The Game-Changing Influence of AI on the Hotel Tech Ecosystem An (almost) comprehensive guide to all possible use cases of AI applications in the hospitality industry Ira Vouk | March 2024
Hotel Tech Ecosystem by Ira Vouk. A High-resolution PDF of this map can be downloaded here: https://iravouk.com/hoteltechmap/.
You may have seen this diagram that recently went viral on the internet. It represents a comprehensive, yet user-friendly outline of our Hotel Technology Ecosystem that I crafted after dissecting numerous maps of hotel tech from various sources for many years. Think of it as my contribution to modern cartography – mapping out the wild territory of our current tech space by arranging existing tools into color-coded categories while also placing them on the spectrum of guest-facing vs back-office tools. This is the first in the industry map of hotel technology that is actually easy to read and is self-explanatory, which is the main reason why it has become so widely adopted.
When I first unleashed it on the world of hospitality, I was flooded with feedback and questions. One burning query stood out: “So, where is AI in this picture?” And my answer was: “Everywhere…”
AI cannot be viewed as just yet another category of software or hardware solutions, but rather, it's technology that is weaved in (or will be, sooner than you think) all categories of products depicted on that map. It's a game-changer, a turbo boost for innovation that increases every single vendor’s potential to build better and smarter products with more efficiency and higher profitability. The same goes for the end users of these technology solutions – they become more empowered to deliver better customer service and improve operating efficiencies and profitability levels through the use of these emerging technologies.
Sure, some skeptics argue that our industry is still fumbling in the dark ages of AI adoption, so how can we possibly say that all categories of tech are already affected by it? And they're not entirely wrong. Hospitality (and Travel in general) is way behind other industries when it comes to technology adoption and digitization, let alone the penetration of AI. There have been a few studies supporting this, including the recent one by Accenture, “The art of AI maturity”.
However, I can also easily prove that every single technology solution has already been affected by one form of AI or another, by asking you (yes, you) this question: do you, personally, use AI in your everyday life? 100 percent of the readers should say yes. Did you use the face recognition option to unlock your phone when you woke up in the morning? Have you ever asked Siri for a score in the latest football game? Have you used ChatGPT to help you write a letter to your boss? Did I use Grammarly to fix my English when working on this article? (nobody will ever know)
AI is everywhere, and employees of tech companies are the same people like you and me (and arguably, much more technologically advanced), so they all use a wide range of AI tools on a daily basis, including productivity applications and GenAI tools that help them code – better, faster and will less bugs.
So on a larger, philosophical level, almost every single human on Earth has already been affected (infected?) by the AI bug, which obviously doesn’t exclude developers of hotel tech software, as special as they appear.
But let’s move from a philosophical aspect of our discussion to a more concrete explanation of how AI applies to our industry.
There are different forms of AI (surprise!). But as of right now, the world of AI (at least in human minds) seems to have split between Generative AI and “everything else”.
Generative AI, which has been rapidly unfolding in recent years, is just one type of AI that generates something new (hence the name) mainly in the form of a language output or an image. But AI as a concept has existed for multiple decades. For example, our team of engineers incorporated a sophisticated AI/ML neural networks algorithm into an RMS that I co-founded in 2011 (yes, over a decade ago). It was a full-blown best-in-class AI algo, as fancy as it gets, with all the bells and whistles. However, only in the last 2 years did our industry actually start paying real attention to the concept of AI and, more importantly, truly incorporating it into our daily workflows.
And the reason for that… is ChatGPT.
ChatGPT is the most well-known representative of GenAI category (which largely consists of LMMs and image-generating tools, along with some other less popular types). According to Writerbuddy, ChatGPT is the most visited AI tool by far, leading (as of August 2023) with 14 billion visits, making up over 60% of the analyzed traffic.
Imagine that: the hype around AI is caused by the release of a single tool, followed by a chain reaction that changed our lives.
Despite this huge spike in the popularity of AI in the recent 2 years thanks to ChatGPT and its companions (which we’re eternally grateful for) the world of Artificial Intelligence doesn’t end there.
Other types of AI that have existed for a very long time have mainly been revolving around data processing, which is the reason why they haven't drawn as much attention from the general public. Because data processing is not as sexy as pictures of other universes or a romantic poem written by a robot as you watch it type. But these number-crunching guys have been holding down the fort long before it was cool.
