The severe weather experienced at present in the US has placed significant strain on the airline industry in the country, with knock-on effects of changes to schedules and routes affecting the rest of the world.
It’s at times like this that companies have to respond to queries from customers at a much greater rate than during normal operations, and there are – in the specific case of the air sector – operational decisions that need to be taken quickly, yet inside the strictest safety boundaries.
Several airlines are turning to generative AI to help them during these types of events, and more generally, to help turn them into more efficient and reactive organisations.
Last year, Air France-KLM built a cloud-based generative AI ‘factory’ for use throughout the organisation, which it described as letting it make AI development more consistent and reusable. It formed a partnership with Accenture and Google Cloud for its factory, using it to test and deploy generative AI models. It produces measurable outcomes in ground operations, engineering and maintenance, and customer-facing functions. The partnership group has stated that enterprise deployment of generative AI has increased development speed by more than 35%.
The AI factory was built on earlier work undertaken by the airline and Accenture, which involved migrating core applications to the cloud. Since then, Air France-KLM has created a private AI assistant and RAG tools linking LLMs with internal search to support tasks like diagnosing and repairing aircraft damage.
The factory is also used by employees, who get trained on how to use AI tools in order that they can use the power of LLMs to make a positive impact to the business.
Weather and when AI is used
United Airlines is similarly exploring AI in its operations. In an interview with CIO.com, CIO Jason Birnbaum described AI as a way to “shorten decision cycles” during irregular operations such as the recent outages caused by the current extreme cold snap. The company’s AI journey began with the use of AI to respond to passenger enquiries.
When flights are delayed or cancelled, customer service representatives are expected to respond quickly and informatively, yet retain a company-mandated communication style – honed during the company’s ‘Every Flight Has A Story’ programme. During extended periods of disruption, maintaining the output from what the company terms ‘storytellers’ difficult.
Jason Birnbaum said, “Considering the number of delays versus storytellers, we couldn’t have a person write a new message with every event. So we focused on prioritising the most impactful situations. […] The data piece was simple: the basic facts of the flight and the running chat between the attendants, pilots, gate agents, and the operations people associated with the flight. We fed that information — with additional data on weather, for example — into the AI model, to generate a good draft customer message.”
“The trick…
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