By Sandeep Bhasin
In recent years, the airline industry has witnessed a profound transformation, largely attributed to the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies. According to the Global Airline Retailing Market Research Report, the global airline retailing market is expected to reach USD 42.35 billion by 2030, growing at a CAGR of 16.49% from 2023 to 2030. Modern airline retailing strives to deliver a travel experience that is not only seamless and intuitive but also intelligent, covering every aspect from shopping and booking to fulfilment. This approach transcends conventional air and ancillary services, offering a broad spectrum of innovative options and non-air extras such as car rentals, accommodations, excursions, and events. The goal is to establish a comprehensive and convenient one-stop solution for travellers.
Airlines are strategically investing in customer-centric experiences and offerings that enhance and customize travel experiences which include customer-centric pricing, biometrics, robotics, and contactless travel, emphasizing digital self-service. Moreover, airlines are embracing AI and ML to enhance operational efficiency, flexibility, and real-time customer engagement, enabling effective cross-selling, upselling, and service provisioning. The analytical capabilities of AI and ML technologies empower airlines to examine extensive datasets, recognize trends and patterns, facilitating data-driven decision-making and personalized service delivery.
AI/ML technology has been extensively integrated into the airline industry for several years, and its prevalence continues to expand. Today, airlines utilize AI/ML technologies across various departments, including but not limited to flight scheduling, airline networks, pricing, revenue management, and operational and staff planning. In this article we will look at some of the areas of AI/ML implementation in the airline industry.
Advancement in Pricing strategies in Airlines
The evolution of pricing strategies in the airline industry has undergone significant advancements over the years. These advancements have led to various pricing models being implemented. Initially, static pricing was the first generation of pricing systems, and it was based on a simple set of rules, such as cost plus a fixed markup.
However, its lack of flexibility and inability to adapt to changing market conditions prompted the development of rules-based systems which use pricing algorithms, based on historical data and revenue management strategies for inventory pricing, as the second generation which was more flexible than static pricing, but it was still not able to capture the full complexity of the market. AI/ML-driven pricing is the third generation of pricing systems that captures the full complexity of the market and makes real-time pricing decisions that are optimized for profitability. It provides businesses with the ability to adapt to and respond to changing market conditions more efficiently and accurately and create personalized offers for shoppers.
Enhancing Customer Experiences with the Power of AI/ML
Adopting retailing practices, wherein airlines portray themselves as contemporary retailers rather than merely suppliers of inventory, is a key trend in the airline sector. This shift in mindset allows airlines to enhance customer experience and drive revenue through personalized offerings and targeted marketing strategies.
By utilizing modern retailing techniques for air, ancillaries, bundles and upgrades, airlines have been able to optimize their pricing strategies and increase revenue. Additionally, these technologies allow airlines to offer personalized recommendations based on passengers’ trip purpose and previous travel history. They also enable seamless integration with other travel platforms, making it easier for passengers to book accommodations and transportation alongside their flights. Travel technology partners like Sabre are increasing using Cloud and partners like Google for development of these AI/ML technologies. These products can help uplift air revenue in 3-5% range and ancillary revenue in 10-15% range depending on the implementation and markets airlines operate in.
This shift in business models not only allows airlines to have more control over the offers presented to passengers but also enables them to personalize and tailor their services based on customer’s shopping context and deducing their needs from the shopping context. By leveraging NDC channel and intelligent retailing solutions, airlines can gather valuable data on customer behaviour and preferences, allowing them to create more targeted and appealing offers that meet the specific needs of their customers.
The Road ahead for Enhanced Airline experiences
Adopting AI/ML in the airline sector has several advantages but also poses certain difficulties. This revolutionary journey is made more challenging by the shift in the airline industry from conventional Passenger Name Record (PNR) based retailing to contemporary offer order-based retailing. Building scalable end-to-end systems that can effectively handle massive amounts of real-time data is a critical component of this shift; this task requires both technology and subject matter expertise. Airlines face significant obstacles in this process even with highly skilled analysts and sizable machine learning teams. First off, building scalable end-to-end systems necessitates strict and methodical methods that go beyond traditional knowledge. For these sophisticated systems to operate without a hitch, effective productization becomes necessary. Moreover, the paradigm shift goes beyond offline operations; these systems actively participate in real-time customer interaction, which calls for extraordinary scalability and performance. Travel technology partners such as Sabre bring the domain and technical expertise for airlines to realize this shift to modern retailing systems. These collaborations ensure that airlines have access to cutting-edge technologies and expertise, allowing them to enhance their end-to-end systems and provide seamless experiences for their customers. By leveraging the capabilities of reliable technology suppliers, airlines can stay ahead of the competition and adapt to the ever-evolving demands of the industry.
The airline sector is only one of the many industries where artificial intelligence is predicted to revolutionize. In a nutshell, the incorporation of AI-driven solutions has the potential to reform and improve all aspects of air travel, with improvements in efficiency, safety, and overall industry transformation anticipated. The implementation of AI in air travel could lead to significant advancements in passenger experience. Some potential advantages of implementing AI-ML applications in the airline industry include the ability to streamline operations, reduce human error, and enhance predictive maintenance capabilities. However, it is important to carefully consider the potential disadvantages, such as the need for significant investment in infrastructure and training. The airline industry stakeholders need to approach these developments with a critical eye, making sure they are in line with requirements and objectives and also select the right technology partner for development of these cutting edge solutions. Critical thinking show allow airlines and technology partners to navigate the advancements that AI/ML offer while ensuring that they benefit travellers and society as a whole.
The author is vice-president, software engineering, Sabre Bengaluru