The reason for this unprecedented popularity of GenAI tools is that it's much more adaptable to our daily lives. We can come up with thousands of applications for these technologies that make us more productive or, simply, entertained: from coming up with bedtime stories for our kids to populating customized images on the fly for that presentation we're putting together for our boss (by the way, these days you can use AI to build your entire PowerPoint from scratch… don’t tell your boss).
So how to differentiate between different types of AI and understand how they're used in travel and hospitality? This may seem confusing at first but is actually not rocket science.
There are 3 ways AI can be (and has been) adapted in our industry:
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Homegrown AI Algorithms. These are AI tools internally developed by technology providers that allow their tools to function in a more efficient manner and (hopefully) deliver better results. Think RMS forecasting algorithms. Those companies were probably the first to adopt AI widely and intelligently. They've been at it for over a decade, perfecting their craft while the rest of us were still figuring out how to use emojis.
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Third-party AI services and tools offered by cloud technology providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and IBM Cloud to leverage their cloud computing infrastructure. Their cloud services come with a pre-built comprehensive suite of AI products, including tools for building, training, and deploying machine learning models. Those are tools that technology providers (or IT departments of large hospitality companies) can utilize to manage their data and draw insights from large datasets. These algorithms are often more sophisticated and reliable than the ones that are internally built from scratch by hotel companies or tech startups, simply because a company like Google can afford better engineers who specialize in this sort of thing. Who needs an in-house AI team when you can just outsource to the tech titans? It's like having Gordon Ramsay cook your dinner.
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Off-the-shelf AI tools, which often come in the form of a finished product (with a face, not just the brain as in the previous 2 examples). And this includes the last wave of AI tools – GenAI, the cool kids on the block. The main differentiating factor of these guys is that you actually DO NOT need to be a developer or an IT person to incorporate these tools into your operations and workflows. They come pre-packaged, ready to rock and roll straight out of the box – just plug and play. Even if you want to hook it up on the backend through API into your existing technology – no coding is often required and it can be pretty straightforward. This can be done either by a tech vendor (when they incorporate these into their existing suite of products) but also by a hotel company directly (when they incorporate these into their existing tech or operational workflows).
And that is THE main reason why these tools are sprouting up like mushrooms after a rainy day. Anyone with a laptop and a dream can whip up an app powered by ChatGPT brains. And if you don't know how to do it – guess what... You ask ChatGPT and it will explain. It's the democratization of AI, and we're all just along for the ride.
So, how do you know what type of AI is right for you? Simple: when a tech vendor tells you their tool is powered by AI, don't just nod and smile. Ask the real questions: "What type of AI do you incorporate into your logic? How exactly does it work? And please describe the use case(s) where AI makes your product better".
And then, based on their answer, you decide whether that specific use case makes sense for your company and whether there's any ROI potential. You may be surprised to discover that in many cases, AI powers the aspect of their functionality that is not even relevant to the way you manage your business, or it’s a small add-on that you weren’t even planning to buy.
Now, let’s move from a general discussion to more concrete examples of applications of AI in our industry, which is the main purpose of this article.
Applications of AI in various categories of hotel technology
Let’s review the categories on the map above to understand how exactly Artificial Intelligence has been adopted in different parts of our tech ecosystem and how it’s affecting the evolution of our industry.
On the map, you see technology solutions organized in 5 different categories: Guest Experience, Revenue Management / Brainy Insights, Operations, Marketing/Sales, and Distribution. The tools that fall under these categories are color-coded for your tech-challenged convenience, according to the color of the category.
When writing this article, I conducted an industry study by reaching out to hospitality tech vendors to understand what categories have been affected by AI the most. I received an overwhelming amount of responses with many AI use cases that I never knew existed. It was like opening Pandora's box. As you read through the article, you will find some applications that are pretty obvious and intuitive, while others are much more subtle, creative and, in my opinion, most exciting. And I’m sure there are more hidden gems out there that didn’t make it on these pages, hence the “almost comprehensive” disclaimer in the title of the article. Speaking of evolution, let me tell you. Since I wrote my book “Hospitality 2.0” just 2 years ago, the number of AI applications has expanded tremendously. I had a much shorter list in my AI-dedicated chapter then. And if you haven't read it yet, well, let's just say you're missing out on a literary masterpiece. No pressure though, just saying.
The transformation our industry has undergone in just two years is truly astonishing!
Let’s start with the Guest Experience category, as it has probably been affected the most, in my humble opinion.
