{"id":66711,"date":"2023-11-15T15:05:33","date_gmt":"2023-11-15T14:05:33","guid":{"rendered":"https:\/\/intellias.com\/?post_type=blog&p=66711"},"modified":"2024-07-29T13:54:34","modified_gmt":"2024-07-29T11:54:34","slug":"ai-in-travel-spotlight-on-market-opportunities","status":"publish","type":"blog","link":"https:\/\/intellias.com\/ai-in-travel\/","title":{"rendered":"AI in Travel: Spotlight on Market Opportunities"},"content":{"rendered":"

Because travel is an inherently human-centric experience, tourism and hospitality companies have been somewhat skeptical of AI in travel impact. But sentiment is shifting.<\/p>\n

\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t<\/linearGradient><\/defs><\/svg>\n\t\t\t\t\t

Europe is and will be a fantastic place to invent new AI applications, especially for tourism. We are the first tourism destination of the world, so we are the one generating the largest, biggest amount of data in tourism on this planet.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tThierry Breton, <\/span> Commissioner for the Internal Market of the European Union<\/span><\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section>\n

As domestic and international travel rebounds, companies are looking for new ways to capitalize on the growth momentum, and AI appears to be one of the vehicles for getting faster traction.<\/p>\n

In this post, we analyze the scale of AI in travel, zooming in on benefits, commercial opportunities, and feasible use cases.<\/p>\n

Key benefits of AI in travel<\/h2>\n

AI models are much better than humans at analyzing data \u2014 and the travel industry has deep data troves. By using algorithms for advanced data analytics, industry players can reach more customers, elevate service levels, tap into new revenue channels, and increase operating efficiencies.<\/p>\n

Deeper customer insights<\/h3>\n

Machine learning (ML) and deep learning (DL) algorithms<\/a> can trawl millions of data points in provided datasets to uncover new correlations, trends, and similarities. In short, AI and ML both enable advanced customer segmentation, sentiment analysis, and behavior forecasting.<\/p>\n

Hostelworld<\/a>, for example, successfully uses machine learning<\/a> for sentiment analysis and marketing campaign optimization. By combining the analytical and predictive powers of ML, Hostelworld managed to increase its click-through rate (CTR) for email campaigns by 86% and its email open rate by 12%<\/a>.<\/p>\n

Better customer service<\/h3>\n

Thanks to natural language processing (NLP), algorithms can easily understand text-based commands and different contextual clues to better deal with incoming customer requests. At the most basic level, AI can help classify and prioritize customer support cases or look up relevant information for agents. More advanced AI use cases include end-to-end customer issue resolution and voice-based customer support.<\/p>\n

Artificial intelligence in tourism can increase support staff productivity by 20% to 50%<\/a> or more. Airlines like Cathay Pacific<\/a> already handle 50% of their customer care chats with AI assistants, allowing human agents to focus on more complex tasks.<\/p>\n

\n\t\t\t
\"AI<\/div>\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
AI Engineering Productivity Cookbook<\/div>\n\t\t\t\t\t
Unleash the potential of AI in software engineering for higher productivity and reduced time-to-market<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t Download now <\/span>\n\t\t\t<\/div>\n\t\t<\/a><\/div>\n

New revenue channels<\/h3>\n

AI models are good at needle-in-the-hystack<\/em> types of problems. By applying classification, regression, or interference, algorithms can locate new revenue-generating and\/or cost-saving opportunities within a presented dataset. An average AI model can make over 100 million<\/a> sales-related decisions each day.<\/p>\n

Model outputs can vary from hyper-personalized cross-sells or upsells to dynamic price optimization. Finnair, for example, increased revenue by 3%<\/a> by optimizing prices across 70 origin and destination (O&D) segments with AI.<\/p>\n

Streamlined operations<\/h3>\n

Apart from supplying teams with business intelligence<\/a>, algorithms can also handle low-value menial work, ranging from data entry and reconciliation to data modeling and reporting. When integrated with other travel technology \u2014 booking engines, property management systems, revenue management software \u2014 AI algorithms can also complete more complex workflows: automatically check in guests, design better route schedules, or optimize staffing levels based on demand trends.<\/p>\n

citizenM<\/a>, for example, uses Mist AI<\/a> by Juniper \u2014 an intelligent IT operations and support platform \u2014 to streamline the deployment and provisioning of IT services across its portfolio of properties. Thanks to AI, the hotel\u2019s team can create automated workflows operated via the cloud<\/a> to support exceptional guest experiences, ranging from guest self-checkout to in-room technology. With AI-driven IT infrastructure and network monitoring, citizenM can also have fewer technical staff on-site for troubleshooting.<\/p>\n

