A longstanding conundrum in corporate travel programs is how to balance business priorities like saving money while still catering to employees' needs for tailored travel experiences. For example, by providing employees with complete flexibility to book travel, travel managers often run into challenges with policy compliance. On the flip side, requiring strict compliance means less enjoyable and productive business travel experiences and employees who don't feel acknowledged. That hurts morale and retention.
This is where artificial intelligence balances the scales. AI reconciles the competing needs of corporations and their employees, and as technology evolves and gets even smarter, these advanced solutions will continue to improve T&E management. Here's a look at how AI juggles the unique and distinct needs of both travel managers and travelers and what's in store for the future.
Where We Are Today
AI is the ultimate data manager. It collects, organizes and draws insights from expansive data sets. While this sounds simple, AI can make recommendations based on user and company data learned over time and interact with other applications also using AI to maximize efficiency. The key is machine learning algorithms that process and synthesize the data providing near real-time feedback and assistance that makes employees' lives easier and helps meet corporate goals.
When it comes to expenses, machine learning models today replace optical character recognition and can instantly read handwritten tips and totals from pictures of receipts. Based on previous expense activity, they can predict what's not on the receipt—such as vendor, location or type of expense—saving travelers time from manually populating details while also leaving little room for interpretation. In fact, machine learning can audit expense reports and validate whether expenses are accurate and in policy by cross-checking them against hundreds of data elements in seconds. With business travel spending expected to reach $1.7 trillion by 2022, according to the Global Business Travel Association, even a fraction of a percentage improvement in savings from policy compliance and reduced fraud could save billions. And as business travel expands beyond borders, AI relieves a huge amount of work for travel managers and travelers by making sense of receipts in different languages and providing accurate translations that factor in context.
Traveler safety is another area where AI is already having an impact. Travel managers want to ensure duty of care and reach employees at a moment's notice in the event of an emergency. Employees want the reassurance that their safety is a priority, but they don't want to give up their privacy by having location tracking on at all times. Machine learning alleviates this pressure by analyzing traveler data like credit cards and itineraries and ensuring the data is accurate. Take, for example, a traveler whose itinerary shows a connecting flight from Atlanta to New York at 3 p.m. and a hotel reservation in New York that night. If the flight takes off as scheduled and that traveler uses his or her credit card at the Atlanta airport at 4 p.m., machine learning could pick up, from itinerary and card transaction data, that the traveler missed the flight. But what about times when the vendor location that feeds into credit card systems doesn't match the transaction location? If that traveler photographed and uploaded the receipt, receipt image processing and analysis of previous card transactions could help pinpoint the traveler's most likely location. Machine learning combines data feeds to produce the most accurate data to predict where employees may be, all without explicitly tracking their every move.
What's Coming
Travel managers' roles have evolved. They're now seen not as gatekeepers but as service providers across multiple booking channels. But they're constantly overwhelmed with how to glean meaningful insights from the sheer amount of data they have at their fingertips. Luckily, machine learning has the speed and agility to draw learnings from data in real time. That means that as time goes on and more and more data is collected, these algorithms will become smarter still.
In the next couple years, machine learning will continue to alleviate pain points in corporate travel programs by redirecting tedious tasks to automated technology. For example, bots will replace written travel policies, using natural language processing to answer travelers' questions. Regardless of the channel where travel was booked, machine learning will check imported itineraries in real time for compliance with booking rules and corporate discounts. Not only will this increase efficiencies for travelers and travel managers when booking, it will also increase compliance and save companies money when travelers use supplier discounts.
As machine learning recognizes patterns in traveler behaviors, it will move from anticipating and recommending itineraries to actually booking travel based on past experiences, calendar holds, user profiles and preferred loyalty programs. This same technology will enable travel managers to ensure that corporate discount programs and commitments are maintained. Hotel bookings will be complete with customized room temperature, amenities and entertainment preferences, all by machines learning from travelers' past trips.
When AI frees travelers and travel managers from time-intensive and low-impact tasks, they're granted new opportunities for interesting, creative, strategic work—the type of meaningful work that helps both employees and businesses get ahead. And by making compliance easy and seamless, AI will bridge the gulf between traveler and corporate priorities, making life better for employees and travel managers alike.