The hospitality industry is at an inflection point.

AI is everywhere. Every vendor has a roadmap. Every hotel group is being told that if they don’t move fast, they’ll be left behind.

And yet, in a recent conversation with Mike Rawson - CIO of citizenM, a very different philosophy emerged that is grounded not in speed or novelty, but in clarity, control, and intent.

If you’d like to listen to the complete podcast you can find it on

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Spoiler Alert - here’s a summary of five learnings that I took away from the podcast

1. Hospitality businesses can’t exist without technology anymore

One of the clearest statements in the conversation reframed the entire discussion: technology is no longer a support layer in hospitality - it is the business.

This isn’t about tools or systems. It’s about leadership.

When technology underpins every guest interaction, every operational workflow, and every decision, the role of technology leaders fundamentally changes. CIOs and CTOs aren’t just servicing / supporting / enabling the business - they’re shaping its future.

For hotel brands, this means strategy, guest experience, and technology are no longer separate conversations.

2. The industry is drowning in AI promises

AI is moving fast, but not always thoughtfully. Mike doesn’t shy away from calling this out directly.

AI adoption without a clear understanding of risk, privacy, and data exposure isn’t innovation, it’s debt. And in people-centric, real world industries like hospitality, that debt snowballs into liability quickly.

CitizenM’s perspective is refreshingly sober: enthusiasm without responsibility doesn’t scale.

3. The real AI question is control, not capability

Much of the AI conversation focuses on what models can do. CitizenM focuses on what they’re allowed to do.

These questions go beyond product features. They touch governance, trust, and accountability.

AI that isn’t bounded by permissions, workflows, or oversight, introduces operational and reputational risk. CitizenM’s approach suggests that the future belongs not to the most powerful systems, but to the most controlled ones.

Capability without intent is dangerous. Capability with guardrails can be transformative.

4. Security and privacy must come before scale

Rather than racing ideas into production, citizenM prioritises discipline with a clear process of POC —> Pilot —> Rollout

This one line reveals a lot.

Experimentation is encouraged, but production is earned. New capabilities don’t scale by default; they pass through scrutiny. This mindset is especially important as AI systems become more autonomous and interconnected.

For hospitality leaders, this is a reminder that trust is built before scale, not introduced as an afterthought.

5. The business is simpler than the technology

One of Mike’s more subtle but important points is that complexity in hospitality often comes from the technology layer, not from the business itself.

This is an important reframing.

Hospitality at its core is relatively simple: sell rooms, serve guests, resolve issues, create a good experience. What makes it feel complex is the accumulation of systems, integrations, and tools layered on top over time.

Mike’s point is that if the technology becomes more complex than the business it supports, it stops being an enabler and starts becoming friction. The implication is clear: technology should reduce perceived complexity, not amplify it.

Final thought

Even though Mike is convinced that AI will be the #1 disruptive factor in the hospitality industry over the next 10 years, the podcast isn’t a manifesto about AI. It’s a conversation about intentionality.

CitizenM’s approach suggests that the future of hospitality technology won’t be defined by who adopts the most tools, but by who asks the hardest questions before adopting any at all.

And with that role comes great responsibility 💪

🎧 Watch or listen to the full conversation

If you want the full context and nuance behind these insights, check out the complete episode:

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Early in my consulting career, one question genuinely puzzled me: how did work happen before email? Was the telephone a 1:1 substitute for email? No inbox, no instant replies, no endless CC chains - yet somehow decisions were made, projects shipped, and companies scaled.

That moment stuck with me, because it revealed something uncomfortable but true:

And here we are with AI.

Each and everyone of us knows this technology will change the world. On an individual level, we get chatGPT to draft our emails, plan our holidays, give us health advice, find answers to loaded “why” questions from the kids, generate recipes from leftovers in the refrigerator (am I giving away too much?)

At a company level, AI doesn’t just save time or provide instant advice, it challenges workflows, roles, incentives, and long-held assumptions about how work should happen. And because I run an AI company, I hear every version of this conversation daily: excitement, skepticism, fear, overconfidence, genuine curiosity. Often all in the same meeting.

