AI in Travel and Tourism: The Revolution Is Happening

The global pandemic significantly affected customer preferences and expectations. Social distancing is now strongly associated with massive digitalization in our private life and at work. In the meantime, the travel industry is rising from the ashes, trying to get to know this new type of customer.

In pursuit of their business goals, tourism companies create “a perfect service”, which often means implementing innovations in regular operations. What tool to use to remain competitive and gain back what was lost during lockdowns? Artificial intelligence (AI) has a lot to answer.

How exactly can algorithms help travel agencies and their clients, and what will change in the near future? This article reveals the potential of AI in the travel industry.

How AI Technologies Impact Travel and Tourism: Trends and Figures

Using innovations is a natural development stage of modern travel companies. Getting from point A to point B is no longer a luxury. The priority is given to tourism experiences, from buying tickets to checking out of the hotel. What role does the use of AI have in this ongoing process? Let us look at the stats.

• 82% of airlines globally are going to try out business intelligence in the upcoming years;
• In 2022, the usage of chatbots in branded and independent hotels is expected to grow by 42% and 64% respectively;

• According to a report provided by McKinsey & Company, modern AI analytics techniques are 128% more effective for the travel industry than traditional analytics methods. This is the highest rate compared to 18 other industries studied during the research;

• According to the same research, AI will likely bring the most value to the travel industry (around 400 billion USD) than to any other niche.

Trending AI-driven innovations in travel and hospitality

Artificial intelligence in the travel industry works even better when implemented with other state-of-the-art technologies, such as:

• Generative AI. Since the release of ChatGPT at the end of 2022, travel companies have been integrating it in their business operations. Generative AI is widely used for client support in travel planning, booking assistance, or troubleshooting. Travelers are positive towards these experiments: 48% of U.S. adults are interested in AI-powered smart assistants. Chi Software specializes in leveraging Generative AI consulting to enhance client support and operational efficiency across various industries, including travel. 
• IoT. Several interconnected devices located in one room can create a one-of-a-kind personalized service for hotel visitors. Plus, sensors store the visitor’s preferences in the database to help create well-targeted customer experiences and marketing campaigns in the travel industry.
• Virtual reality (VR) and augmented reality (AR). Traveling many miles has never been so easy. One can use virtual reality gadgets to ‘go’ to a place they consider visiting, and there is more. The first VR-based booking platform for the travel industry was introduced in 2017. Such solutions can also provide AI-based personalized recommendations or price predictions for the virtual world.
• Blockchain. This technology can help the travel industry by providing transparent payments, smart contract options, and data processing. AI algorithms, in their turn, greatly simplify the tracking of baggage or personal information.

Read also: How AI transforms mobile app development

AI in travel inspires entrepreneurs and software developers to innovate and restore tourism after a massive pandemic shock. The following examples of artificial intelligence in the travel and hospitality industry will give you an idea of ongoing transformations.

The Most Popular AI Use Cases in Travel and Tourism

You have probably come across several of these examples of AI in tourism but never paid much attention to their true value. It is time to examine them more closely.

1. Smart booking assistants (chatbots)

With modern online services, clients do not have to visit travel agencies to plan their trips. Technologies have gone even further: now customers do not have to talk to travel agents to make necessary arrangements. AI-powered chatbots have all questions answered.

They help book flights, accommodations, and even cars for rent. As a rule, these assistants are in-built into messengers or social media to make service for travelers more “natural-looking”.

Market example

Big market players, such as Booking.com or Skyscanner have been utilizing smart assistants for some time. The communication is simple but effective for users. They type in desired destination points, and chatbots provide all required details based on dynamic prices and availability.

2. Sentiment analysis

Every user leaves a unique online mark on social media. We post photos, share impressions, repost content, etc. We do it every day, and technologies are aware of our actions.

Using machine learning and natural language processing (NLP), companies from the travel industry get a complete overview of what people think about their service (or the services of others) in real time. Simply put, they analyze users’ sentiments on social media platforms or any other online resources.

Can you imagine tracking social media manually? Maybe, you or your employees have done it already, so you probably realize how much time and effort it takes. But using AI has changed everything.

Market example

You can find several ready-made solutions to analyze user reviews and, more importantly, conduct sentiment analysis in real time. IBM Watson offers Qualaroo, while HubSpot provides a dedicated customer service platform Service Hub.

4. Flight forecasting

Any person traveling by plane knows how hard it is booking a plane ticket at the lowest price. But what if AI in the travel industry does all the hard work? Innovative AI-driven apps help travelers find the most profitable deal and provide cost predictions.

Market example

Hopper is probably the most popular platform with flight booking and prediction features. Platform creators implemented sophisticated ML algorithms allowing a customer to book plane tickets and hotel rooms at the best price even a year ahead.

