Need for AI in Travel Industry


Every sector is anticipating a dismal future. Even in these gloomy times, AI can help us float the boat. In Wuhan, where the virus originated, China facial recognition software linked to a mandatory phone app that color-coded people based on their contagion risk, decided who could enter public spaces. Even before such technology was implemented, BlueDot, A Canadian AI start-up, alerted about unusual pneumonia around a market in Wuhan in the month of December.

With the growing middle class and an increase in disposable income as a result of easy credit availability, the travel and leisure industry has benefited the most. However, The COVID  pandemic has affected the regular lifestyle of many. This sector stands most affected. In China, international travel was suspended even for those holding a valid visa.

Travel is a consumer-oriented service. AI can help understand customer needs in order to enhance loyalty as well as profitability. Conversational AI can be employed on social media platforms where the customers provide their feedback.  Chatbots can also be used to handle customer queries to make the process hassle-free. online customer service could also be enhanced by the same.

Traveler’s behavior and needs (most traveled regions, age group, gender, etc) can be understood with the use of heat mapping and travel service providers can target their marketing accordingly.  Facial recognition can ensure that tiresome paperwork is gotten rid of.  This way people can easily move through airports and other transport centers.

Machine learning can use external data and customer behavior to provide suggestions to the customer based on the same. For instance,  a change in climatic conditions can result in a change in travel plans. This can be managed by AI for the customer.

Travel is not only about customer satisfaction but also sustaining in the market.  When Jet Airways quit the market, the vault created for customers had to be filled by other airline service providers. In such a situation predictive analysis plays a key role In understanding competition and customer churn rates. Each airline could have predicted market conditions earlier and developed itself to serve the situation.

India was having slow economic growth even before the pandemic. To tackle the fall in aggregate demand, artificial demand had been created in various sectors. However, at this moment supply is stagnant due to the virus outbreak. Such a situation could also be tackled with predictive analysis.  Even when the virus began to spread earlier this year, reduction in travel was certainly foreseeable. Ways to sustain employment could be discovered beforehand by predicting customer trends with AI.


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