In April, United Airlines hit a huge pocket of public relations turbulence after a passenger was forcibly removed from one of its partners\u2019 airplanes. The incident raised questions about blindly following procedures, passenger rights, and United\u2019s executive leadership.\r\nHere\u2019s another question it raised: Could artificial intelligence (AI) have prevented the embarrassing drama from even happening?\r\n[ Find out which\u00a0which deep learning network is best for your organization. | Get the latest insights with our\u00a0CIO Daily newsletter. ]\r\nAI and machine learning are already impacting many areas of business, such as\u00a0marketing, as well as most industries, including\u00a0retail. The travel industry in particular \u201cis ripe for AI interventions,\u201d says Param Singh, Associate Professor of Business Technologies at Carnegie Mellon University\u2019s\u00a0Tepper School of Business. From chatbots to robotic bellhops, here are seven ways AI could impact business travel in the months, and years, ahead.\r\n1. Fewer overbooking dramas\r\nOn April 9, 2017, a paying passenger was dragged off United Express Flight 3411, from Chicago to Louisville, Ky. Four seats on the full flight were needed to accommodate airline crew members, as\u00a0USA Today\u00a0and others reported.\r\nAfter no volunteers came forward, four passengers were selected by computer. Passengers were chosen on the basis of frequent-flier status, fare type, and connecting flight options. Three passengers eventually deplaned willingly in exchange for travel vouchers. A fourth, physician David Dao, refused, was removed against his will\u2014and became an unwilling member of the\u00a0viral video\u00a0hall of fame.\r\nAI could have helped United avoid the high-profile drama in several ways, says Henry H. Harteveldt, president and travel industry analyst of Atmosphere Research Group. In theory at least, AI could have provided an early warning to the airline\u2019s crew scheduling or planning application about a potential staffing problem on the horizon, giving the airline more time to address the issue, he explains.\n\t\t\tIn April, United Airlines hit a huge pocket of public relations turbulence after a passenger was forcibly removed from one of its partners\u2019 airplanes. The incident raised questions about blindly following procedures, passenger rights, and United\u2019s executive leadership.\nHere\u2019s another question it raised: Could artificial intelligence (AI) have prevented the embarrassing drama from even happening?\n[ Find out which which deep learning network is best for your organization. | Get the latest insights with our CIO Daily newsletter. ]\nAI and machine learning are already impacting many areas of business, such as marketing, as well as most industries, including retail. The travel industry in particular \u201cis ripe for AI interventions,\u201d says Param Singh, Associate Professor of Business Technologies at Carnegie Mellon University\u2019s Tepper School of Business. From chatbots to robotic bellhops, here are seven ways AI could impact business travel in the months, and years, ahead.\n1. Fewer overbooking dramas\nOn April 9, 2017, a paying passenger was dragged off United Express Flight 3411, from Chicago to Louisville, Ky. Four seats on the full flight were needed to accommodate airline crew members, as USA Today and others reported.\nAfter no volunteers came forward, four passengers were selected by computer. Passengers were chosen on the basis of frequent-flier status, fare type, and connecting flight options. Three passengers eventually deplaned willingly in exchange for travel vouchers. A fourth, physician David Dao, refused, was removed against his will\u2014and became an unwilling member of the viral video hall of fame.\nAI could have helped United avoid the high-profile drama in several ways, says Henry H. Harteveldt, president and travel industry analyst of Atmosphere Research Group. In theory at least, AI could have provided an early warning to the airline\u2019s crew scheduling or planning application about a potential staffing problem on the horizon, giving the airline more time to address the issue, he explains.\nAlso, on the day of the flight, AI might have enabled the airline to identify the passengers most agreeable to changing their travel plans based on their profile data, Harteveldt says. Younger passengers, for instance, would potentially have more flexibility and greater interest in travel vouchers, vs. a physician like Dao, aged 69, who was anxious to return to his practice in Kentucky.\n2. More personalized service\nSome of the AI interventions are already happening, with chatbots for booking (such as GuestU and SnapTravel), personal travel assistants (such as Mezi), and AI to help human agents with travel planning (notably Lola), Singh says.\n\u201cMost of the AI interventions right now are what we could call machine-learning-driven,\u201d Singh explains. \u201cWith large amount of personal data, sophisticated algorithms are able to predict your needs and recommend appropriate solutions. These are, at a core level, automating the functions that people perform.\u201d\nBut with the next wave of applications, \u201cwe\u2019ll start seeing major improvements in the business travel experience,\u201d Singh says. \u201cThis wave will be AI interventions built on cognitive computing. These systems will have the ability to understand, learn and reason through the enormous data and then provide solutions that a human agent won\u2019t be able to provide on their own. These systems would provide value-added services and experiences, which would cognitively not be possible for the average employee in the travel industry.