But that is not all. Hopper offers another AI-powered feature we already mentioned, which is personalized travel recommendations based on the customer’s search history. The app also informs users about the most attractive discounts via push notifications for travelers to quickly “hop” to the best deal.

5. Facial recognition

Facial recognition is another increasingly popular application of AI in the travel industry. As the name suggests, it helps identify a person by comparing their facial features with images available in the database.

Read also: How to build smarter apps with AI?

This use case of AI in tourism is already employed at airports, train stations, hotels, and other places, providing a customer with easy access to various facilities and saving their time. Going further, it also guarantees a high level of security for a particular business and its personnel.

Market example

It is not exactly a market example, but still, it demonstrates how using AI in tourism becomes a game-changer on all levels of decision-making. As of July 2022, the U.S. CBP (Customs and Border Protection) service used facial recognition at 32 airports for those traveling abroad and at all airports for those who arrive in the country.

Facial recognition at Dulles International Airport | Photo: Ray Whitehouse for The New York Times

This biometric recognition is a part of the Simplified Arrival program launched in 2018. It is stated that manual facial verification takes 10 to 30 seconds, while algorithms cut it to two-three seconds, significantly improving travel experience.

6.  Baggage handling systems

It is time to say goodbye to well-known baggage labels for tourism – AI in travel will handle the task way more successfully with baggage handling systems. Plus, it is environmentally friendly. What exactly do we mean by that?

While the number of travelers grows yearly, specialists from the travel and tourism industry are looking for a way to optimize baggage processing. And here it is. Computer vision technology can trace the tiniest bag characteristics and send a complete bag “profile” to the database. Machine learning then distinguishes the right baggage according to its unique portrait.

Market example

AI-based baggage handling was first tested in 2020 by BagsID at Eindhoven Airport and proved successful. The pilot is extended till 2023 to provide higher accuracy and improve customer experience.

Travelers take a photo of their luggage and upload it to the system. This is the only step needed to track the bag wherever it may appear. At first, such a system does not seem reliable, but mind that every bag is unique, considering size parameters, spots, scratches, dints, and so on. As the creators say, “Pictures do not lie.”

7. Robotized self-service

Are you ready to hire a robot for customer services of your tourism business? Surprisingly or not, the robotized staff is appearing in different corners of the world, and the Covid pandemic has played a significant role in it.

Read also: Robotic process automation in the banking industry

Robots can speed up numerous daily operations, conduct data analysis and make assumptions based on it, and deal with several tasks at a time way more effectively than humans.

Market example

Connie, created by IBM Watson for Hilton hotels, is a classic example of a robotic concierge first presented in 2016 for better customer service in tourism.

Connie understands human speech using voice recognition technology and can answer customer queries to provide personalized travel. Machine learning helps the robot study on the go and become smarter with every new interaction.

7. Personalized recommendations

Machine learning algorithms started a new era in the recommendation service. They continuously track customer activity and create personalized suggestions for travel planning and booking. It is no secret that personalization is the key engine for customer satisfaction.

Read also: What about machine learning? Here is how you can use it for demand forecasting

According to McKinsey & Company, 71% of consumers expect a personalized approach, and 76% get frustrated if they do not get it. Ignoring personalization becomes a highly hazardous business decision in tourism as well.

Market example

Strictly speaking, all big travel aggregators offer advanced recommendations. Otherwise, a potential customer may get lost in the myriads of hotel options and leave unsatisfied. To prevent this, Expedia provides travel planning recommendations for every platform visitor. If you are interested in technical details, here you’ll find an explanation of how it works.

Based on CHI Software experience of providing AI in travel, powerful recommendations engines make a good match with smart assistants. Let us check another real-life market example used in the travel sphere. 

AI-Powered App Development for the Tourism Industry: View From the Inside

In 2021, a US-based startup turned to our company, aiming to create a geosocial networking app, a relatively new type of social media solutions. It uses the customer’s geolocation and time zone to offer relevant recommendations for nearby locations, places of interest, and events. The most popular market players of this kind are Yelp, Foursquare, and Facebook Places. 

Our team was in charge of the project from the very beginning, starting with the discovery phase. Now the project is over, and we are responsible for product support and updates.

The solution’s features

1. Calendar flow, which organization revolves in real time around the customer’s current whereabouts and internet connectivity, ensuring a seamless connection to the local context and, of course, improving travel experience.
2. Identification of the event, date, time, and location of the user thanks to Named Entity Recognition (“What”, “Where”, “When”) or a voice assistant powered by ChatGPT. Leveraging this information, the customer receives a curated list of recommendations, insightful answers to their queries, and even translation services, tailored to their specific needs.
3. The internal chat platform equipped with a range of features including the ability to share photos and videos, as well as comment on posts made by other users. 
4. A knowledge graph built by our ML experts for efficient data analysis. This tailored database securely stores and organizes diverse facts provided by users, ensuring their availability for future communication and personalized recommendations. 

