AI Insights: Generative AI for search functionality in business travel programs

Tripism, a platform aggregating all aspects of a business travel program from multiple sources and driving engagement between travel teams and traveling employees, has just unveiled its generative artificial intelligence search functionality.

As part of our ongoing series on how travel brands are using generative AI solutions from companies including OpenAI, Google and more, Adam Kerr, CEO of Tripism, shared his thoughts on the technology and its impact on the travel industry.

We began working with generative AI ... a couple of years ago, using data to drive personalized responses in the Tripism platform. The first example of this was our data-driven restaurant recommendations, in partnership with Dinova, where we used AI to offer customized restaurant suggestions based on multiple sources of data (such as location, spend, culture and colleague reviews) and individual user preferences.

Since then, we have built on this experience to further enhance our machine-based learning capabilities, to deliver a more intuitive and advanced use of AI for our wider search functionality. The new search engine functionality, which launched in the autumn of this year, augments the user experience for the business traveler, using AI to deliver timely, relevant and tailored content from multiple sources.

Our current work with generative AI is focused on … improving our search functionality, using AI to continually adapt and improve the business traveler experience. AI facilitates the presentation of highly specific, relevant information, so the business traveler can access the information they need quickly and seamlessly.

We are always looking for ways to improve the user experience, offering different ways to search and find information quickly and easily. Currently our search functionality is all type based. The next step is to mirror this intelligent search as chat functionality, which we are looking to launch next year.

We are also looking to use generative AI to influence traveler behavior, particularly around making more sustainable choices. Sustainable travel management relies on empowering travelers to select greener options by measuring emissions and informing travelers of their carbon footprint in advance of booking. We plan to use AI to help facilitate this shift in mindset, to educate travelers and support travel managers who are looking for ways to better communicate with employees about sustainable choices.

The biggest challenge for us related to generative AI ... is that each business travel program is unique and highly specific to each company. Tripism delivers aggregated, bespoke and highly personalized information for each corporate, using information sourced through our own Tripism platform but also other platforms. The data-driven sets we are working with are confidential, and therefore machine learning must be on a company-by-company basis. This level of personalization requires more complex generative AI to deliver accurate and secure responses.

For the travel industry overall, we see the most potential for generative AI ... in the ability to answer the more administrative questions, for example, information about visas, travel times or risk-related questions. There are still numerous high-touch points, which could be streamlined with AI to reduce manual processes and improve the experience. There is also huge amounts of data, information overload – so the opportunity to automate and tailor messages would be beneficial.

One year from now we expect to be using generative AI ... more widely across our platform, using continual learning across texts and sources in the Tripism platform but also through external supplier content. Our goal is always to improve the business traveler experience, and using AI we are in a unique position to offer the traveler personalized information based on their requirements through one platform, weighting answers to questions based on corporate travel policy, employee feedback and multiple external resources.