimmingly with the numerous resorts that already offer bespoke, all-inclusive meal plans.

Use Case #6: Computational therapies. Bringing it all together for our final use case, when you combine AI-driven functional nutrition with a bespoke guest itinerary, a step further is to customize each treatment to optimize a guest’s biomarkers based on all personal data submitted to the hotel. Perhaps this is as simple as adjusting the time in the infrared sauna to be five minutes longer based on said person’s innate collagen production, along with a specialized remineralization beverage given to the guest immediately afterwards that contains exactly what they need to optimize the body. Or for the more futuristically inclined, it may involve the on-the-spot creation of a bespoke blend of raw ingredients to produce a skin cream that’s perfectly attuned to that guest’s moisture levels. Lab-made meats are still a ways off from global readiness, but such bioreactors may creep in to generate these ingredients in a manner that doesn’t harm the environment. For any use case, we are inevitably talking about data, which then means AI will enter the picture to deliver this degree of personalization.

While the latter use cases may see us authors getting a bit carried away, what’s most important to know is that wellness is becoming an increasingly in-demand amenity for hotel guests, and there are a lot of ways to use AI to ramp up the processes behind the scenes so that when all these futuristic doodads reach the commercial stage your company is ready to seize the day for an already-captivated audience.

Together, Adam and Larry Mogelonsky represent one of the world’s most published writing teams in hospitality, with over a decade’s worth of material online. As the partners of Hotel Mogel Consulting Limited, a Toronto-based consulting practice, Larry focuses on asset management, sales and operations while Adam specializes in hotel technology and marketing. Their experience encompasses properties around the world, both branded and independent, and ranging from luxury and boutique to select-service. Their work includes seven books: “In Vino Veritas: A Guide for Hoteliers and Restaurateurs to Sell More Wine” (2022), “More Hotel Mogel” (2020), “The Hotel Mogel” (2018), “The Llama is Inn” (2017), “Hotel Llama” (2015), “Llamas Rule” (2013) and “Are You an Ostrich or a Llama?” (2012). You can reach Larry at [email protected] or Adam at [email protected] to discuss hotel business challenges or to book speaking engagements.

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