\u201d\nThe travel industry can use AI and machine learning \u201cto learn about the habits and preferences of its frequent fliers and guests, to provide more personalized experiences,\u201d says Sumit Gupta, VP of HPC, AI and analytics at IBM. \u201cImagine the day when you can sit down in your seat and the flight attendant already knows just how you like your gin and tonic. Then, you\u2019re greeted at the hotel desk by name because of visual recognition software. And the Yankees game is already playing on the TV when I arrive in my room.\u201d\nWayne Thompson, chief data scientist at analytics software developer SAS, paints the following picture of AI-assisted business travel in the future:\n\u201cLet\u2019s say you have an important customer briefing in Los Angeles,\u201d Thompson explains. \u201cYou\u2019ve already received a text that your flight is on time.\u00a0Monday\u00a0morning is one of the busiest times at the airport, and naturally you\u2019re running late. You start to worry about finding a spot to park in the packed airport garage, but then your navigation system uses image detection to direct you to the best open spot.\u00a0Using convolutional networks, the computer can analyze photos of the parking lot in real time and detect images with a 6 percent error rate, which is better than the human eye.\u201d\nOnce you pass through airport security, \u201cyou\u2019re back on track timewise and decide to get a coffee and something to read,\u201d Thompson continues.\u00a0\u201cWhile approaching the book store, you\u2019re notified of special promotions based on your reading history. Then, at checkout you receive a coupon for gardening and classic car magazines, based on a recommendation system that knows these are your hobbies.\n\u201cNow you\u2019re starting to wonder why your co-worker hasn\u2019t arrived at the gate. She receives a warning that she was in the wrong terminal and gets instructions on the quickest route to the correct gate. Location services have long been used to route planes. Now, they can also be leveraged to better move passengers along and help assure that flights are on time.\u201d\nOnce you\u2019re in the air, you use the airplane\u2019s Wi-Fi to tweet something like: \u201cRDU > LAX leaving on time. No complaints here. First leg of this busy travel day could have been ugly but was not.\u201d Using entity extraction and sentiment analysis software, the tweet is interpreted as positive, so the airline responds: \u201cThanks! We hope the rest of your day goes as smoothly. Should be sunny and 80 in LA when you arrive.\u201d\n3. Smarter apps and chatbots\nMany developers are already using AI and machine learning to enhance the traveler\u2019s experience via apps. For example, based on information Kayak has learned about you and what you\u2019ve told the app\/web service, your preferred hotel brands will be at the top of your Kayak search results. Location and context-aware data will alert you if, say, you\u2019re on a trip to Paris and rain is in the forecast. \u201cYou\u2019d get an alert, telling you if you want to see the Eiffel Tower, go now,\u201d says Kayak CTO Giorgos Zacharia.\nThe Lola app, released in 2016, offers AI-based chatbot functionality along with a staff of human travel agents. \u201cWe\u2019re trying to create superhuman travel consultants who are AI-powered and can handle more trips per hour than a regular travel agent can,\u201d Lola CEO and co-founder Paul English told Skift. \u201cThey can make dramatically better recommendations than normal travel agents.\u201d\nAlso in 2016, 12 Radisson Blu Hotels in the U.K. began offering guests access to \u201cEdward,\u201d an interactive, SMS-based service to answer guest questions about hotel amenities, directions, and receive guest feedback, Forbes reported.\n4. Better customer service\nHilton Worldwide contact centers have AI and machine learning help from Mattersight, a behavioral routing software service, in hopes of creating a better customer experience.\n\u201cWhen a business customer calls into a hotel, airline or cruise line using our technology, Mattersight\u00a0matches their data and analyzes their\u00a0personality and behavior traits in less than five seconds,\u201d notes Andy\u00a0Traba,\u00a0Vice President of Behavioral & Data Science at Mattersight Corporation.\u00a0\u201cTone,\u00a0tempo, grammar, and syntax are all fed into an algorithm. That algorithm mines data from billions of customer calls\u00a0to quickly pair the traveler with a call center agent who is best suited for their personality and current behavior.\u201d\nFor example, a caller traveling internationally who\u2019s distraught about a lost reservation \u201cwould likely be routed to a different agent than someone who calls up to check room availability,\u201d Traba says.\n5. Travel planning integrated into everyday tools\nWe\u2019re already seeing travel tools added to apps like Facebook Messenger, Skype and Slack. For example, Concur (developer of TripIt) has developed a chatbot for collaboration app Slack, enabling users to request information about their travel plans and submit expenses via Slack using a conversational interface, says Tim MacDonald, EVP of Global Products at Concur. For example, users can type a question such as, \u201cWhen is my next business trip?