Dear ‘Hospitalians’. AI. We’ve Seen This Before — Sort of

Yes, another article on AI. However, in this I provide both a historical disruptive technology point of view and a prospective view for AI in the hospitality/travel/leisure industry. My protagonist is the ‘Hospitalian’ – simply, those of us in and around the hospitality/travel/leisure businesses.

I offer three specific, actionable considerations for senior executive hospitality leaders to incorporate AI into our strategies and operations, along with specific AI hospitality examples, and importantly relevant historical technology perspectives that can guide us.

‘Hospitalians’ and AI. Depending  on how you view the topic of AI, you may be optimistic, pessimistic, or perhaps neutral with a ‘wait and see’ approach. Are you surfing this massive wave as it takes rapid shape? Or are you running in concern of getting negatively impacted by it? Both reactions are natural as you and I are human, unlike the ‘bots’, algorithms, and models driving the innards of AI-enabled methods.

Having been personally involved in helping shape and deploy several past disruptive ‘digital waves’ and being involved in applied ML-AI the past few years with both hospitality and tech companies, I am bullish on this wave; I am a wave surfer. I have also been reflecting on  several lessons learned from past digital disruptions that can be applied, my fellow ‘Hospitalians’.

| Three Leadership Considerations of AI FOR Hospitality |
Drawing on the past ‘digital waves’ [see later section] and the current opportunities that AI present (including GenAI / ChatGPT), I offer three key strategic considerations for Boardroom, C-suite, and business unit leaders as it relates to AI:

  1. Consideration: Be Clear on The Business Problem(s) We Are Aiming to Solve?
    Be specific. For us in hospitality (for that matter in most consumer/end-user facing industries) the opportunity drivers often fall into these three broad categories. Having internal clarity strategically and operationally can then help point AI-enabled initiatives toward:
    a) To what extent can we increase personalization and elevate the guest experience to grow revenue by driving customer acquisition, engagement, loyalty, referrals, and larger share of wallet?
    b) How much can we improve internal business efficiencies of staff engagement and/or expenses to expand margins and EBITDA?
    c) Or, can we utilize new techniques to improve quality or time to market or other competitive drivers, which invariably will aid revenue and/or EBITDA growth.
  2. Consideration: Has The Internal Team Been Through Evaluating/Deploying Disruptive Tech Before?
    As I mention in my ‘history lessons’ [see later section], in previous new digital waves that took shape, ‘off the shelf’ skills/resources often did not exist. Why? These were new emerging fields, just like AI is now. Often the skills needed to succeed are frequently the ‘softer attributes’ as much as they are the technical/functional – e.g. leaders and specialists who have prior experiences to draw upon, that have been in similar ambiguous contexts before, that exhibit high learning agility, risk-taking, and data-driven analytical experimentation. In prior disruptive digital waves, often the skills needed came from outside the traditional companies and sectors. If one does not have these skills internally, it is the perfect context to augment via external skills to couple with the current internal teams.
  3. Consideration: Is the Organization Adept at Acting and Experimenting Swiftly?
    We should not put our heads in the proverbial sand (even if you run a beach resort). Planning, deploying, and trialing is key to building new muscles and capabilities, or enhancing the existing internal muscles. In doing so, it is vital to have leadership that fosters the needed culture of appropriate risk-taking, experimenting, measuring, and iterating. In innovation, there is an adage: ‘innovation loves constraints.’ Counterintuitively, such assessments and deployments of new tech can actually be process-driven and with constrained resources. The disciplined approaches will have broad business cases in hand and be metrics-driven to inform the business decisions. And core to it all is a practice of an overall learning organization.

| What is ai?|
AI. Artificial Intelligence. What is it – in simple terms. As you probably know from elsewhere, AI is when computers / “machines” can perform [increasingly] tasks that otherwise would require human logic, experience, and intelligence. The field of AI covers many disciplines (akin to science) and has many branches including machine learning, deep learning, narrow/general AI, computer vision, robotics, natural language processing, and more. The recently mainstreamed popularized ChatGPT is in the narrow/general AI branches – the types of AI that possess human-like intelligence and in this case complex language models or what you likely have heard as “LLM” – large language model architecture. The “GPT” means ‘Generative Pre-Trained Transformer’, or also referred to as Generative-AI or GenAI or conversational-AI. Whew. Importantly, be mindful to not conflate key elements of AI: while ChatGPT equals AI (it is inside one of the AI disciplines); AI does not necessarily equal ChatGPT. Whew, again.

| Common and More Complex AI Ideas for Hospitality |
Here are some applications of AI within the hospitality industry. You and your company may already have embarked on these more common (but still powerful) applications of AI. Again, these can drive revenue via guest/customer/staff personalization and/or internal business efficiencies:

  • E.G. Personalized Recommendations – to tune even more for a guest’s desires by tailoring operations to prior preferences and making sharper recommendations, usually through a combination of internal and external data sources.
  • E.G. Virtual Assistants/Chatbots – for bookings, service interactions, and service recovery to lift more routine tasks from human agents so they can focus even more on higher levels of service. And of course on-demand language translation services for global, ubiquitous customer engagement.
  • E.G. Revenue Yield/Cost/Profit Optimization – for analyzing mass amounts of internal and external data to further drive revenue yield, profit, etc. while optimizing occupancy or load factors.
  • And the list goes on…

Further, here are a few more complex and even more powerful business enabler examples of applying AI in hospitality:

  • E.G. Predictive Maintenance – predictive modeling for when equipment in hotels, airplanes, theme parks may need maintenance to continue driving safety, cost efficiencies, and guest experience.
  • E.G. Emotive Insights – digging in deeper to guest/customer sentiment in a causal as well as predictive manner to tie back to marketing, sales, and customer service actions. Similarly, techniques can be applied internally to analyze customer success teams to inform and improve training for improved service.
  • E.G. Operational Sustainability – the monitoring and computational analysis of the total end-to-end consumption/waste cycles, processes, and cost/benefits of sustainability initiatives to help inform and drive broader ESG goals likely tied to the UN SDG’s.

| LEARNINGS From the Recent Digital Past. It Matters… |
Let’s walk down memory lane. Why? Because history offers valuable themes and lessons that are applicable to AI:
à new digital tech emerges à ingenious innovation and transformation leaders and staff figure out how to harness the new tech for business purposes for revenue and/or business efficiencies à the corporate culture leverages a risk-taking and experimentation mindset à resulting in many new winners and many dislocations and market ‘losers’.

Further, the speed of this AI wave taking shape today is at a pace and breadth unlike anything we have seen before. I was in the audience last year at the SKIFT conference when Clare Ward, Worldwide Tech Leader for Amazon’s AWS, quoted [in reference to AI including GenAI]:
Today is likely the slowest technology innovation we will ever see.
Let that sit for a minute.

The Rise of WWW…

For those that were running businesses in the mid-90’s, remember when ‘www…” came into the foray? Back then, email communications and websites were sprouting up, and some of us in the burgeoning E-commerce sector called it the ‘world wide wasteland’. There was no history or institutional knowledge of ‘E-commerce’ – we just had to figure it out strategically and operationally. Quickly. Companies large and small scrambled to put up a website with content and/or transactional capabilities. That’s great, as the sites could increase efficiencies and expand one’s presence and reach. And for many, it drove transactional efficiency and more ‘one-to-one’ marketing (or it felt that way even though still largely reaching a mass audience). There were obvious winners and losers. Notably, brick & mortar-based travel agents with large books of business were dramatically impacted.

Around that same time the online travel discovery and booking marketplaces launched (think Travelocity, Expedia, others). The advent of what we use and take for granted now became known as the OTA’s (online travel agent) and quickly garnered massive scale. As a consumer, do you remember the first time you quickly price shopped multiple offerings and booked an airline ticket with the click of a button? This drove massive shifts in the buyer/supplier dynamics.

The Emergence of Mobile Engagement

Fast forward, into the 2000’s. Those in business then, remember how often in whatever halls you were in at that time discussions of “we need a mobile app. How do we do that?” That need may have been true, and as mobile apps launched at breakneck speed many floundered as the end-user consumer was confused on the real utility and benefit to them. The winners were those that understood the users’ needs and latent needs, and oriented on-demand personalization for them, while internally perhaps simultaneously driving business efficiencies. And yes, such efficiencies caused workforce and skills displacement – e.g. in the world of reservations and customer service agents.

Social Media Platforms. Online Communities.

Next, we wrapped around web and mobile the wave of social media platforms/communities – another digital wave. Not just the volumes of people (quickly billions!) and the social engagement/disenfranchising that manifested from ‘likes’, ‘tweets’, and ‘swipes’, but we also birthed the case for even deeper marketing techniques. How many times did you hear, “we need to advertise on [insert favorite social platform]?” For marketeers and business innovators, this presented a unique opportunity to drive sharper segmentation and engagement in various stages of the marketing “why” vs “buy” funnel. And simultaneously the audiences ushered in the age of the online influencers. When done well, it works extraordinarily well. And on the flipside, there are countless cases of ‘failed’ attempts in social media.

Connected-Devices and IoT

The next wave in the 2010’s was also heralded to change the world again as connected-devices, IoT (Internet of things) proliferated. From Nest thermostats and Siri and Alexa, to ‘always-on’, viewable anywhere home cams, to remote data sensors for businesses, the list was plentiful. I even had a connected IoT egg tray in my refrigerator that sent me and my wife real-time text message alerts when only two eggs were left in the tray (seriously, ask me about it). The IoT deployments extended to smart hotel rooms, wearable smartbands at theme parks, and even to smart cruise ships – happy to talk about my time deploying Princess MedallionClass wearables and mobile connected experiences. Overall, the IoT wave was not as thunderous as www/E-commerce, mobile, and social, though its impact on ease of use, personalization, insights, and efficiency is still present and continues to roll forward. Keep an eye on (literally) Apple’s Vision Pro even though the innovative Google Glass ‘failed’ way back in 2014.

| In Closing: Humans at the Center of AI |

Whew. Again. With this large, complex, fast-moving wave called ‘AI’ upon us, we must also keep the human side at the center. In hospitality operating contexts where we blend physical contexts with digital realms – with guests and front-line staff across hotels, airlines, cruise ships, theme parks, restaurants, arenas/venues, resorts, parks, etc. – we are here to serve consumer, business, and ‘bleisure’ travelers and vacationers. They are trying to enjoy their vacation time and/or be productive in their work travels. They are individuals. They are people. And we ‘Hospitalians’ serve them. In ‘hospitality‘ – derived from Latin ‘hospes’ meaning ‘to host’ – the power and need of human connections should not be underestimated. Borrowing from product innovation, the legendary Guy Kawasaki quoted:  “Think Digital, Act Analog.” This is even more imperative in the wave of AI, as humans are analog creatures.

#AI #hospitality #leadership #transformation #ono #PragShah

*Prag Shah is a former operations, digital, and transformation executive of Vail Resorts and Princess Cruises.


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