What struck me was that most of these conversations were happening at a distance. Armchair judgement. Lofty panel discussions. Utter BS social media commentary. Pitch decks unhinged from reality. Gurus unhinged from reality. Rarely face to face, and rarely grounded in the reality of running hotels day in, day out.

We spoke about this disjoint at D3x and decided to do something about it.

Instead of adding another hot take to the internet, we packed our bags and took a road trip across Europe to sit down - in person - with hotel leaders that we genuinely admire. Operators, CXOs, and builders across different brands and market segments. No stage lights. No scripts. Just honest conversations about how they’re thinking about AI, what they’re testing, what they’re resisting, and what they’re quietly worried about.

That journey became a podcast.

The idea was simple: if AI is going to change hospitality, the most interesting insights won’t come from theory - they’ll come from operators making real trade-offs under real constraints. Budget pressure. Staffing shortages. Guest expectations. Legacy systems. Scale. That’s where AI either earns its place or quietly fails.

And today we’re releasing our first episode with Paolo Donà, CIO of Staycity Group, recorded at their newest location in Vienna to talk about how one of Europe’s leading aparthotel brands approached AI earlier than most - and why that decision wasn’t easy.

We’ve worked with Paolo over the past 2 years and this episode was a great chance to zoom out and explore bigger concepts around

• moving from pilot to production

• why experimentation alone rarely delivers value

• how leadership, ownership, and operational discipline determine success far more than technology choices.

Paolo shares candid lessons from deploying AI across a large, multi-market hotel group, including the trade-offs, internal resistance, and surprises that only appear at scale.

This episode sets the tone for the series: real conversations with hospitality leaders, recorded where the business actually happens. I hope you will enjoy this episode and follow our journey over the rest of the trip 😀

Very grateful that Paolo took the time to record this and was so candid with his experience and learnings. Thank you Paolo! On a personal note, after 14 years in hospitality, I’m so excited to be working on the frontier of what’s possible. Every day offers a new challenge that hasn’t been solved before. If you’re as excited as I am about the upcoming change, I’d love to connect. Feel free to grab some time on my calendar.

Listen on Spotify

Watch on Youtube

AI is transforming hospitality faster than ever before. Since ChatGPT debuted in late 2022, billions have poured into AI, and hotels that leverage this technology early will stay ahead. As a founder deeply embedded in hotel AI automation, here's a concise, actionable state of how visionary hotels are harnessing AI today.

Humans

Phase 1 - 2023

Phase 2 - 2024

Phase 3 - 2025

We’re at a stage where people are beginning to accept that chatGPT is here to stay. That’s not to say that we’ll all move at the same speed. There are broadly 6 stages for adoption of a disruptive technology and we’re getting to the stage where AI is crossing the chasm for the hotel industry.

Technology

This is much easier to track than human behaviour. OpenAI simplified this for us by defining 5 steps on the path to AGI (artificial general intelligence where AI > human).

• Step 1 - conversational AI has been employed in chatbots across hotel websites and messaging automation for SMS / Whatsapp. Older generation tech companies had built in-house conversational models which have largely become obsolete due to LLM technology.

• Step 2 - reasoners. Incredibly helpful for individual contribution and a partner to help you walk through the steps necessary to solve problems. Reasoning improves accuracy and fights back against hallucinations. Limited use across the organization.

• Step 3 - AUTONOMOUS AGENTS ← WE ARE HERE

• Step 4 - innovators. Think scientific progress, discovering a new law of mathematics, etc.

• Step 5 - organizational AI. Can an AI manage a score of agents to orchestrate actions across an organization?

Before we dive in, there are 2 megatrends to bear in mind

Mega Trends

1. Cost of AI is dropping 10x every 12 months

This means that AI can be used for previously considered frivolous tasks / tasks that humans could not and would not do. Imagine calling every guest 24 hours before check-in and asking if they would like to personalize their stay - baby bed, birthday, quiet room, gluten free, etc.

2. No current limits to AI intelligence

But..but..but hallucinations? Erase this from your memory.

