Deloitte’s 2026 Airline CEO Survey lands at a peculiar inflection point. On the one hand, the industry entered the year projecting record passenger volumes, all-time high load factors and $41 billion in global net profit. On the other hand, by mid-year, surging fuel costs, persistent inflation and a delivery backlog exceeding 5,300 aircraft had turned that optimism into a daily fight for margin. The survey’s 21 CEOs are not panicking – but they are recalibrating…hard.
One topic that this report has written all over each of its sections is data. Not data as an aspiration, but data as the operational backbone of every decision that matters right now – from fuel optimization to on-time performance, from dynamic pricing to disruption recovery. What the survey conveys is that the airlines navigating this moment best are not per se those sitting on the largest data sets, but rather the ones that have learned to turn raw operational data into decisions fast enough to matter.
That distinction – between having data and knowing what to do with it – is what we would like to elaborate on in this article.
The AI Pivot Is Real. But It Rests on a Data Foundation.
One of the most striking findings in the survey is how dramatically AI and machine learning have risen on the technology agenda. In a single year, they have moved from trailing data analytics to leading the entire technology investment ranking. Deloitte attributes this partly to the fact that “the foundational data work is far enough along that the conversation has moved to putting AI to work on top of it.”
That sentence deserves to sit with the reader for a moment.
What it means is that AI – for all the urgency airlines are now attaching to it – is not a plug-and-play solution. It is a capability that sits on top of data infrastructure. Without structured, reliable, standardized operational data flowing consistently from the right sources, even the most sophisticated machine learning models will optimize noise rather than signal. The airlines that are genuinely pulling value from AI today are the ones that invested, often quietly, in getting their data house in order first.
This is not a new observation. But in the context of this survey – where AI has suddenly become the industry’s top technology priority – it is a critical one. There is a risk that airlines, under margin pressure and looking for quick wins, reach for AI as a solution before they have resolved the more fundamental question of data quality and data flow.
The Real Insight Behind "Ground Operations Efficiency"
Among the AI use cases gaining most ground in this year’s survey, two stand out beyond the perennial leader of revenue management: sustainability & fuel optimization and airport & ground operations efficiency. These are not coincidental risers. They reflect where CEOs believe untapped margin actually lives – in the operational processes that have historically been the least digitalized and therefore the least visible.
Ground operations is particularly instructive. For decades, the apron has been the least data-rich part of the airline operation. Fueling, loading, handling, servicing – processes that happen at the physical interface between an aircraft and an airport – have largely run on paper and have been ensured through verbal handoffs and manual reconciliation. The data they generate, if captured at all, arrives late, in inconsistent formats and through fragmented channels.
The result is a paradox: some of the most cost-critical processes in aviation are also the ones for which airlines have the least actionable data. Fuel alone represents 20 to 30 percent of total operating costs – and in a year of surging prices, considerably more. Yet many airlines still lack real-time visibility into actual fuel uplifts across their network, making it nearly impossible to optimize tankering decisions, catch discrepancies before they become invoice disputes or model the true cost of a delayed departure.
The CEO prioritization of ground operations as an AI domain is, in effect, an acknowledgment that this data gap needs to close. But AI cannot close it alone. The prerequisite is digitalization at the point of service – capturing structured operational data where it originates, in real time, in formats that can actually feed downstream analytics and decision-making.
Our digital aviation fueling platform aFuel makes exactly that possible. It connects airlines, into-plane agents and fuel suppliers on a single shared platform – replacing paper slips, phone calls and manual reconciliation with electronic data capture at the moment of delivery. So with every fueling event, structured, real-time data such as uplift quantities, delivery confirmations, timestamps or discrepancies is generated and flows immediately into airline systems, enabling the kind of visibility, traceability and downstream optimization that the paper-based world simply cannot support. It thus builds the desperately needed data foundation to analyze and optimize ground operations intelligently. Today, aFuel connects carriers including Lufthansa, Swiss, Cathay Pacific, Finnair, Eurowings, Condor and more with into-plane agents and IT providers across airports
From Data Points to Decisions: The Gap That Still Matters
There is another layer to this challenge that the survey touches on, though perhaps not in those exact terms. Even where operational data exists, the question of what to do with it – how to translate it into decisions that improve performance – remains genuinely hard.
