Artificial Intelligence. It is hard to dispute that the future lies with AI, but are airlines doing everything they can to stay ahead of the curve? AI has existed for a while but has only hit the mainstream in the last few years. The most common use cases are routine task automation, customer service improvement, and rule-based tasks such as revenue optimization. All of these use Machine learning and AI to study the previous actions of humans and apply them automatically to future decisions. What happens when you allow the AI to transform from a decision-support system into a decision-making system? Let’s dive into how Generative AI is changing the airline industry.
What is so special about generative AI?
Artificial Intelligence and Machine Learning refer to any model that can create a result based on supplied data. When moving into the world of Generative AI, we reach models that can create something entirely new after understanding the provided data. The most known instance of generative AI today is ChatGPT. The way it works is that when given two words, the AI can predict the next most probable word. Such a model is driven by a Goal supplied to it by the user. Now imagine taking that same thought process, but instead of text, we apply it to market data.
When provided with rich data that every airline has, Generative AI can understand an airline’s market down to the most granular level and then make market move decisions, taking into account the actions and reactions of all market participants: The airline, The buyers, and the competitors.
Truly understanding demand using AI
Demand is the bread and butter of any revenue management department. If we can forecast and understand demand accurately, we can price correctly and capture the most revenue.
Analysts spend hours upon hours dissecting data to predict how demand will change. The most significant limitation of humans is that we can consider at most 3-5 factors when deciding. When it comes to demand, the amount of factors that need to be considered is in the tens. By feeding the same data airlines use today into a generative AI engine that can digest internal and external data such as weather, stock prices, entertainment shows, and other things that impact demand, airlines can genuinely understand and react to live demand. Instead of five factors per decision, the AI will consider ten or twenty and do it faster and more accurately. A generative AI engine can create tens of thousands of demand curves and discover the most probable one and its demand elasticity.
Dealing with the competition
Competition is one of the most significant impacts on any revenue management decision. The actions of our competitors affect decision-making directly, and the key to success is to understand and foresee what my competition will do. Once again, the knowledge of historical competitor actions can inform us of their future decisions, but what about other factors?
Competitors adapt their pricing strategies, and relying on historical data is not enough anymore. When applying a Generative AI engine to competitive analysis, a brand new dimension of simulating competitor reactions comes into play. Imagine if you could decide on a tentative price, see how your competition reacts, and determine if it was the right decision. Imagine doing that ten thousand times for every single pricing decision, all in milliseconds. This isn’t a dream. It’s done today in e-commerce.
Generative AI engines also learn from live data, so every single pricing decision gives it another data point as to the pricing strategies of their competitors, allowing the forecasting of competitive behaviours to become much simpler and more accurate.
Putting it all together, from decision support to decision making
The possibilities with Generative AI engines are immense, but how can you harness them to your goals? The greater the degrees of freedom given, the greater the result such an engine can produce. An AI engine that accurately forecasts demand, optimizes prices to the fare base level, controls inventory allocation across RBDs, and publishes automatically creates a significant revenue uplift. Such an engine is agnostic to the airline type because it learns the singular market for each airline. A legacy airline and an ultra-low-cost airline are just different markets for the AI to learn. A Generative AI engine is a decision-making machine that can empower airlines to capture hidden and lost revenue by transforming the entire pricing approach.
The power of generative AI
Now, Imagine taking everything above and giving it a voice. By applying existing LLM technologies, You can talk to the Generative Pricing and Inventory Engine. Ask why it made a particular decision, and discuss the best way to increase the load factor by 10% in a certain O/D. Ask it to make you a report about competition performance over the last week, every Monday at 8 am, and send it to your email. Generative AI can empower airlines across all departments, giving a voice to the airline’s private data for the first time.
AI is the future, and the future is already here. With shifting market shares and revenue generation, the first-to-market advantage of airlines willing to embrace generative AI and empower their departments with its possibilities will be evident in the coming years. Fetcherr is leading the charge and bringing the future to airlines today, with Azul and Virgin Atlantic already in production.
Interested in learning more? Join the airlines embracing the future and contact us at info@fetcherr.io. Don’t forget to mark your calendar for September 27th, when we will host a workshop showcasing our system in production and present a case study with one of our customers.
Article by Fetcherr
Also in the news:
Holograms, hyper-reality, and AI enabled AR experiences: Emirates Group demonstrates their forward thinking mindset when it comes to innovative technology.
Unlocking Gen Z engagement: Three essential factors to remember
Four trends to look out for in 2023
In-Flight Connectivity. A Lucrative, Loyalty Building Opportunity