Why Aer Lingus prioritized a data-fluent culture to modernize its 90-year legacy
by Aly McGue
Aviation is one of the most data-intensive industries on the planet. Every flight generates a torrent of information: fuel consumption, engine telemetry, passenger preferences, real-time weather patterns and more. For Aer Lingus, Ireland’s flagship carrier, this complexity is compounded by a storied history. Many airlines still operate on systems built decades ago, where data is trapped in departmental silos. In this environment, making simple decisions can require manual data extraction and weeks of analysis.
Dave O’Donovan, Chief Digital, Data & Transformation Officer, Aer Lingus, is leading this charge. Under his leadership, Aer Lingus has undergone a radical shift, redirecting a significant portion of its capital spend away from traditional IT maintenance and toward a unified platform powered by Databricks.
I sat down with Dave to discuss the mechanics of this transformation. We explored how Aer Lingus is moving past legacy to a fully digitally led customer experience, and why he believes the secret to AI success is data literacy.
Aly McGue: Aer Lingus is 90 years old. That is an incredible milestone, but it also comes with the challenge of legacy systems and processes. How are you framing the company's mission today in the context of a rapidly evolving digital landscape?
Dave O’Donovan: It’s a fascinating time for us. Aer Lingus is Ireland’s window to the world. We have a massive short-haul network across Europe, and we’re actually the second-largest European carrier on the North Atlantic by US destinations served. But being 90 years old means we have systems and mindsets that have matured over decades.
Our mission now is to maintain that famous “warm welcome” and caring brand identity while meeting the expectations of a traveler who is more digitally savvy than ever and wants premium experiences. That forces us to ask: How do we offer a self-service, digital-first experience that still feels like Aer Lingus? The answer, invariably, is data.
Aly: You’ve made a very bold move recently by redirecting a sizeable percentage of your IT and change spend specifically toward data. What led to that “all-in” moment?
Dave: It was a collective decision at the management committee level about 18 months ago. We reached a point where we realized that understanding how to leverage AI is no longer a “nice to have.”
For years, many companies, including airlines, could get away with under-utilizing their data. But the pace of AI evolution has been like gasoline on a fire. We decided that instead of chasing every new “shiny thing” our competitors announced, we would stop and lay the foundations. We’ve spent the last year and a half focused on the platform, governance, data quality and, most importantly, data literacy. If you don't have those solid foundations, any AI you build is just a house of cards.
Aly: Many organizations struggle with the transition from legacy data warehouses to a modern architecture. How did your starting point at Aer Lingus influence your choice to go with Databricks?
Dave: Strangely, we felt lucky that we were a bit slower to move than some of our peers. We hadn't made massive investments in the “first wave” of cloud data tools, so we didn't have to worry about writing off recent sunk costs. We still had many legacy on-premises warehouses.
When we looked at the market, it had matured. It was clear that Databricks offered a “soup to nuts” solution. We could go all-in on a single lakehouse architecture. What really clinched it for me wasn't just the feedback from our data engineers — who loved the performance — but the vision for democratizing data. I’m excited about things like Databricks' data warehousing platform and Databricks Genie. These tools allow business users to ask questions of the data in plain English. That is the only way to truly scale.
Aly: You mentioned the “bottleneck” of legacy systems. If you could snap your fingers and remove one obstacle between your data and a final decision, what would it be?
Dave: It would be the physical extraction of data from systems that are “60 years young,” as we like to say. These legacy systems are fantastic at what they were built to do — running an airline safely — but they weren't built for the age of generative AI.
We need to move from a world where a department says, “This is my data, I own it,” to a world where data is a shared, holistic asset used to improve the entire operation.
Aly: Let’s talk about that human element. You’ve invested heavily in a “Data Literacy Academy.” Why is that such a priority for an airline executive?
Dave: Because tools are only half the battle. You can have the best LLM or the fastest compute in the world, but if your teams don't have the intuition or the skills to use them, you’ve gained nothing.
We partnered with a UK-based group to build a custom curriculum. We’ve done everything: online training, in-person workshops, and even recording our own podcasts. But even with all that, you have to push it every single day. It has to be top-down. Our CEO is constantly encouraging teams to think about data literacy. We try to provide “bite-sized” chunks of information that people can use in their day jobs immediately.
My goal is that, in five years, “citizen developers” will be the norm at Aer Lingus. If we still have a situation where a business leader doesn't know how to exploit data to run their department, then I’ve failed in my role.
Aly: In an industry like aviation, “real-time” is a requirement. Where are you seeing the biggest impact of real-time insights today?
Dave: The Operation Control Center (OCC) is the heart of the airline. About 24 hours out from a flight, the variables start moving fast: weather patterns change, crew availability shifts and aircraft maintenance issues might pop up.
In the past, these decisions were often made in silos. Now, by pulling data from various sensors across the operation into a unified platform, our OCC teams can see the “full picture” in real time. If we have to cancel a flight or take a delay, we want that decision to be based on the most current data possible to minimize disruption for our customers.
On the commercial side, it’s just as vital. We sell over 80% of our tickets through direct digital channels. We are a high-volume retail platform. Being able to use real-time insights to adjust pricing — ensuring we maximize our load while also maximizing yield — is a massive competitive advantage.
Aly: How are you experimenting with AI agents today? Do you have a specific use case in mind?
Dave: We’re starting with something “nice and simple” but incredibly common: business case development. In any large organization, you spend a huge amount of time writing business cases to get funding.
We are looking at an agentic workflow where an agent helps you craft the case. Then, we want a “CFO agent” to review the case and identify exactly what the CFO will ask. It’s a great way to stress-test our internal logic before we ever even step into the meeting room.
Aly: With the pace of change being so fast, how do you balance that urgent need to “scale now” with the reality of experimentation?
Dave: It’s a delicate balance. It’s very easy to get distracted by “shiny things” to keep your board or CEO happy in the short term. But you can't lock yourself in a closet for 18 months to build the “perfect” platform either.
I follow a 75/25 rule. About 75% of our capacity is focused on the long-term foundational strategy — getting the data quality and Unity Catalog governance right. The other 25% is focused on innovation and rapid market value growth. You need those small wins to maintain momentum and keep the business engaged. We even set up a dedicated “Continuous Improvement” team of about 20 people who go around to different departments — finance, customer care, operations — and redefine processes so they are “AI-ready.”
Aly: Finally, what is your advice to other CDIOs who feel the pressure of this AI hype cycle?
Dave: Don't focus on being “future-proof,” because you can't be. The technology changes every six to 12 months. Instead, focus on being “pivot-ready.”
Partner with platforms like Databricks that are built on open standards and open source. That gives you the flexibility to change direction as the market evolves. And most importantly, invest in your people. The most valuable people in my organization are those with curiosity, intuition and creativity. In an era where technology is becoming commoditized, those human qualities are your only true competitive advantage.
Dave’s approach at Aer Lingus serves as a masterclass in modern digital leadership. While the industry fixates on the generative potential of AI, he has focused his mandate on the one variable that determines an organization's ultimate ceiling: its people.
By treating data literacy as a business-wide imperative rather than a technical elective, Aer Lingus is solving the fundamental challenge of the AI era. They aren't just modernizing a legacy airline; they are building a resilient, data-fluent culture where every employee is equipped to turn raw information into operational excellence, in a sector where seconds matter in decision-making. That cultural foundation is the ultimate competitive moat.
To discover how more than 25 industry experts are charting a course toward successful AI deployment, access the “Making AI Deliver” report from Economist Enterprise, produced with support from Databricks.
Watch the full interview with Dave O’Donovan below
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