By Kris Glabinski VP Strategy, Aggregate Intelligence (Formerly European Distribution Manager, British Airways)
When I served as the European Distribution Manager for British Airways in the early 2000s, the world of airline data operated on a foundation of structural rigidity and high certainty. Today, leading strategy at Aggregate Intelligence in 2026, the modern data intelligence provider for the airlines, I look back at that time and realize we were living in a “deterministic era”. Over the last two decades, the industry has undergone a profound philosophical shift, moving from a centralized monolith to a fragmented mosaic.
My personal evolution mirrors this industry trajectory. To understand the complexity of modern data intelligence, we have to understand the simpler world we left behind.
The Era of “Granted” Data (2008)
When I departed British Airways in 2008, the distribution landscape was dominated by an oligopoly of Global Distribution Systems (GDS). These providers acted as the undisputed clearinghouses for global inventory.
In that environment, my interaction with data was passive. I treated GDS data as “granted”—an immutable byproduct of the transaction. We filed fares and operated within fixed price ladders using pre-defined Booking Designators. The “truth” of a price was singular, filed, and retrievable from a single pipe. We never questioned the veracity of a fare displayed on a green screen because, for all intents and purposes, the GDS was the market.
The Great Fragmentation
The dissolution of this singular truth didn’t happen overnight. It began with the “disaggregation” fostered by Low-Cost Carriers (LCCs) in Europe, which proved that high-volume sales could occur entirely outside the GDS ecosystem. This created the first major blind spot in traditional data feeds.
This was accelerated by the introduction of IATA’s New Distribution Capability (NDC) in 2012. NDC signaled a shift from static EDIFACT messaging to dynamic XML standards, allowing airlines to decouple offer creation from legacy infrastructure and act as true retailers.
2026: The Stochastic Turn
Standing here in 2026, the static certainty of my days at BA has been replaced by dynamic complexity. My own cognitive evolution has had to shift from rule-based logic to understanding reinforcement learning and AI.
We have entered the age of “Continuous Pricing”. Today, technologies from providers like Kambr, Maxamation, and Citizenplane utilize AI to analyze real-time demand elasticity, calculating optimal prices in milliseconds. In this environment, a price is no longer a static integer filed weeks ago; it is a fluid variable calculated the moment a request is made.
For a data strategist, this requires a fundamental change in mentality. I can no longer rely only on “filed” fares as a proxy for market rates. In a world of continuous pricing, the “actual” fare—the price front-facing the customer—is the second metric that matters.
The New Truth is Aggregated
This evolution has changed the definition of “Fare Intelligence.” In 2008, the value of data was in its access; in 2026, the value is found in its aggregation.
Because of the LCC market gap and dynamic offers that bypass legacy systems, GDS data alone now may provide an incomplete picture of the market. To find the truth today, we must synthesize multiple data streams:
- Filed Fares: We still look to GDS/API data for interline and traditional agency flows.
- Actual Fares: We must simultaneously collect data from Brand.com websites, Online Travel Agencies (OTAs), and Metasearch Engines (MSEs) to capture the full spectrum of offers.
Conclusion
In 2008, I viewed data as a static utility—a single truth to be consumed. In 2026, I view data as a complex mosaic that must be actively constructed. The widespread adoption of AI has made the market more efficient, but less transparent to the unequipped observer.
For modern airlines and tech providers, the lesson is clear: Truth is no longer given; it is aggregated. Only by embracing this multi-source complexity can we navigate the probabilistic future of airline distribution.
Kris Glabinski
VP Strategy
Aggregate Intelligence
