The management of talent has always been and continues to be a major challenge for most industries. This is particularly true for knowledge based industries like information technology. The dramatically changing dynamics of the Indian Technology industry compound the challenges and opportunities faced by the industry.

Never since the advent of mass production has an industry seen such dramatic volatility in such short period of time. The revolution before primarily added to the productivity of the labor and moved across the globe. The current revolution is not merely transcending national borders – it is redefining jobs, eliminating others and creating new opportunities.

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Over the years, the influence of artificial intelligence (AI) has spread to almost every aspect of the travel and the hospitality industry. Thirty percent of hospitality businesses use AI to augment at least one of their primary sales processes, and most customer personalisation is done using AI. The proliferation of AI in the travel and hospitality industry can be credited to the humongous amount of data being generated today. AI helps analyse data from obvious sources, brings value in assimilating patterns in image, voice, video, and text, and turns it into meaningful and actionable insights for decision making. Trends, outliers, and patterns are figured out using machine learning-based algorithms that help in guiding a travel or hospitality company to make informed decisions.

“Discounts, schemes, tour packages, and seasons and travellers to target are formulated using this intelligent data combined with behavioural science and social media attribution to know customers behaviour and insights. “

Let’s take a close look at the AI-driven application areas in the travel and hospitality industry and the impact on the ensuing business value chain:

Bespoke and curated experiences

There are always a few trailblazers who are up for a new challenge and adopt new-age exponential technologies. Many hotel chains have started using an AI concierge. One great example of an AI concierge is Hilton World wide’s Connie, the first true AI-powered concierge bot. Connie stands at two feet high and guests can interact with it during their check-in. Connie is powered by IBM’s Watson AI and uses the Way Blazer travel database. It can provide succinct information to guests on local attractions, places to visit, etc. Being AI-driven with self-learning ability, it can learn and adapt and respond to each guest on personalised basis.

In the travel business, Mezi, using AI with Natural Language Processing technique, provides a personalised experience to business travellers, who usually are strapped for time. It talks about bringing on a concept of bleisure (business+leisure) to address the needs of the workforce. The company’s research shows that 84 percent of business travellers return feeling frustrated, burnt out, and unmotivated. The kind of tedious and monotonous planning that goes into the travel booking could be the reason for it. With AI and NLP, Mezi collects individual preferences and generates personalised suggestions so that a bespoke and streamlined experience is given and the issues faced are addressed properly.

Intelligent travel search

Increased productivity now begins with the search for the hotel, and sophisticated AI usage has paved the way for the customer to access more data than ever before. Booking sites like Lola.com provides on-demand travel services and have developed algorithms that can not only instantly connect people to their team of travel agents who find and book flights, hotels, and cars, but have been able to empower their agents with tremendous technology to make research and decisions an easy process.

Intelligent travel assistants

 Chatbot technology is another big strand of AI, and not surprisingly, many travel brands have already launched their own versions in the past year or so. Skyscanner is just one example, creating an intelligent bot to help consumers find flights in Facebook Messenger. Users can also use it to request travel recommendations and random suggestions. Unlike ecommerce or retail brands using chatbots, which can appear gimmicky, there is an argument that examples like Skyscanner are much more relevant and useful for everyday consumers. After all, with the arrival of many more travel search websites, consumers are being overwhelmed by choice – not necessarily helped by it. Consequently, a chatbot like Skyscanner is able to cut through the noise, connecting with consumers in their own time and in the social media spaces they most frequently visit.

Recently, Aero Mexico started using Facebook Messenger chatbot to answer very generic customer questions. The main idea was to cater to 80 percent of questions, which are usually repeat ones and about common topics. Thus, AI is of great application to avoid a repetitive process. Airlines hugely benefit from this. KLM Royal Dutch Airlines uses AI to respond to the queries of customers on Twitter and Facebook. It uses an algorithm from a company called Digital Genius, which is trained on 60,000 questions and answers. Not only this, Deutsche Lufthansa’s bot Mildred can help in searching the cheapest fares.

Intelligent recommendations

International hotel search engine Trivago acquired Hamburg, Germany machine learning startup Tripl as it ramps up its product with recommendation and personalisation technology, giving them a customer-centric approach. The AI algorithm gives tailored travel recommendations by identifying trends in users’ social media activities and comparing it with in-app data of like-minded users. With its launch, users could sign up only through Facebook, potentially sharing oodles of profile information such as friends, relationship status, hometown, and birthdays.

