Nowadays with the help of machine learning and AI, one can use a one-stop travel platform to plan and book everything from the comfort of their home. Let’s see some of the implementations of AI that make this possible.
Digital assistants and chatbots are the most easily identified example of AI applications in the travel industry. According to a document by Google, many travelers are interested in using chatbots to plan and book their trips. The services of virtual travel assistants range from advising on travel destinations to providing local weather forecasts or booking services for the user. Most travel chatbots integrate with many of the instant messaging platforms available.
Some chatbots are even advanced enough to respond to vague queries like “romantic weekend in southern Europe”. Their functionality can go beyond booking too. Some can be used as mobile travel guides and companions, helping to solve problems or providing info during the trip. It’s worth remembering that with all the benefits they bring, chatbots are still unlikely to replace human interaction entirely.
New AI-based technologies like voice-enabled virtual assistants are now helping create seamless hotel stay experiences. Guest can use them to control various amenities of a hotel room. Various IoT devices are employed in the room and guests can manage all hotel room features through voice control. In fact, the hospitality industry is getting more and more IoT-friendly and digitally advanced. Most hotel operators now believe in the mass adoption of voice assistants to control room devices, lights, and air conditioning.
The third technology that’s gaining popularity in the travel industry is facial recognition. Many airports worldwide have started using this technology to enable swift check-ins and document checks for tourists. Some airlines have started using facial recognition for a paperless boarding experience, using fully integrated biometric self-boarding gates in some airports. Other companies have experimented with using selfies submitted by the passengers to identify them through the check-in process. With the successful matching of photos and data, the app sent a message to the departure control system validating their identity and flight status and allowing them to get on board. This reduced boarding times greatly.
One of the applications of AI that has seen the greatest implementation so far is generating personalized recommendations. Furthermore, reports have found that many customers would like promotions based on past purchases and would visit more often if hotels offered the service. Just like every other eCommerce recommendation, many online travel agencies and operators are applying machine learning to analyze customer data.
The AI-powered recommender engines generate suggestions based on your current search queries and historical data of all users, singling out typical searches and providing the right recommendations to the right users. The process can be improved through sentiment analysis. Sentiment analysis is the process of mining text to detect positive, negative, or neutral sentiment. Hotels, airlines, and other travel businesses can use customer feedback analysis to personalize and enhance their services.
These are some of the implementations already at work to make each traveler’s experience better. We can expect to see more of the same technology applications in the future.
