Your airline doesn't have an AI problem. It has a leadership problem.
One of the world's largest network carriers claimed they reduced management headcount by 4% "due to AI adoption." Four percent is attrition. The claim is a better story than admitting what's really happening: weakening demand in some markets, margin pressures and preparing for a softer outlook.
Another global carrier announced 4,000 job cuts by 2030 because of AI — six years out, plenty of time for natural turnover to do the work while they claim the narrative now.
These aren't AI transformations. They're normal business cycles with better PR. But the announcements create real pressure — boards want to talk AI, the street wants proof it's working, and CEOs want to one-up each other.
So we do what the system trains us to do: we call up the consulting firms for a 100-page deck, we launch RFPs for AI solutions, reorganize business teams around tech teams and announce AI pilots to show we're moving.
Meanwhile, the actual work — aligning teams around shared definitions, simplifying data architectures, building trust in the numbers — doesn't get done.
The organizations that will win with AI aren't buying more technology. They're doing the boring work first.
They're getting revenue management, finance and commercial analytics to agree on what constitutes revenue, a channel, a market. They're building unified customer views from data they already have — from the web, from their app, from campaign tools and yes, even from their legacy systems from the 1960s.
The data is all there. The data is all joinable.
The data isn't complicated. The organizations are.
AI won't fix a misaligned organization. It'll just automate confusion.
The path to winning with AI runs through alignment. Alignment creates better data. Better data leads to stronger businesses. We have to have the forethought to make the data work before we try to make AI work.
Making data and AI work for leaders means resisting the pressure to look innovative and having the courage to do the foundational work that actually enables innovation.
Push back on the hype. Focus on alignment. Get your data right, and everything else will follow.