AI isn't hitting intelligence limits anytime soon. Longer thinking times and increased training data continuously boost AI accuracy and capability. This emerging behaviour allows the AI to become more self-aware and hence more accurate with its output.

Current State - Autonomous AI Agents

"Agents" emerge as AI systems capable of operating autonomously for extended periods. These advanced models can spend several days acting on a user's behalf, taking on complex tasks, making decisions, and adapting to changing circumstances without constant human oversight.

Read more

At this stage I’d like to divide agents into 2 categories that would deeply impact the hospitality industry

1. Creative (consumer) agents - find me a hotel room in Stockholm with the best sauna. Lots of implications here for hotel discovery + distribution. Don’t sleep on this. It’s likely that first movers will have a momentary advantage.

2. Agentic workflows (for hotel operators) - get some work done for me following a well defined set of guidelines. I’d like to double click on this topic because it’s where I’m spending most of my time.

Agentic workflows

Most of us think of AI as conversational. Reply to a guest message. Help me draft an email. Use data from my knowledge base and don’t make stuff up. Valuable but still surface level automation.

AI agents take this to a whole new level of performance by connecting to the underlying technology (PMS, housekeeping + maintenance tickets, CRM, etc).

Here’s a good visualization of the level of sophistication of AI agents

Automating Tasks

At D3x, we’re increasing the number of tasks that we can execute at step 2 of this journey and slowly making our way towards complete Workflow automation.

Some of the tasks we already automate at D3x include:

1. Housekeeping - “I need a towel”. We need to figure out, who’s I? Which room are they in? Is towel an in the housekeeping system. And then construct an API query to hit the housekeeping system with the towel request and then convert the API response into “tone of voice” response to the guest.

2. Booking Confirmation - “I didn’t get an email - is my booking confirmed?”. As simple as this may seem, this question needs authentication. Is the person messaging the AI allowed to access reservation information. Once authentication is complete (last name, arrival date, res ID), the AI would then be able to reply using realtime reservation information retrieved from the PMS.

3. Upsell - “Can I check-in early?”. Here’s where a reservation might need to be modified to include a charge to the customer one the price has been fetched and confirmed with the guest. The same principle would apply to parking, late checkout and something as random as an island tour.

4. Maintenance - “the air-conditioning doesn’t work”. Here’s where the AI needs to attempt to assist the guest with self-service - did you close the door? is the key card in the holder? If that doesn’t work, a ticket needs to be logged in the maintenance system and assigned to the relevant department.

On our roadmap includes tasks such as handling lost and found requests, group booking funnel + table reservations for the in-house restaurant.

Workflow Automation

The next step beyond handling basic tasks would be where agents can just take care of tasks by themselves. Imagine that every single guest phone call asking for their invoice to include their company name could be automatically handled by an AI workflow running in the background. No need for wait for the reservation department or for the finance team to get in at 9am on Monday. Hand it over to the AI and forget about it!

The holy grail of workflow automation would be booking modifications. This would involve a series of checks and operations for numerous scenarios

• I need to move my room

• Will be arriving one day late or checking out a day early

• What if the rate plan doesn’t have availability?

• Can I get another room for my friend?

The hospitality industry is at a tipping point because from a technical standpoint, the road ahead of us looks pretty clear. Managing humans for change is where the challenge lies.

Hotels embracing autonomous AI agents today will not only streamline operations and elevate guest experiences—they'll lead the charge into the future. As technology continues to evolve at lightning speed, staying informed and proactive isn't just smart business—it's essential survival. The question isn't whether your hotel will adopt AI automation, but how soon you’ll start.

What can D3x do for you today:

1. Address every guest request instantly - anytime, in any language - available for SMS, WhatsApp, Phone, Email, Instagram, Facebook, Website Chatbot

2. Automate repetitive tasks such as booking confirmations, housekeeping or maintenance requests overnight

3. Augment revenue by tapping into conversational commerce through smart upsells

Are you ready to transform your hotel's operations and step into the future?

