The Rise of AI and Chatbots in the Hospitality Industry: Opportunities and Challenges

The hospitality industry is highly competitive, so it’s important that it moves with the times. In the recent years, there has been an uptick in hotels using Artificial Intelligence (AI) and Chatbots, taking personalised customer experience to new levels.

The hospitality industry is embracing cutting-edge technologies, including Machine Learning, Chatbots, and Artificial Intelligence. AI and chatbots offer the ideal opportunity for travel firms to improve marketing, customer support, customer experience, and retention. The increasing number of travellers and deep technological advances in the hotel industry force service providers to differentiate themselves from the competition. As a result, best practices and existing business processes must be redefined at all levels of the organisation to suit guest preferences, offer unique travel experiences, and improve customer loyalty.

To personalise interaction with guests, hotels have begun to use AI technology in their customer service portfolio and operations. AI employs cognitive learning to do typical human jobs at far lower costs, with enhanced efficiency, and with few errors. According to Worldwide Hospitality, Travel 2021 forecasts, AI will be used by 85 per cent of online travel agencies and 70 per cent of hotels globally by 2024. This will result in a 40 per cent increase in clients.

Even though visitors leave their digital imprint at a variety of touchpoints such as restaurants, recreation facilities, airlines, stores, events, social media, and elsewhere, the use of this valuable data to discover guest preferences and new income sources is rather low. Data analytics provide the majority of the insights. With advances in technology and tools, using AI principles on top of data may now improve the accuracy of forecasting visitor choice. The travel and hospitality industry has already started applying AI by deploying robots and humanoids as receptionists and guides at hotels and airports.

Context Sensitive Personalised Services

To gather personalised data, information about client preferences, purchasing behaviour, satisfaction levels, and likes/ dislikes is decoded from personal/ professional networks and other sources. The largest problem here is gathering relevant data from a variety of diverse systems and drawing useful conclusions from it.

• AI may assist in the creation and refinement of hyper-personalised marketing in order to enhance revenue and client retention.

• ML may assist businesses in gathering predictive data, identifying trends within massive collections of data, and understanding customer behaviour to promote frequent flier points (FFP) redemption.

An Intelligent virtual assistant: Chatbots

According to research, 68 per cent of airlines and 46 per cent of airports aim to expand to put in place sophisticated Chatbot services based on AI. These chatbots will scan terms and react with keywords from the learning database that match. The system, which is supported by a digitally linked expert, will record, process, monitor, and learn about every event that occurs around the visitor, including environmental elements.

The virtual assistant applications will include:

• An 'intelligent virtual assistant' that communicates with guests and recommends services, special discounts, vacation ideas, recommendations, and alternate arrangements.

• The chatbot will minimise the use of call centres by providing hyper-personalised self-service.

• Without logging into separate systems, the chatbot will have access to information about the passenger, timetables, service status, loyalty, seat/room availability, cheque, and so on.

Post Trip – Loyalty and Sentiment Analysis

Customers now choose to express themselves on the internet, thanks to the rise of social media. Using AI and ML, hospitality businesses can determine which aspects of their loyalty programme are appealing to clients and which are offputting.

Sentimental analysis (using Natural Language Processing) may assist organisations in understanding good, negative, and neutral viewpoints by analysing emotional behaviour.

• Based on recommendations, hotels and service providers can build personalised smart movies and deliver them to clients. These might be about new deals, recommendations, advice, or anything else.

As per the International Air Transport Association (IATA), 7.2 billion people will be in transit by 2035. With such a large number of travellers, maintaining smooth operations would be difficult. Flight turnaround actions would necessitate the use of clever and intelligent technology to monitor and analyse potential departure delays.

• Passenger flow may be forecasted using predictive analytics and machine learning to avoid airport overcrowding.

• Machine learning may be used to estimate the risk of delayed departures based on the present operating state as well as historical data and patterns.

• Machine learning skills may be utilised to create a virtual assistant that can proactively track baggage by understanding common baggage mistreatment and breaking points, as well as conditions and settings.

AI has enormous potential. Enterprises are shifting away from rules-based automated solutions like Chatbots and towards intelligent cognitive agents that handle unstructured data, engage in more humanlike interactions, and continually learn. By merging AI with sophisticated analytics concepts, the travel and hospitality sector can offer personalised service, resulting in a better value and memorable experience for its visitors. Guests may read the news, check the weather, use maps and more in the mirror.