Persona-based travel recommendations, use of customised pictures and text are now gaining ground to entice travel. KePSLA’s travel recommendation platform is one of the first in the world to do this by using deep learning and NLP solutions. With 81 percent of people believing that intelligent machines would be better at handling data than humans, there is also a certain level of confidence in this area from consumers.

Knowing your traveller

Dorchester Collection is another hotel chain to make use of AI. However, instead of using it to provide a front-of-house service, it has adopted it to interpret and analyse customer behaviour deeply in the form of raw data. Partnering with technology company, Richey TX, Dorchester Collection has helped to develop an AI platform called Metis.

Delving into swathes of customer feedback such as surveys and reviews (which would take an inordinate amount of time to manually find and analyse), it is able to measure performance and instantly discover what really matters to guests. Métis helped Dorchester to discover that breakfast it not merely an expectation – but something guests place huge importance on. As a result, the hotels began to think about how they could enhance and personalise the breakfast experience.

Intelligent forecasting: flight fares and hotel tariffs 

Flight fares and hotel tariffs are dynamic and vary on real-time basis, depending on the provider. No one has time to track all those changes manually. Thus, intelligent algorithms that monitor and send out timely alerts with hot deals are currently in high demand in the travel industry.

Trivago and Make my trip are screening through swamp of data points, variables, and demand and supply patterns to recommend optimised travel and hotel prices. The AltexSoft data science team has built such an innovative fare predictor tool for one of their clients, a global online travel agency, Fareboom.com. Working on its core product, a digital travel booking website, they could access and collect historical data about millions of fare searches going back several years. Armed with such information, they created a self-learning algorithm, capable of predicting future price movements based on a number of factors, such as seasonal trends, demand growth, airlines special offers, and deals.

Optimised disruption management: delays and cancellations 

While the previous case is focused mostly on planning trips and helping users navigate most common issues while traveling, automated disruption management is somewhat different. It aims at resolving actual problems a traveller might face on his/her way to a destination point. Mostly applied to business and corporate travel, disruption management is always a time-sensitive task, requiring instant response.

While the chances of getting impacted by a storm or a volcano eruption are very small, the risk of a travel disruption is still quite high: there are thousands of delays and several hundreds of cancelled flights every day. With the recent advances in AI, it became possible to predict such disruptions and efficiently mitigate the loss for both the traveller and the carrier. The 4site tool, built by Cornerstone Information Systems, aims to enhance the efficiency of enterprise travel.

The product caters to travellers, travel management companies, and enterprise clients, providing a unique set of features for real-time travel disruption management. In an instance, if there is a heavy snowfall at your destination point and all flights are redirected to another airport, a smart assistant can check for available hotels there or book a transfer from your actual place of arrival to your initial destination.

Not only are passengers are affected by travel disruptions; airlines bear significant losses every time a flight is cancelled or delayed. Thus, Amadeus, one of the leading global distribution systems (GDS), has introduced a Schedule Recovery system, aiming to help airlines mitigate the risks of travel disruption. The tool helps airlines instantly address and efficiently handle any threats and disruptions in their operations.  

Future potential: So, reflecting on the above-mentioned use cases of the travel and hospitality industry leveraging Ai to a large extent, there will be few latent potential areas in the industry that will embrace AI in the future :

“Undoubtedly, we will witness many travel and hospitality organisations using AI for intelligent recommendations as well as launching their own chatbots. There’s already been a suggestion that Expedia is next in line, but it is reportedly set to focus on business travel rather than holidaymakers.”

Due to the greater need for structure and less of a desire for discovery, it certainly makes sense that AI would be more suited to business travellers. Specifically, it could help to simplify the booking process for companies, and help eliminate discrepancies around employee expenses. With reducing costs and improving efficiency two of the biggest benefits, AI could start to infiltrate business travel even more so than leisure in the next 12 months.

Lastly, we can expect to see greater development in conversational AI in the industry. With voice-activated search, the experience of researching and booking travel has the potential to become quicker and easier than ever before. Similarly, as Amazon Echo and Google Home start to become commonplace, more hotels could start to experiment with speech recognition to ramp up customer service. This means devices and bots could become the norm for brands in the travel and hospitality industry.

The travel and hospitality industry transformation will morph into experience-driven and asset-light business, and wide adoption of AI will usher a new-age customer experience and set a benchmark for other industries to emulate. Fasten your seat belts … AI will redefine the travel and hospitality industry.