How AI Is Improving The Air Travel Experience

Several airlines and airports around the world are testing and implementing facial recognition software that can verify travelers with a “quick photo capture”, allowing passengers to board using a biometric self-boarding gate. Airports like Jackson Atlanta International Airport have ‘fully biometric’ gates and terminals where travelers’ faces are their tickets. It is predicted that by 2021, the majority of airlines will be using self-boarding gates with biometrics. This is expected to improve safety and security, while creating a faster and more efficient check-in and boarding process.

Then we come to AI-powered robots – some of these are being deployed at airports, especially in Asia. Seoul’s Incheon Airport has a number of robots performing concierge roles, while airports in India and Japan are applying similar solutions. Similar to AI-enabled messaging, the idea is that it will reduce the need for guests to wait in line to ask a question, while freeing up employees’ time to focus on other tasks.

With AI, we can also get better at predicting trip disruptions. Various solutions which use predictive analytics to identify delay patterns across flights to forecast disruptions are being developed. They factor in things like the historical on-time performance of an airline, seasonality, flight timings, flight paths and air traffic, congestion at various airports, and weather forecasts. With this information, they can predict the probability of a delay occurring, as well as the length of the delay.

Challenges and limitations

While AI can deliver cost savings, a streamlined booking process, and many other benefits, it has its limitations. For instance, we still cannot rely on it for the full automation of complex or unusual bookings, as the consequences of “getting it wrong” can be quite severe. If an automated stationery buying tool ordered virgin paper instead of recycled, you could just send it back. But if a business traveler gets to the airport and finds he’s been booked to Shanghai instead of Beijing, that could cost his company a contract – not to mention the frustration for the individual. Travelers require zero errors in their bookings, which is a high standard for AI to stand up to and so limits it to use cases in booking and trip management where near 100% accuracy is routinely achievable.

Another complication is that to a large extent, industry players have worked in isolation, developing a myriad different apps and other technologies aimed at enhancing the travel experience. All of the disparate development means end-users have to rely on fragmented solutions, with each individual technology only addressing part of the experience. And it’s hard to see how the diverse solutions can be integrated because of the competing business models and financial interests in the travel value chain. To date, all the major players have, understandably, focused on meeting their own needs – and these do not always align with those of their supply chain partners. This does, however, present enormous opportunities for third-party integrators.

There are also legal issues which hinder the indiscriminate adoption of many technologies. Most of these are centered on privacy and data protection concerns of data processing and ownership of data required to enable a complete range of digitally-enhanced traveler services. The recent European General Data Protection Regulations (GDPR) provisions regulate the sharing of personal data and we expect further similar data regulations from other jurisdictions in future.

Technology has largely evolved much faster than the key players’ capabilities to manage it, and while the traveler appetite for tech solutions grows, the gap will continue to widen. This, however, should not sound alarm bells. If anything, experience shows that such an environment is the breeding ground for disruption, and we could well see the emergence of new players able to assemble all the functionality onto a single screen – and profit from the process.