Book a Call

Reach out if you’d like to learn more about automating your hotel operations.

In startup-land, there’s a famous saying - if your website has a favicon (small image displayed next to the page title in the browser tab) at launch, then you waited too long to launch.

Having been around the block a few times, we skipped the bit that required us to waste time and energy on vanity design such as favicons and pretended that marketing didn’t exist.

The year that was

In 2023 we

1. Spoke to more than 100 hospitality operators, seeking to understand their business and figure out how AI could help augment their operations.

2. Launched our product and onboarded ~200 properties

3. Built 15 certified integrations(!!!) with messaging tools, email clients, property management systems and helpdesk software

4. Processed >5,500 guest conversations with our AI agent

5. Kept our heads down and chipped away at the problem

So what’s the problem?

Consider 3 personas — the operator, the manager and the executive. If we were in a jungle hacking away at the trees trying to make our way through to the other side, it’s the operator who sharpens the machete and hacks through the vines while keeping a wary eye out for snakes. The manager taps impatiently on a watch and says that at this speed we’ll run out of food before we get through the jungle implying that the operator has to move faster and take fewer smoke breaks. Meanwhile, the executive climbs up a tree and yells "Wrong jungle!"

And that’s our jungle. Having operated hospitality businesses for 8 years, the visceral pain of the 3rd party commission is etched in our subconscious mind. Our mission is to be an antidote to that poison. Our goal, to arm David with a slingshot to fight the good fight against Goliath.

Fortunately for operators, our slingshot got a MEGA upgrade when OpenAI released GPT4.

AI + Travel

Most of the operators we’re speaking to are encountering genAI for the first time. There are mixed emotions. Some expect magic - a superhuman intelligence that understands their world. Others are skeptical of Silicon Valley’s hype-fuelled marketing and dismiss AI advancements without consideration. Few others ask themselves whether implementing AI might come at the cost of unemployment in an industry whose growth has largely been fueled by human capital.

Regardless of where you stand, one thing is for certain. People want to travel. More than ever before. And AI is not going to replace that urge to see the world nor can it provide a worthwhile substitute for a soft bed and a comfy pillow. The fundamentals are secure.

However, hospitality is also a dog eat dog world where competitive advantage changes with the wind and barriers to entry are at best flimsy. Once the basics have been taken care of (room, wifi, cleanliness, security, etc.) the only differentiator is the experience. The feeling that remains with the guest long after they check out. The experience is what brings them back and converts strangers into die-hard fanatics of your brand.

Enter D3x

An omni-channel, multi-lingual, ever-vigilant AI agent responding patiently to guest queries and personalizing responses to deliver an experience aligned tightly with your brand.

We’re deploying AI to

1. Set website chat widget on auto-pilot

2. Automate Booking.com guest messages

3. Channel queries from Google search + Google maps to your booking engine

4. Draft responses to guest emails with 1-click (gmail, Outlook, Zendesk, Freshdesk)

5. Provide staff with access to AI-knowledge base via Whatsapp, Slack

The unifying theme of all these features is to utilize AI to save your team’s time while responding to guests instantly and encouraging them to book direct. Our north star is a world where we can increase direct bookings by 3x —> D3x.

We’ve spent some time documenting our value proposition and capabilities in a fun, easy to consume, website so please head over if you’d like to check it out. And if you’d like to talk about how AI could help turbo charge your guest experience, please drop me at note at jason@d3x.ai.

AI has taken the world by storm and it’s here to stay.

Most of my twitter and LinkedIn feed is full of technological mumbo jumbo, doomsday predictions or euphoria for the impending productivity gains. I do partake in a reasonable amount of click bait, because I like to keep myself up to date. Here’s my analysis of where things stand at the moment. I hope this will help you navigate the challenges in your business as you plan for the future.

Grab a coffee and let’s dive in.

The Current State of AI

Technology

Let’s start off with the technology. Anyone who has spent a few minutes with chatGPT knows that it’s a big deal. Here are 5 technical terms you should be aware of

1. LLM - large language model. Text question, text answer. This is the base innovation that has sparked the entire uproar. It’s an AI system that can respond like a human.