Guest Experience
Chatbots. Okay, this is a no-brainer. According to the latest Skift report, Generative AI’s Impact on Travel, Customer Service Chatbots represent one of the most prominent use cases for generative AI and large language models in our industry. The main reason: the type of conversation with an inquiring customer aligns perfectly with the capabilities of an LLM. So for the providers of customer service bots it was a very logical step in their evolution. AI technology is extremely effective for direct messaging and online chat services. These guys can respond to your queries faster than you can say "What time is checkout?" These types of response times are almost impossible to maintain with human-to-human interaction. Plus, AI bots never get tired, never need a coffee break, and never accidentally send you cat videos instead of directions to your hotel. A couple real-life examples of vendors offering these products:
Runnr.ai developed an AI-based tool to automate guest conversation with various functionalities.
Lacoly provides guest communication and guest management through WhatsApp, also using AI.
AI-enabled devices for in-person customer service These are available in a variety of different forms – the most visible are the robotic butlers, concierges, and luggage handlers. The cutest example of this was an AI robot called ‘Connie’, which was adopted by Hilton back in 2016 for some time. Connie could understand conversational questions, speak responses, and use body language like pointing to give directions. Most impressively, it was able to learn from human speech and adapt to individuals. This was one of the early examples of conversational AI applications. You can think of it as ChatGPT’s older brother who actually had a body. These days, you can see more of these examples in our industry, like delivery robots, luggage handlers, etc.
Mobile and voice-activated assistants Think Google Home devices or Alexa by Amazon – something like that, in any shape or form, placed in hotel rooms (or anywhere on premises for that matter). They're like the ultimate travel companions, ready to answer your burning questions with just a voice command, who never judge your questionable taste in vacation destinations. These don’t necessarily have a body. They can be floating in space, accompanying Siri and the like, accessed by a mobile app.
As an example, Bookline.ai introduced Voice AI Agents for Hotel Reservations. Crafted using well-known reservation management techniques, those are typically designed to boost direct net sales for hotels. In response to the widespread talent shortage and staffing issues, this technology offers a promising value proposition. Tenyx, another emerging startup, offers a similar product.
Now, as you may have noticed, the above examples mainly revolve around Generative AI. But as you now know, because you’ve been paying attention, the world of AI is much richer than that, so we’ll talk about other forms of Artificial Intelligence that expand past GenAI. They might not be as catchy but, arguably, are much more effective in many cases.
Operations AI isn't just about making guests happy – it's also about keeping your employees sane. Robust hotel software systems with AI at the core can automate all repetitive operations like check-ins and check-outs, housekeeping deliveries, room assignments, and the like. In combination with the chatbots mentioned above and powerful analytics tools, hotels are able to minimize response times, reduce costs, and ultimately increase revenue through the use of AI. How? Let’s review some use cases.
Employee Productivity There are various examples of off-the-shelf AI-based productivity tools (including, but definitely not limited to, ChatGPT) that can, and should, be used by employees of any organization. We won’t spend time on these obvious examples. Let’s dig into something less intuitive but not less exciting.
Aphy, for example, introduced cloud-based digital workers that automate operations 24/7. One of their interesting AI use cases is an email labeler that monitors an inbox at the hotel, adds labels according to the content, and sorts them by urgency. The best part is that they also combine it with process automation to trigger robots to do things like checking the systems for rates and availability, creating bookings, sending invoices, etc.
Configuration and implementation This is an interesting one. AI helps significantly cut down configuration times for implementations of all kinds of technology. This improves operating efficiencies for hotels as it saves a lot of time for the employees, which ultimately has a very positive effect on technology adoption. For example, IDeaS uses AI to pre-configure the application so all the hotel client has to do is review and approve all the fields instead of configuring it themselves.
Workforce Optimization AI helps in scheduling staff more efficiently, ensuring that manpower is aligned with demand and other business requirements. Zira.ai is an example of an industry tech vendor offering this functionality. It is aimed to improve retention and performance and save on labor costs by automating many repetitive tasks. It can optimize schedules for compliance, cost, custom rules, etc. Improving team communication is also part of the offerings of such platforms.
Predictive Maintenance Datategy is an example of a company that utilizes AI to predict and schedule maintenance that prevents equipment failures and extends its lifespan, reducing operational disruptions. It's like having a crystal ball that tells you when your toaster is about to go on strike.
Accounts Payable Yes, even accountants can benefit from AI. For example, Reeco developed a machine learning model that learns your GL coding patterns and maps your GL accounts to the right inventory items when filing your invoices. So instead of your team spending hours manually going over invoices with a ruler to mark down the GL code for each product, and then spending days inputting all the data into their accounting system, now you are able to upload your invoices in one place – and then sit back, relax and let AI work its magic. They claim to reduce invoice processing time by 84%.
