Artificial intelligence is changing how we interact with technology. Everything, from movies and television to the orientation of spacecrafts in orbit, now fundamentally depends on artificial intelligence. Meanwhile, as brick and mortar companies come to terms with accepting and integrating AI technology into their framework, businesses that fail to learn and adapt get swept under the rug.
One only needs to look at what fintech startups are doing to giant financial conglomerates to learn about the consequences of remaining confined to a rigid structure that doesn’t evolve when it has to.
One industry that is undergoing phenomenal change due to artificial intelligence is travel. The travel industry takes improvements in technology very seriously and doesn’t hold any reservations when it comes to integrating itself with digital technology. After all, the traveler’s comfort depends on it.
This has given rise to innovative value additions that make traveling easier and more enjoyable. The industry is using artificial intelligence to predict travel choices, complete bookings, personalize services and manage their customer’s trip needs.
Uber and Lyft
Both Uber and Lyft count on artificial intelligence to work for them. In order to enhance the user’s experience and increase the profitability of their business, ride hailing apps like Uber track millions of metrics to understand the spending patterns of their customers. Artificial intelligence analyzes all of this data without the intervention of human input and makes relevant decisions for the client. Uber even went so far as to acquire the machine learning startup Geometric Intelligence to create a new division within the company called Uber AI Labs.
Some of the advantages of artificial intelligence is identifying if a rider is drunk or if the app is being misused.
Phoning a call center to book tickets is also in the process of getting phased out because many startups are integrating AI into the service side of things to enable smart bookings. An example is HelloGbye, a virtual assistant that stores a traveler’s flight rewards in their apps, makes changes to their trips and gives on-the-fly notifications for last minute changes such as flight cancellations and delays.
In the future, artificial intelligence will allow travelers to book tickets based on their preferences, completely cutting out the middle man involved in the entire transaction and making the trip more cost effective.
Learning a Customer’s Preferences
There are a lot of variables that go into traveling that cannot be accounted for by simple software or human intervention. Little things such as seat location on a flight and lodging preferences can make or break a traveler’s trip. AI will use all of the data generated by the travelers to make bookings and decisions that meet their expectations. This saves time and money, both of which are a big part of business travel.
Many startups in Silicon Valley are going head to head against each other in a race to develop the best technology for self-driving cars. Countries that lead the race globally are US and China, with Germany and Japan trailing behind them despite being known for their robust automobile industry. According to autonomous vehicle expert Tony Han, co-founder of JingChi, there are five levels of integrating AI into autonomous cars.
Level 1 is a very basic, on-the-surface technology that has been around for several years. This includes little changes such as cruise control. On the other end, implementing Level 4 would mean a car can operate without the driver’s intervention in controlled environments, but cannot be used in busy streets or areas of high traffic. Level 5 is the most advanced, allowing AI to assume full control of the vehicle without the driver’s information.
The stakes are so high in the self-driving autonomous industry that even chipmaker Nvidia has begun providing vehicle technology solutions to automotive companies that want to make their cars ‘self-driving’, pouring billions of dollars. It will be challenging for engineers because the underling AI has to be perfect, requiring a tremendous amount of computing power and a lot of code to write. This involves extremely intelligent minds and a lot of money.
How Social Media Will Play a Big Role
Social media such as Facebook, Twitter and Instagram will be used by artificial intelligence to take advantage of big data. These platforms will be used to decode the traveler’s overall satisfaction when it comes to their journey, taking into account their sentiments before the actual travel, during the journey and after it. If the traveler writes a scathing review of the service on their social media handles, listening tools will capture the customer’s intent and apply their feedback to improve services.
Improving Travel Across the Borders
Traveling across countries requires extreme scrutiny of travel documents by authorities that often overlap different departments. This procedure can be very slow for business travelers resulting in a loss of both time and money. This is where facial recognition technology can be used to easily move the customer through airports, immigration and customs.
A relatively simply facial scan can be used to make it easier for travelers to visit restaurants, use entertainment services and board a plane. Of particular use here is blockchain technology which will ensure that the data being generated is reliable and trustworthy.
Traveling by Rails
Traveling is particularly stressful for railway passengers. Railway authorities simply cannot analyze every single traveler’s data. This is where machine learning can be used. AI can be utilized to create a highly personalized and predictive journey for the client. One of the key features that will be made available in the future is price prediction for specific tickets, subject to demand.
One app that comes to mind is BusyBot which crowdsources data from passengers by taking a small survey. It then uses the collected data to notify other passengers about how busy any specific section of a railway currently is.
Apps will allow customers to see how long their desired ticket will remain at a certain price, how many tickets are currently available at that price and display the cheapest available ticket for the day.