What is next? The top benefits of implementing AI for travel based on the provided market example

• Enhanced customer engagement with a growing number of active app participants.
• Personalized marketing & promotions considering individual user preferences, location, and behavior, leading to potential growth in conversion rates and customer satisfaction.
• Efficient customer support with quick responses to FAQs and other issues and queries, potentially reducing the support team workload and improving customer experience.
• Competitive advantage obtained by offering personalized and engaging features, potentially leading to an improvement in retention.

Needless to say, the gathered user data provides invaluable insights concerning a customer portrait, preferences, and trending requests.

The Future of AI and Machine Learning in the Travel Industry

We can say for sure that the use of artificial intelligence is gaining momentum across many industries, and tourism is only a part of the big change occurring in the world. Our AI team assumes the following innovations to take the market by a storm within a year. Contact our experts directly to gain more insights regarding AI in travel and its implementation in your business in particular.

Occupancy prediction

In November 2022, the global population reached the eight billion mark. For travel industry, it means increasing passenger traffic and fewer rooms for hotel visitors.

Advanced data analytics with deep learning algorithms will help travel companies make occupancy predictions accurately, optimize their resources, and plan marketing activities a lot more effectively.

AIoT (Artificial Intelligence of Things)

The combination of AI and the Internet of Things will continue to be a thing in the travel and tourism industry. This time, we mean a recent innovation of autonomous cars. The Waymo One ride-hailing service is now available in two US cities, but soon, it may become a trend and spread within the country or even globally.

Looking for vetted AI and IoT developers? We have a team for you. Let's talk!

Autonomous (also known as self-driving) cars do not require any human involvement during the trip, which provokes a lot of questions and concerns. But, as with many other AI use cases, these cars are still being perfected to ensure the security and reliability important for passengers.

Hyper-personalization

Customers may come for products (or services), but they stay because of great customer experience. A big portion of it is given to personalization. While it is a common feature already, it is also a quickly-evolving innovation in tourism.

Read also: Will AI algorithms replace content creators?

The latest niche advancements demonstrate that businesses can hit the right spot with the highest precision ever. Applications of AI allow companies to treat travelers as individuals with their distinctive set of traits. Thus, each person will find something unique for themselves. It may be one product (or service), but, at the same time, it is myriads of experiences.

NLP for exquisite translation services

You can hardly find a hotel manager or travel agent speaking more than three languages. Instead, you can turn to AI in travel that understands dozens of languages and is capable of providing answers.

The latest developments provided by OpenAI give extra powers to NLP solutions in tourism. GPT-3 is the largest neural network collecting vast amounts of data from the entire Internet. Technologies used in the travel sector have never been this close to a high-quality translation.

In our upcoming article, we will delve into the process of how to train a GPT model for tourism applications, focusing on optimizing language models for accurate and contextually relevant translations.

Metaverse traveling

A metaverse is a virtual reality space similar to a multilayer online game where users from different places can interact and gain a common immersive experience. 

Metaverse tourism is a virtual exploration of digital twins for real-world tourist attractions, replicas of past landmarks, or events. The technology has much potential as a pre-travel assistant service for costly experiences, such as exclusive cruises, theme parks, and luxury flights.

Biometrics payments

We are used to paying with biometrics, owing to Apple Pay and Google Pay. However, payments can go even more smoothly in the travel industry. In today’s airports, travelers apply biometrics to prove their identity, make check-in, and drop off luggage. Soon, they can confirm transactions in airport boutiques or add flight-in services with a nod or wave of a hand.

AI for dynamic pricing and revenue management

Algorithmic pricing is a powerful tool for competitive advantage in the travel and tourism industry. Advanced pricing algorithms powered by AI/ML technologies enable travel companies, hotels, and airlines to optimize occupancy in real time, increase revenue, and maximize profits.

Final Thoughts

Experts do not question if businesses will use artificial intelligence in travel. The revolution in tourism is happening just as you are reading this article. Be it booking chatbots or flight forecasting services, applications of AI bring higher transparency, flexibility, and convenience to the travel and tourism industry. What business would give that up?

If you are wondering what AI use case to implement in your company, contact our team. CHI Software has managed various business challenges in tourism with the power of smart algorithms, and we will gladly share what we have learned so far.

About the author

Alex Shatalov Data Scientist & ML Engineer

Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.