Procurement/Purchasing Same company, Reeco offers a purchasing platform that intelligently optimizes the buyer’s basket during the purchasing process by searching for alternative products or suppliers, to reach the highest level of savings.
Food Waste Winnow Solutions has developed an AI-based commercial food waste management analytical platform that helps to cut costs and decrease environmental impact.
Revenue Management / BI This is my favorite part because I’m a real nerd and I’ve got a soft spot for spreadsheets and a deep appreciation for the beauty of a well-optimized algorithm.
As you may be aware, where AI has been utilized widely and consistently within the hospitality industry is data analysis. I know, this is not as exciting as cute robots but this is where true ROI is hiding. Because data is everything.
AI algorithms are best used to quickly sort through large amounts of data and draw important conclusions for optimal decision-making. Here are different ways of applying artificial intelligence in this category.
Revenue management and profit maximization In my opinion, this is the item that yields the highest ROI for hotel owners and operators. Because who doesn't love making more money without lifting a finger? RMSs are inherently using AI since their inception so it’s really nothing new for them.
When it comes to revenue and profit management, AI and ML make the most sense when applied for the purpose of forecasting (mainly demand forecasting but really anything you want to predict) and optimization (dynamic pricing and other decisions that influence revenue and bottom-line profit). AI-driven revenue management systems have an extraordinary ability to identify patterns and trends within ridiculously large amounts of data to inform all kinds of revenue management decisions.
PricingService.ai, for example, a newly emerging startup offers an AI-native Revenue Management platform that is coded from scratch using AI, ML and dynamic pricing techniques. What’s interesting about this company is that it’s a service, not a product. Meaning, there’s no UI for the user to administer or website to navigate. The prices are updated in the PMS system automatically via API.
On the other side of the spectrum, iDeaS, the behemoth of our industry, is continuing to expand the use of data sets to ingest into their 100+ forecasting models with AI.
Upselling and Cross-Selling AI identifies optimal opportunities to offer additional services or upgrades to guests, enhancing their experience and increasing revenue.
Oaky, for example, a hotel upselling software company, utilizes AI to enhance its product capabilities. They leverage AI to automate the upselling process throughout the guest journey in hotels.
Summaries and contextualizing The RMS gang has lately been experimenting with the adoption of GenAI as well.
The main use case for GenAI that makes sense in this domain is for LLM to narrate a story of how exactly the forecasting and optimization algorithm of a given RM system came up with a specific decision, or explain what the decision actually means. Those of you who have been paying attention to the development of modern Revenue Management technologies would know that while ML-based algorithms are smart and tend to be more effective than simpler regression models, their biggest disadvantage is the “black box” approach where neither the customer nor even the developers themselves would be able to tell you how they actually think and why they recommended $135 for that Non-Smoking King this Saturday instead of $149. We’re hoping that GenAI can help with that. Hence the use case for LLM models in this space.
GenAI can also help explain the results of the decision-making process to the user in an easy-to-understand text output or provide summaries of various datasets and visualizations. Because what good is all that data if you can't make sense of it?
While some RMS vendors are still struggling with adopting LLMs for this purpose, others have made significant progress in that direction.
Infinito Revenue Management Solutions claims to be the first LLM RMS. They have been doing AI summaries and contextualizing for a few years.
Lighthouse (formerly OTA Insight) recently released smart summaries, which are essentially automatically compiled emails that highlight relevant hotel performance trends on a weekly basis to various stakeholders. A caveat: this is not an RMS company, they offer market intelligence insights, which is still very relevant for this discipline.
myDataValue built an AI Revenue Assistant that promotes collaboration, saving revenue managers time and providing an intelligent partner for brainstorming, monitoring KPIs, and driving data-informed pricing. Their AI is trained on the property's internal and external data, allowing for in-depth analysis. This helps answer questions like 'Why is occupancy/ADR/revenue high/low in a particular period?'. Pretty cool.
Report generation The same company, myDataValue, is working on ChatGPT-based data analysis functionality which could be fed, for example, reservation data and generate things like an accrual basis report with a single prompt/question. Additionally, the tool automates daily, weekly, and monthly reports, for example, a pace report consolidated by different sources such as Direct, OTAs, Corporate, etc. in a structured form.