2. Vectorized databases - AI models work with numbers representing probability. If you were to look inside a model you’d see different weights like z1=0.1673, z2=0.9775. Vectorized databases store such numbers which don’t mean much to humans.

3. Function calls - convert a conversation into an API call. Unthinkable, 6 months ago. Magic? Definitely.

4. Code interpreter - Throw in a huge csv file and query the file instantly. chatGPT writes Python code for you and makes the data sing. Pivot tables and reports as we know it are dead.

5. Models - chatGPT (OpenAI) is the frontrunner for blazing to 100m users in 2 months but there are numerous other emerging models. Llama2, Cohere, Claude, etc. These are LLMs. Other AI models focus on other tasks, Dall E2, Midjourney, Stable Diffusion for images, InflectionAI as a personal psychologist, etc.

Coming soon - Gemini by Google. Allegedly allows users to combine text queries with images, graph interpretations, etc. All eyes on this launch.

Social + Economic Implications

AI will become a commodity like AWS. Sure, there will be differences but the competition will likely benefit you, the end user.

What’s important to note though is that AI will be drastically cheaper than hiring a human. And that’s terrifying but realistic. Jobs will disappear and new jobs will get created. The past is littered with people who have predicted the downfall of civilization.

It’s unlikely that your business demand will be impacted because people will always need physical services like a comfortable bed for the night, a freshly brewed beverage, etc. However, costs are about to reduce drastically.

Legal

There will be legal troubles for sure. Politicians are motivated to seize the narrative to retain power. OpenAI and other market leaders are motivated to hype AI-fear for regulatory capture - so that they can remain the anointed ones protecting us from evil AI variants.

Ultimately, fighting against technological progress is a losing battle. Imagine fighting against electricity, telephones or the internet.

This is an arms race. Once an organization (or country) deploys AI and gains superpowers, competing organizations (or countries) are forced to do the same. You cannot afford to think that laws (if and when enforced) will protect you and your business. Do not concern yourself with how the LLM was trained. The genie is out of the bottle. The time for your business to act is now.

So What?

What this means is that you’ll be able to drive more revenue with less money and time.

The holy grail.

How?

1. Convert inbound customer inquiries into bookings - not to mention instant, 24/7, multi-lingual responses

2. Internal tooling to turbo-charge productivity for social media posts, product descriptions, photos, etc.

3. Automated / assisted support to free up team’s time and improve guest satisfaction

4. ChatUI powered software interfaces that requires zero training

5. Custom reports generated instantly on demand (is this end of manual account reconciliation? 😰)

6. Predictive analytics telling you where your business needs to improve

For example

• Hotels - AI isn’t going to replace housekeeping but it definitely can help automate guest messaging + concierge, ultimately freeing up staff time and providing assistance to guests with the following

  • Instant

  • 24/7

  • Multi-lingual

  • Personalized

• Experiences - AI can’t take people skydiving. But it can help drive bookings while you’re 10,000 feet in the air. Customers don’t have to wait for you to respond but can chat with an agent that has been trained on your historical messages, rates, reservations, availability, mimics your brand tone and even your voice 🤯

• Online marketplaces - sales / support agents are expensive and slow. Agents cost between $15-60 per hour and the average first response time is 11mins. In that time, customers have already moved to their 10th browser tab and have booked with a competitor. Human agents should be spending their time on resolving hairy issues.

• Travel - have you ever called an airline to reschedule a flight? ‘nuff said..🤣🤣

Putting AI to Work For You

Step 1 - Define your objective

You know your business the best so you should be in a position to understand the place to get started. Broadly speaking, there would be 3 possible areas to evaluate

Sales

• Search and discoverability - how can you better assist customers and match them to the right product?

• Booking funnel - can you simplify the booking process by understanding implicit information? (obviously I’m traveling with my kids - I’ve booked this 17 times!!)