\u201d and the Concur chatbot will respond with itinerary details, he explains.\nConcur is also working with Microsoft to integrate travel planning and expense processing into Microsoft Outlook 365. From the Outlook inbox, you\u2019ll be able to submit an expense by clicking \u201cSend to Concur,\u201d MacDonald says. \u201cAnd when business travel plans are added to an Outlook calendar, you\u2019ll have the option to book travel right then and see travel options pop up in the Details pane for those plans,\u201d he continues. \u201cThe business traveler will have the option to book flight, hotel and transportation for that city. Concur will read the trip dates and suggest options based on company travel policy.\u201d\n6. Voice-enabled smart hotel rooms\nVirtual assistants\u2014which some view as a low-level form of AI\u2014are making inroads at some hotels. \nMarriott International is among the hotel chains exploring natural language processing and digital assistants. \u201cOur guests are quickly adopting this technology and intelligence in their lives today,\u201d says a Marriott spokesman. \u201cFor example, people use their phone to ask for directions, order products before you even know you need them or have translation easily available. We\u2019re excited to test what it means to bring voice-activated technology into the guest room, so guests can request services, learn about the local area, and perform general informational tasks like asking for the weather or setting an alarm for the next morning.\u201d\nMarriott is currently testing this capability by placing Amazon Echo devices in some Marriott properties, with primary tests being conducted at the W Hotel in Austin, Texas. Amazon\u2019s Alexa virtual assistant in Echo devices can control the lighting in some Marriott rooms. The brand is also testing Apple\u2019s Siri in some properties, particularly Marriott\u2019s Aloft hotel in Boston.\nMeanwhile, Wynn Resorts Ltd. plans to install Echos in all 4,748 of its Las Vegas hotel rooms by this summer. \u201cAlexa will let guests control room lights, room temperature, drapery, and the television using voice commands,\u201d CEO Steve Wynn told The Verge.\n7. Hotel robots!\nIn 2014, Marriott division Starwood introduced its robotic butler, \u201cBotlr,\u201d at the Aloft Hotel in Cupertino, Calif. (home of Apple\u2019s headquarters). The R2-D2-ish robot delivers small items, like toiletries, to guest rooms, among other chores. It\u2019s also in service at Aloft Long Island City, Aloft Miami Doral, and Aloft Silicon Valley (in Newark, Calif.).\nMarriott says it\u2019s currently designing and testing Botlr\u2019s next-generation model, which is currently being tested. Guests will be able to text their hotel\u2019s Botlr to request service and get information about the hotel, among other amenities, according to Marriott.\nThe Henn-na Hotel in Japan, which opened in 2015, achieved fame as the \u201cworld\u2019s first robot hotel,\u201d according to Wired. The hotel has a humanoid robot, Yumeko, as well as an English-speaking dinosaur that wears a bellboy hat and bow tie. The hotel also uses robots to clean rooms and features AI-powered systems that let guests unlock their hotel room doors using facial recognition software.\nConnie is Hilton\u2019s IBM Watson-powered robot that acts as a AI-powered concierge, answering guests\u2019 questions about hotel amenities, nearby attractions and restaurants. Connie made its debut in 2016 in Hilton\u2019s McLean, Virginia property.\nThe challenges of AI for travel\nTo provide value-added services, AI needs \u201ca significant amount of personal information about the customer,\u201d notes Singh. \u201cIt wouldn\u2019t work without this information, and it\u2019s a huge privacy concern. A lot of people might not feel comfortable sharing their information.\u201d\nBusiness travelers \u201cwill feel better giving up their data if the travel organization is transparent about its use and puts the control back in the hands of the business traveler,\u201d adds Robert Zippel, global technology lead for Accenture Travel. \u201cSo, travel organizations need to work together with the business traveler on what the data will be used for, in regards to inputting into AI and ML capabilities, and provide opt-out options as well.\u201d\nAI introduces data security concerns as well, says Singh. \u201cWith so much personal data being stored and shared across systems, a corrupted system or a hacker could be a significant risk to the individual and the organization.\u201d\nAI also raises ethical concerns, Singh says. \u201cWhat is an AI system\u2019s goal? Is it on the customer\u2019s side by helping them? Or is it focused on the profit of the companies by guiding the customer to the most profitable product they could potentially purchase? These things would be coded into the algorithm, and no one is sure now how it will work.\u201d\nUltimately, AI\u2019s major challenge will be \u201cto provide a human touch, which is particularly important in the hospitality industry,\u201d Singh says. \u00a0\nRelated resources\n\n\n Which deep learning network is best for you? \n Why you should invest in AI talent now \n Why AI careers can start with a degree in linguistics \n The year of Alexa and the coming decade of A.I.