Data handling is a major use case for AI in this category. This is where AI really shines (the old-school non-GenAI). A few examples worth noting:
myDataValue has built an ML-supervised model to ensure a single source of truth and quality of data received from different sources. Their approach is aimed at consolidating different sources of data into a structured format to make hotel insights standardized and easily accessible. What I find very valuable in their solution is that once the property data is unified – it allows for attaching correct variable costs to each reservation in real time, depending on the reservation type. The idea is for the system to automatically match the transaction ledger with reservations to ensure a reliable single source of truth. This is something that our industry has been trying to solve for decades (unsuccessfully), which I wrote about in my “Hospitality 2.0” book a couple of years ago. And I’m very happy to see progress in this area.
Directful is a tool that was designed to transform big data into actionable insights resulting in increased direct bookings. They harness real data science to predict travel patterns around the world. Using hyper-personalization, their algorithms empower each hotel to take a set of steps to win more guests.
Quicktext. These guys developed an AI-based tool that allows you to merge all kinds of data points (up to 1900 as they claim), structure them, and distribute them in different directions, like instantly communicating this information to the guests, feeding it into the hotel's information sources (web, app, CMS, communication media) or external media (Google, Facebook, etc.).
FastSensor offers AI-backed customer behavior tracking for event and retail spaces in their hospitality environments.
Marketing / Sales This is a very fruitful territory for all things AI.
Analysis of customer reviews AI has been helping us analyze the large pool of information across a broad range of online sources and provide valuable insights into customer sentiments. These algorithms allow for deep sentiment analysis of all reviews in real time, determining positive and negative phrases. The mood-reading robots sift through online feedback faster than a caffeine-fueled intern on a Monday morning. This data can help gauge guest satisfaction and identify areas for improvement.
Skift also lists this as one of the use cases for GenAI that will have a significant impact on the travel industry. Guest feedback has a reputation of being a key performance indicator across the travel sector and online reviews are perceived to have substantial revenue impact.
This is not a new use case for AI as it’s been going on for years, but now this part of our tech stack is getting an unplanned makeover due to the recent developments in the GenAI category. An ecosystem of tech vendors has sprung up to make it easier for travel companies to not only analyze but also track, manage, and respond to guest feedback. Good software in this category prompts happy guests to leave positive reviews. But it also helps manage the fallout from negative posts.
For example, Zambello deployed an AI-driven reputation management tool that is capable of suggesting carefully worded responses to online reviews. The idea is that AI already knows what the guest liked or was upset about, so it generates an answer based on this specific feedback. The AI’s purpose is to optimize the review specifically for that guest, that market, and, what’s fascinating, all other people who are going to read this response in the future.
Content Generation It is well known that LLM tools like ChatGPT and others are often used to generate marketing content, including descriptions and promotional materials, tailored to engage specific customer segments (I use it myself all the time to promote my online learning courses).
Digital Marketing agencies like Matrix and others now offer AI-based content marketing services for Travel and Hospitality companies. That type of AI technology produces high-quality, SEO-optimized content.
Targeted Ad campaigns Another important application of AI in marketing is advertising. For many years AI has been used by companies in different industries to help serve consumers more relevant, targeted ads. As the algorithms keep advancing and richer consumer data becomes available, AI will continue to learn purchasing behaviors and deliver more relevant content for potential travelers.
An interesting example in this category is Quicktext. They built an AI-based chatbot but the exciting part of their value proposition is that the conversational data generated by the bot is segmented according to the following criteria: country, city, device used, date, and time of connection. Then another part of their tool records these criteria and generates multiple “personas”. These personas then allow advertising campaigns to be optimized in real time by personalizing them according to the previous analysis, which leads to an increased click-through rate.
Personalized offers Similar to the above use case, AI helps customize offers to a specific target audience, but not only in the form of ads. There is also personalization that happens in the booking engine itself that results in the right offer being displayed to the right customer on the property (or brand) website. Site bookings are known to be one of the friction points for the hospitality sector. AI-based functionality introduced into the hotel’s website reduces this friction, maximizes the sales potential, and provides a better booking experience.
Allora is an example of such a booking engine platform powered by AI. Developed by Avvio, a hotel technology provider, it uses learning models to analyze hotel booking data and optimize booking engines to cater to guest needs, resulting in increased direct bookings.
SEO Another common use case for GenAI. While there are typical applications like, for example, asking ChatGPT to generate a list of optimal keywords, we’re also seeing some creative solutions popping up.
Quicktext strikes again. They use data generated by their chatbot to automatically create relevant FAQs by language. These FAQs are then updated weekly and are integrated into the property website. This process enables a fresh flow of relevant structured content that is used by Google for indexing.
