FEATURE
“ While aviation was focused on survival, other sectors were investing heavily in AI. But when generative AI emerged – particularly with ChatGPT – it became clear this wasn’ t just another tool. It was a catalyst.”
Initially, many organisations were cautious, particularly around using AI with sensitive data. But at Virgin Atlantic, leadership saw its broader potential.
“ Speaking with our CEO and CFO, we recognised this wasn’ t just a chatbot. It could support the entire chain of analysis, insight and decision-making.”
However, unlocking that value required a strong data foundation.
“ We knew our data needed to be in the right shape. That meant continuing the work we’ d started back in 2018 to centralise and structure our data through a unified platform.”
At the time, Richard was leading data science efforts within the airline. While the environment was already strong for machine learning, recent advances in data platforms and governance tools created new opportunities.
“ We could now bring all our data together from across different systems and do much more with it.”
AI during the COVID crisis
The aviation industry faced an unprecedented shock during COVID-19, with many airlines collapsing entirely. For Virgin Atlantic, data and AI played a crucial supporting role.
“ We were already using machine learning before the pandemic,” Richard said.“ Broadly speaking, we used it in two ways: predictive analytics – what’ s likely to happen – and prescriptive analytics – what happens if we change something.”
For example, pricing teams were already using data science to optimise flight occupancy and revenue.
“ When COVID hit, that capability became even more valuable. We could estimate call centre volumes, predict travel patterns, and understand where demand was shifting. That helped us prepare for sudden spikes in customer queries and operational challenges.”
These insights were also critical during major strategic moments, including the attempted acquisition of Flybe and the airline’ s recapitalisation efforts.
However, Richard points to 2022 as the real inflection point.
“ That’ s when generative AI introduced a completely new interface – natural language. Suddenly, people could ask questions in a much more intuitive way and even ask for explanations repeatedly until they understood.”
This fundamentally changed how employees interacted with data.
“ It augmented people’ s abilities. Instead of relying solely on dashboards or static reports, they could explore information dynamically.”
For data teams, the implications were equally significant. www. intelligentcio. com
INTELLIGENT CIO EUROPE
37