7 real-world use cases of AI in tourism<\/h2>\n

AI models may be great with analysis, but what can they know about real-world adventures? A lot, actually.<\/p>\n

\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t<\/linearGradient><\/defs><\/svg>\n\t\t\t\t\t

ChatGPT has turned out to be a capable travel agent<\/a>. Whether you\u2019re looking for \u201cthings to do on a budget in Rome\u201d or a \u201c10-day itinerary for a backpacking trip in Peru,\u201d ChatGPT has an unlimited roster of options. Thanks to plugins<\/a>, travelers can also compare flights, research car rentals, and handle hotel bookings straight from the GPT app.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t A third of travelers say they would use ChatGPT to plan their vacation. <\/span> Longwoods International<\/span><\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section>\n

But conversational AI<\/a>\u00a0in travel is just one use case. Almost every major player in the tourism and travel industry is sizing up the technology\u2019s cross-functional potential and looking into building foundational AI models in-house.<\/p>\n

Among travel executives surveyed by Euromonitor<\/a>, 97.8% agree that AI will have a major impact on the industry over the next five years. The travel booking industry is expected to be among the first to be disrupted by AI, though other players can also see substantial dividends from AI investments.<\/p>\n

If you want to be among the next generation of leaders, we recommend looking at the use cases of AI for travel.<\/p>\n

Digital concierge services<\/h3>\n

An outstanding guest experience is a major revenue factor for the hospitality industry. So is impeccable customer service. But with ongoing staff shortages, both are hard to deliver.<\/p>\n

\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t<\/linearGradient><\/defs><\/svg>\n\t\t\t\t\t

Eighty-two percent of US hotel managers are experiencing a staffing shortage, 26% severely so \u2013 meaning the shortage is impacting the hotel\u2019s ability to operate.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t <\/span> The American Hotel & Lodging Association (AHLA)<\/span><\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section>\n

Unlike the early generation of chatbots, which were mostly driven by pre-programmed rules, an AI travel agency or AI travel assistants have more wits<\/em> and can perform a greater repertoire of tasks. Thanks to natural language processing (NLP) and large language models (LLMs), chatbots can analyze and summarize content from a wide variety of sources to reply to different user queries.<\/p>\n

On the back end, conversational systems can also interact with other tech systems: exchange data, look up information, update records, etc. Thanks to such integrations, an AI concierge can automatically handle a wide range of tasks, from guest self check-in to ordering late-night munchies and upselling some neat services in between.<\/p>\n

At Virgin Hotels, guests are greeted by Lucy<\/a> \u2014 an in-app virtual assistant. Lucy functions as a contactless mobile key to access the room and can automatically adjust the lights, thermostat, and TV. She\u2019s also the one to ring up for room service or ask about any details regarding the stay.<\/p>\n

Lucy is a capable concierge because it integrates directly with Virgin\u2019s property management system (PMS), which contains data about guest bookings; a point of sale (POS) system used for managing food and beverage operations; a smart system for controlling every appliance in the room; and guest management software, which automatically generates checklists for staff based on guest requests. Thanks to such deep integrations, Lucy can perform a wide range of tasks across all Virgin properties and retain guest preferences for better experience personalization.<\/p>\n

AI-driven revenue management<\/h3>\n

Profit margins in the travel industry went from 21.93% in Q3 2021 to 14.22% in Q2 2022<\/a>. Energy price hikes, rising fuel costs, ongoing supply chain kinks, and accelerating inflation are behind that squeeze. Moreover, many travel companies are still rebuilding cash reserves depleted during the pandemic.<\/p>\n

In the hotel industry, room rates have historically been the main source of revenue. But as external costs continue to rise and guest expectations evolve, hoteliers need to focus more on total profitability.<\/p>\n

The problem? Most revenue management software typically produces spreadsheet-based reports, which managers then need to interpret and transform into better strategies. AI solutions can do more advanced number crunching when it comes to analyzing data, predicting trends, and prescribing strategic actions.<\/p>\n

By analyzing historical data and operating trends, AI-powered revenue management solutions can suggest better:<\/p>\n