It’s no secret that the travel industry has become digital-first over the last several years. In fact, research shows that 60 percent of leisure and about 40 percent of business travel transactions are now completed online.
While most business travelers are required to use company-provided booking tools or resources, half of those still “go rogue” and purchase out-of-policy travel. Why? Because corporate travel management tools too often present irrelevant inventory and, even when they do, a sub-par user experience drags out the time it takes to book. Combine pre- and post-travel pains with an on-the-road headache—delayed or canceled flights, last-minute changes in meetings that require a change in travel plans, and a lack of exercise and healthy meals—and we’re looking at a sector of the industry that’s ripe for innovation.
When you stand back and think about how to solve all of these corporate travel management challenges, the one word that comes to mind is personalization. Consumer travel sites have done a phenomenal job in this area, offering depth and breadth of inventory as well as user-friendly experiences that take into account the traveler’s personal preferences and loyalty clubs, putting the pressure on corporate travel management solutions to “up their game.” This is where technology, and machine learning in particular, are helping to transform business travel today as we know it.
The gap between consumer and business travel solutions is obvious from the moment the traveler logs in to book a trip. Whereas a consumer travel site almost instantly fills the page with a plethora of personalized options, minimal personalization occurs for the business traveler. And while the company might be perfectly happy with those policy-compliant options, the traveler may not. Their experience does not take into account their flight and hotel preferences and loyalties, encouraging them to go rogue. By leveraging artificial intelligence, business travel solutions can better match travelers’ personal preferences and desires with inventory that meets company policy guidelines.
Machine learning, a subset of AI that analyzes large sets of examples and studies correlations, can help achieve this goal. A machine learning algorithm can help improve the user experience by finding recurring patterns in their preferences and behavior and then predicting the best options that can meet both company policy and the business traveler’s needs. Through machine learning, business travel solutions can learn booking behaviors every time an employee uses it, resulting in a continually improving user experience—and reduced booking times—so employees can focus on the reason for the travel rather than the travel itself. In fact, it’s how we help our customers reduce the typical hour to book travel down to an average of six minutes.
Beyond the booking process, AI can help support travelers on the road when they need help most. For instance, there are examples of tools that employ AI-powered chatbots to help reduce the workload on limited customer support staff. However, it’s important to understand chatbots aren’t enough when an employee is in the airport looking at a multi-hour delay and a missed child’s performance back at home. The human touch is needed. In the ideal scenario, the corporate travel platform leverages machine learning to catch impending travel blips, flagging to human support agents that they need to proactively engage with the road warrior –– helping the traveler get home in time for a curtain call.
It’s hard to imagine a situation in business travel where AI will completely eliminate the need for human intervention or touch. Ideally, AI will be leveraged and then engage humans in higher value add situations for the traveler—in just the right way and at just the right time. As more companies transform and innovate their business travel function into “people-first” organizations, the human component will always factor into employee satisfaction. In the long term, a user-friendly business travel solution that employees love is the clearest path to a more effective travel program and spend management, as well as better visibility into employee travel overall.