Distribution Hotel distribution is the process of making hotel inventory available to potential guests. It involves the communication of availability and rates (and also content) to different sales channels such as online travel agencies (OTAs), global distribution systems (GDS), direct hotel websites, wholesalers, tour operators, and other intermediaries. AI has been utilized to improve different parts of this process.
Optimized Content Distribution In hotel distribution, the accuracy and completeness of your descriptive information and photos across core points for online travel search can make or break a prospective guest’s decision to book your hotel. It directly correlates to the perceived value of your establishment; therefore, having an accurate representation of your property on all distribution channels is essential. And… there’s an AI for that.
HotelPORT offers an AI-powered content monitoring and audit solution called PropertyVIEW to help hotels ensure accurate and complete online content across distribution channels.
Parity Management Nothing ruins a good party like someone showing up with a cheaper ticket. AI-powered rate parity and price integrity solutions like RateGain's PARITY+ allow hotels to track rate violations, define strategies to minimize revenue loss, and communicate directly with hotels to improve parity.
AI-powered Search There are fundamentally two types of travel searches based on where the customer sits in the purchase funnel: dreaming/consideration searches and planning/transaction searches. According to Seth Borko at Skift, Transactional searches that take place while planning travel are likely the first part of the search industry to be impacted by AI. The biggest pain point for consumers at this step is complexity: a wide variety of options on a variety of booking websites. GenAI reps (Large Language Models specifically) have the potential to shine here. Their strong suit is synthesis, and so AIs can do a great job at sifting through the huge range of inventory that is available out there.
In fact, we have already seen the first ChatGPT integrations in the travel sector take place via travel distributors. ChatGPT announced plugins that allow its AI to access specialized datasets and up-to-the-moment information. Expedia and Kayak were both launch partners for OpenAI plugins. In a demo that Expedia shared, ChatGPT uses the plugin to provide flight itineraries, offer hotel and STR pricing, and suggest things to do while in the destination. All results include links to Expedia’s platform to complete the booking process. Conclusion As we wrap up this rollercoaster ride through the Hotel Technology Ecosystem, one thing becomes clear: Artificial Intelligence isn't just a buzzword; it's becoming the secret sauce of all things tech. From chatty chatbots to nerdy forecasting algorithms - AI is everywhere we look. In fact, it appears that AI is also where we didn’t even think to look.
Artificial Intelligence is the ginormous elephant dominating the room. And those companies who ignore its overwhelming presence might as well be wearing blindfolds at a dart tournament – it's a recipe for disaster.
In this article, I have done my best to provide a comprehensive list of applications of AI in our industry to give you an idea of various possible ways this new powerful concept can be utilized to improve hotel operations. But mark my words, by the time we have a panel discussion at the next HITEC conference on the same topic, the list of AI use cases will be twice as long. This space is evolving so rapidly – it blows my mind.
Let's raise a virtual toast to the future of our industry where AI takes the throne, turning mundane tasks into magic and making every guest feel like a VIP. Here's to the robots who deliver towels with a smile and the algorithms that keep our hotels generating steady cash. With AI by our side, the future of hospitality looks brighter than ever. And the only limit is our imagination - and maybe our Wi-Fi connection.
Thank you for reading. To download a high-resolution PDF of the Hotel Tech Ecosystem map, go to https://iravouk.com/hoteltechmap/. And as always, feel free to reach out on LinkedIn with any questions.
Ira Vouk https://www.linkedin.com/in/iravouk/
Ira Vouk is the author of industry best-sellers “Hospitality 2.0” and "Revenue Management Made Easy", a hospitality consultant and technology innovator recently recognized as "top 17 technology professionals inspiring innovation in the US hotel industry". She is also the originator of the first in the industry online learning course on hospitality technology, currently offered to large organizations all over the world.
Ira brings two decades of practical industry experience, predominantly championing the role of revenue management and the use of data and technology to provide hospitality companies with insight to lead their business strategy better.
Frequent speaker on the topics of hospitality technology, distribution, revenue management, profitability and automation (AAHOA, HEDNA, HITEC, ICHRIE).
HITEC Advisor @ HFTP, Strategic Advisor @ HTNG, Hospitality & Tourism Alliance Advisory Board Member @ The California State University, former Advisory board member at Cornell CHR @ School of Hotel Administration.
Adjunct professor at SDSU. Guest lecturer at UDEL, DU, SJSU, University of Angers (France), ESSEC Business School (France).