Delivery

• Servicing customer requests - omni-channel customer communication delivered with the right context

• Guest experience - delivering more than just a service. Leveraging your data to provide a memorable experience

Back office operations

• Team productivity - stop doing busy work and work on things that matter

• Automation - get rid of cumbersome manual processes

Step 2 - Data

Now that we have a chatty AI (chatGPT), it’s utility will only be as good as the underlying data. There are four types of data that every organization deals with

• Online static information - business description, location, phone number

• Gated static information - historical communications, SOPs, recommendations

• Online dynamic information - rates, availability, reviews

• Gated dynamic information - reservations, customer preferences, promotions

LLMs currently have access only to Online Static Information. You should be very careful about keeping your gated information private. This is your edge.

Step 3 - Generalist Chatbot for Sales & Support

Every single organization should be deploying an online AI chatbot for 2 reasons

1. Forcing function to gather your data in one place to train a model

2. Low cost method of collecting user input and feedback (customers will figure it out or call you if urgent)

The long term implications are huge though. You would be on your way toward understanding and developing an AI strategy.

Step 4 - Expand

Once you have a working model, you can then think about expanding the scope of your project with the following questions

• Revisit your big picture goal(s)

• Can you connect your base model to new channels (Facebook, Email, Whatsapp, Zendesk, Twilio, etc.)?

• What data + APIs does the AI model need to level up it’s capabilities? Can you feed in historical messages to improve responses.

• Is it time to plug in dynamic data (rates, availability, reservations)?

• Is there any tooling out there that can help you achieve your objective? No prizes for reinventing the wheel.

• How can you break up the work into smaller pieces and iterate?

Your AI Journey

1. Acknowledge the elephant in the room

2. Define an objective that AI can help you with

3. Take stock of your data

4. Train a base model for your business

5. Apply it to a simple use case (generalist chatbot for sales / support)

6. Monitor customer interactions

7. Process feedback and retrain

8. Ingest additional data (historical messages)

9. Connect to new channels

10. Expand functionality using APIs and dynamic data

Other resources

• Skift AI travel newsletter - weekly newsletter capturing latest news

• Everything AI in travel - new publication from Tony Carne

• Michael Parekh - more technically oriented AI news

That’s the trick with AI - apply it at the right places for best results. Apply it poorly and the “garbage in, garbage out” rule kicks in. Another dimension especially relevant to the travel, experience & hospitality industry is that it will never be able to replace a friendly smile, a thoughtful gesture or a freshly made bed.

At akin, we’re building an AI agent that can free up operator’s time by providing timely, contextual, multi-lingual responses while guiding customers towards making a booking.

Enough about us, let’s dive in.

Addiction

Customer acquisition has been high on a drug for the past 10 years - Google Ads.

Expedia and Booking together coughed up $7.5 billion in 2022. It’s generally thought that Booking.com might be Google’s largest customer.

With a drug this big, the downstream implications are significant. Most companies have the following

• People - Highly specialized operators adept at pouring money into the Google engine and playing the adwords game

• Software - Specialized tooling and funnels designed to monitor performance and optimize for clicks

• Habit - Processes around incentivization, training, content creation, A/B testing and numerous other functions all in service of Google ads driven monetization

Together, they lock incumbents into a mindset of straightening deck chairs on the Titanic. From Kodak to Nokia to Xerox, history is littered with giants stumbling during periods of technological transformation.

AI rocks the boat

Over the past 6 months, the world has come to realize that AI has come of age. Google is scrambling to adapt and OpenAI (chatGPT) has taken the lead in what looks likely to be a step function change in how the online world works. Function calls, Llama2, 32k context, AutoGPT and numerous other innovations being released every second week making it quite hard to separate the signal from the noise.

Which of these innovations are relevant to our industry?

Let’s start by breaking down travel requests into their core components and evaluating the impact of AI on each piece

1. Search and discoverability

LLMs (large language models - commonly referred to as AI) have digested large volumes of data available on the web and are better suited to answering the question above than Google. Marketplaces are currently scrambling to incorporate AI-search into their offering. Meta-search would always be more valuable to the customer and because it’s not feasible for one marketplace to have all encompassing information. A meta-tool like chatGPT or Google (AI) would be infinitely more knowledgeable. Brand-related loyalty and habitual behavior (Airbnb + Booking) might offer some defensibility to marketplaces for a while, but customers are ruthlessly shopping around for better prices and this will not last forever.