Deloitte’s findings show that on-time performance has surged to the top of the operational agenda, with IROP recovery close behind. These are outcomes. The data inputs that drive them are complex, distributed and time-sensitive: gate readiness, ground service completion, fueling status, catering confirmation, crew positioning. An airline that can see all of these data streams in real time – and that has built the analytical layer to identify which combination of delays will cascade into a missed departure – is in a fundamentally different position from one that reconstructs the picture retrospectively.
The difference is not simply having more data. It is having the right data, connected, in time to act.
This is the work that often goes undiscussed in broader conversations about aviation technology – the patient, unglamorous process of connecting data sources, standardizing formats, building the integrations that allow operational events to flow seamlessly from the point of occurrence to the people and systems that need to respond. It is less exciting than talking about large language models or agentic AI. It is also, in our experience at Information Design, where the real value is built and where most implementations either succeed or stall.
Turning Operational Data Into Strategic Intelligence
What the Deloitte survey ultimately describes is an industry in search of better decision intelligence. The specific tools and use cases vary, but the underlying need is consistent: take the operational complexity of running an airline, extract signal from it, and present it in a form that enables faster, better decisions at every level of the organization.
This is exactly where we have built our expertise over nearly three decades working with carriers across Europe and beyond. Not as a data consultancy in the abstract, but as a company deeply embedded in the specific operational workflows of aviation – where the data is generated, what it means, and how it needs to flow to be useful.
The insight we bring is not just technical. It is domain-specific. Understanding what a fuel uplift discrepancy actually means. Knowing which ground process delays are genuinely predictive of a late departure versus which are recoverable. Recognizing the difference between data that reflects operational reality and data that reflects how a process was supposed to work. These distinctions matter enormously when building analytics that people actually use and act on.
Deloitte’s survey notes that the biggest barriers to AI adoption are not technology or funding – they are talent shortages, cultural resistance and the difficulty of integrating AI into legacy systems. We would add a fourth: the challenge of translating model outputs into decisions that frontline teams can act on with confidence. Analytics that stay in a dashboard and never change a behavior have not delivered value. The last mile – from insight to action – is the hardest part, and it requires operational knowledge as well as technical capability.
It is the challenge our products aIntelligence and aWall are designed to address. aIntelligence is our analytics layer for aviation operations – turning the structured data generated across ground processes into KPIs, trend analyses and anomaly detection that operations and finance teams can actually use. aWall takes this a step further, surfacing the most critical operational intelligence in real time on dedicated display systems at airports and airline operations centers – making the right information visible to the right people at the moment they need it to act. The goal in both cases is the same: not data for its own sake, but intelligence that changes a decision.
The Competitive Landscape Is Being Redrawn Now
Deloitte closes its report with a characteristically sharp observation: competitive landscapes don’t get redrawn after a crisis. They get redrawn during one. The airlines making the right analytical investments today – building the data infrastructure, the integration layer and the decision intelligence that turns operational complexity into competitive advantage – are the ones that will define the industry’s next chapter.
The window for these investments is open right now, and it will not stay open indefinitely. As costs normalize and the immediate pressure eases, the airlines that used this period to strengthen their data foundations will find themselves with capabilities that peers will spend years trying to replicate.
We have seen this pattern before. And we remain convinced that the most durable competitive advantages in aviation are built not in the boardroom, but in the data – specifically, in the ability to see what is actually happening across an operation, understand what it means and act on it before the moment has passed.
That is what we work on every day. And if the 2026 Airline CEO Survey is any guide, it is exactly what the industry needs most right now.
