Seven gen AI use cases for travel and transport
1. Hyper-personalizing the passenger experience
Personalizing customer experiences is important in almost every sector, but in the travel industry, where experience is the product, personalization is everything.
The content-producing capabilities of generative AI enables travel organizations to create personalized content at scale. For example, travel operators can create personalized itineraries based on customer prompts, incorporating not only a traveler’s preferences, but external factors such as weather forecasts, passenger location, nearby special events and more.
Development of these applications is well underway. For instance, Trip.com released a ChatGPT-powered plugin to deliver customized product recommendations and assist with itinerary planning. Users can enter their destination, trip dates and other preferences to reveal a suggested itinerary based on their prompts.
In many cases, offering personalized services also opens up opportunities for cross-selling and up-selling. For example, a company that offers personalized itinerary planning can integrate third-party sites, such as local restaurants and attractions, and offer their users the added convenience of one-click booking.
A hyper-personalized customer experience goes beyond booking and planning capabilities, though. Other applications include:
- Immersive previews. The generation feature, in concert with enabling digital technologies such as AR/VR, can give customers a first-person preview of destinations, attractions or hotels, letting them make better purchase decisions.
- Software agents. Gen AI-powered virtual assistants can converse with passengers in natural language and help them book tickets, reserve connecting transportation, or even navigate stations and airports.
Essential to personalizing the travel experience is creating a more inclusive experience for travelers. This can take any number of forms: from personalized recommendations for accessible accommodations and routes, to providing customer support in a variety of local languages.
For example, MakeMyTrip, India’s leading travel company, introduced voice-assisted booking in Indian languages to make the platform more inclusive and accessible. MakeMyTrip’s CTO, Sanjay Mohan, estimates that this feature will open the travel industry to 100-200 million new users who prefer to communicate in their native language and use a voice system, rather than a mobile app. Mohan also says the tool will help improve accessibility for users with disabilities who sometimes cannot use traditional digital tools.
- Summarization. Gen AI applications can condense lengthy travel guides or itineraries into concise and accessible formats, making it easier for individuals with cognitive or reading impairments to understand and plan their trips.
- Software agents. Gen AI-enabled tools can act as personal travel assistants, catering to individual needs and providing personalized recommendations based on user preferences, mobility requirements, and accessibility standards.
- Sentiment analysis. Transport operators can also leverage sentiment analysis and classification to suggest service offerings tailored to passengers with special needs.
- Inclusivity. The generation and translation features can be used in combination to develop innovative solutions, such as using AR/VR-enabled avatars to convert travel announcements into sign language in real time.
Generative AI can be used to influence passenger behavior and enable a modal shift towards more sustainable options. For example, a city council may leverage generative AI to power a mobile app that produces customized walking, cycling or public transportation routes that will not only take the user to their final destination, but also pass a number of popular landmarks, cafés and restaurants along the way. The app could also calculate the amount of carbon offset by these more sustainable travel methods and suggest opportunities for people to reduce their carbon footprint when traveling.
- Emissions reduction. AI systems can analyze the vast amounts of data related to transportation patterns, energy consumption, and environmental impact to identify areas for improvement and suggest sustainable strategies for the sector.
- Customer engagement. Sentiment analysis can help monitor public opinion and feedback related to sustainable travel and transport initiatives, while gauging the effectiveness and acceptance of sustainability efforts.