Winner - Customer

2. Rates and availability (API)

This information changes every second (increasingly generated by pricing AI) and cannot be memorized by LLMs (chatGPT). So an API to real world information is necessary. Assuming the AI exists to help the customer, it follows that AI would choose the cheapest price to book. And if that is true AND operators are able to connect their price engines to AI engines, it could very well be game over for the middleman — Booking.com, Expedia, etc. But don’t expect them to go down without a fight. The game will quickly evolve into rewards, promotions, discounts, hidden fees, non-refundable rates, etc.

Winner - Customer

3. Product Information

Price alone isn’t a deciding factor. Attributes such as proximity to the beach or wifi speed could be important to the customer. There are two sources of product information

1. Travel Operator - Real world information that changes all the time. Much of it is offline but relevant (Room 101 overlooks the pool). Some information takes time to show up in the online sphere (if at all).

2. Reviews / blogs - multiple 3rd party sources would be more believable on subjective questions such as cleanliness, friendliness, etc.

Will AI be legally allowed to live-scrape marketplace reviews? What if the product doesn’t match online promises? How would customers get insured against misrepresentations? How will chargebacks be handled if the AI hallucinated?

AI will be able to crunch multi-variate information quickly and will be able to match customers with their desired preferences. Traditionally marketplaces have charged a premium for this matching function and as AI becomes ubiquitous, marketplace matching wouldn’t be a sufficient differentiator. However, there are lots of moving parts here.

Winner - Operator

4. Historical booking preferences

Customers have certain implicit preferences that might not be apparent to them or that they might not explicitly call out. In this case, booking history + customer reviews (across multiple trips) becomes a huge decider in finding the right option on a subsequent trip. Currently marketplaces have a good overview of customer behavior and are well poised to provide the best recommendations assuming customer behavior hasn’t changed (having a kid drastically alters travel preferences). Switching costs would be quite high.

Winner - Marketplace (Airbnb, Expedia, Booking.com)

5. Offline customer preferences

Online booking behavior is only the tip of the iceberg. The real magic happens when operators deliver the booked experience. Guests might cancel, extend, request for add-ons and reveal a multitude of preferences that were previously unknown. Can hospitality operators capture this data and then use it to lure back customers when they’re ready to book again? Loyalty programs, upgrades, promotions, discounts would fall here.

Winner - Operator

The Bottom Line

Customers

It should come as no surprise that the winner in all of this is the customer. AI will be a commodity and all the surplus of AI related economic gains will go to the customer. What that means in the travel context is that customers will be able to book better holidays for cheaper. Better as in better suited to the guest’s needs and expectations. And AI will not play tricks to get people to pay a higher price for the same offering.

Marketplaces

The creation of Google Adwords coincided with the emergence of Booking.com as a superpower who were relentless with A/B testing and funnel optimization. A step change in the technology underpinning search could result in a few winners and losers. Any bets?

Search

Is Google going to remain undisputed? Many observers have likened this technological revolution to the browser wars of the early 90s. Microsoft won against Netscape because they could package Internet Explorer with Windows. Will Google be able to pull off the same trick? User habits (“let me Google that”) are notoriously difficult to break. On the other hand, Google is struggling to get started on the AI game. Will this fumble result in their demise or is the upcoming Gemini AI release going to save them?

Operators

Whether it’s transportation, accommodations or experiences, travel operators have an opportunity to fight back for their fair share of direct bookings. And the key decider will be data. Can they get the act together and collect meaningful offline data, coupled with targeted promotions to lure AI agents into making direct bookings?

Bring out the popcorn folks. This is going to be turmultuous and wildly entertaining. 

Nobody, not even AI, can see where the dice are going to land. I, for one, am very excited about where this road leads us because maybe the golden age of experiences, hospitality and travel lies ahead of us and not behind.