Next up in our Executive Q&A series is an interview with Christopherson’s Chief Technology Officer, JB Walsh. JB shared his expertise and insight on artificial intelligence (AI) and its place in business travel software.
JB Walsh, CTO at Christopherson Business Travel
Q: Before diving into the application of artificial intelligence in business travel, let’s just start with your thoughts on where things currently stand with AI.
A: AI has been in the media for years now, but several factors have more recently allowed it to mature to a level where it is being used prevalently across multiple industries. Being comprised of multiple sub-disciplines, AI required advances in deep learning, machine learning, and even natural language processing to really take hold.
Q: For any of us non-tech people, can you explain a bit more about deep learning, machine learning, and natural language processing?
A: Sure. Deep learning are the advances in hardware and cloud services that have allowed real-time analysis of much larger data sets than ever before. Machine learning is the result of the rapidly growing marketplace of off-the-shelf machine learning tools that have opened the doors to inexperienced users wanting to experiment. And natural language processing refers to the advances in natural language processing engines that have allowed developers to easily apply AI services in a variety of new platforms such as mobile devices, bots, etc.
Ultimately, all of these advances mean it’s much less expensive today to invest in AI than it was 5 years ago, so the adoption of AI is growing rapidly.
Q: So how do you see AI being used in the business travel industry?
A: Travel companies across all verticals in the industry have troves of anonymized data available to them for use in business travel-related AI applications and services. An example of this would be the personalization of products and services where anonymized business traveler data is being segmented into various profile types and is then used to predict everything from flight, room, and car preferences, to the best times to offer value added products and services.
Another example would be self-service offerings where AI is used to create bots that can interpret natural language input from business travelers to help them self-service their bookings and other travel needs.
Reputation management is another example. In this case, AI-based applications monitor social networking feeds to determine real-time customer sentiment and automatically intervene where appropriate to abate potentially negative situations.
As a travel management company with industry-leading proprietary software and an in-house development team, we are consistently evaluating where our technology can benefit from AI and in turn restructuring the data we store. Doing this allows us to provide clients with continually better tools that actually help them make informed decisions for their travel programs.
Q: What do you think are the most important benefits of AI for business travel managers?
A: One of the great benefits of AI is the ability to self-serve. Servicing individual traveler needs can be very time consuming for corporate travel managers and can create a work load that fluctuates dramatically. By using technology that employs AI to allow business travelers to self-service their bookings, travel managers can save a lot of time and help mitigate large fluctuations in workload.
Another benefit would be the ability to better evaluate their travel program more quickly. One key success metric for travel managers is to achieve cost savings while retaining high levels of service. While some changes to a travel program may be obvious, AI can uncover seasonal or other less obvious trends that could lead to big cost savings.
Q: From your perspective, do you have any predictions for AI progress or applications in the near future?
A: Today, AI requires large sets of data in order to find meaningful patterns. Additionally, the data still needs some level of intervention by people in order to identify what data is important and what data isn’t. I think the focus over the next five to ten years will likely be to improve in these two key areas. Advances in these areas would allow AI applications and services to run on less powerful devices and make real-time decisions with less historical information. These advances would also help alleviate the growing issues around storing large amounts of personal data while also opening the doors for more advanced self-service bots, innovative disruption management services, and new fraud detection techniques.
Q: Do you have any tips or advice for business travel managers regarding AI?
A: The starting point for travel managers is to understand the data they have available to their organization. Then they need to identify how it can be used to drive additional revenues or lower expenditures. If they’re unsure of how to do this, Christopherson’s Account Managers work closely with our clients to do exactly this. I would also encourage travel managers to utilize our software integration with Domo, to better understand and visualize their data, so that they can in turn make data-driven decisions that benefit their travel program.
