Delta Airlines is ramping up their use of individualized pricing generated by AI.
How do you feel about buying something and paying a price that is set for you personally by all-knowing artificial intelligence? This scenario is getting closer than you might think.
Delta Airlines Has A Plan To Profit
Delta Airlines is betting big on AI to boost profits. It plans to expand AI-determined pricing from 3% to 20% of tickets by year’s end. While executives are excited about “amazingly favorable unit revenues,” they overlook how tone-deaf that will sound to customers on the other side of those transactions.
They are missing a powerful psychological factor that could derail this strategy: the human need for pricing fairness.
According to Fortune, Delta’s long-term goal is to move away from set fares entirely, creating individualized prices for each passenger using AI. “We will have a price that’s available on that flight, on that time, to you, the individual,” president Glen Hauenstein told investors. When customers hear this, who do they think will benefit more – the customer or the airline?
This represents a fundamental shift in the airline industry’s psychological contract with customers. Even outside the airline industry marketing leaders should pay attention.
The Fairness Perception Problem
For decades, airline pricing has operated on a principle of inequality. But, that inequality was mostly transparent.
The person sitting next to you may have paid much more or much less for the same flight. Prices varied based on when you booked, or whether your fare was fully refundable. Booking early was usually cheaper. Booking at the last minute might be far more expensive if few seats remained, or even cheaper if the flight was still half empty. Prices varied continuously based on bookings and predicted demand. The system could result in major fare discrepancies, but it still felt fundamentally fair. The rules applied equally to everyone.
Delta’s AI pricing destroys this perception. When an algorithm determines your personal price based on masses of data unique to you but with no transparency, you’ll likely feel cheated.
The Asymmetric Information Problem
If you’ve ever bought a used auto from a car dealer, you’ve experienced the asymmetric information problem. The salesperson knows far more than you: what’s wrong with the car that may need to be fixed soon, what they paid for it, what comparable cars are selling for, your credit rating and history, the minimum profit the dealership will accept, and much more.
By the time the salesperson juggles the numbers with the vehicle price, financing, dealer add-ons, and trade-in pricing, even savvy buyers walk out suspecting they were taken advantage of. Is it any wonder that used car salespeople are among the least trusted professions? (Only Senators and Members of Congress fare worse!)
Asymmetric information isn’t always bad. It exists in doctor-patient relationships, but most people trust their doctor’s advice. The problem occurs when the party with superior knowledge weaponizes it to take advantage of the other party. The car salesman who sells you a car known to have uncorrected problems or with an exorbitant markup is an example.
Delta Airlines’ Use Of Asymmetric Information
Delta’s AI approach makes used car salespeople look clueless. Their algorithm knows everything. Pricing and availability of competitive flights. Predicted demand for seats. Your credit information. Your flight purchase history. Your price sensitivity. Whether you are pursuing higher loyalty status. Your behaviors in this particular search session. And, likely a dozen (or more) variables I can’t even imagine.
Research in behavioral economics shows that consumers have an innate sense of fairness that, when violated, triggers stronger negative emotions than almost any other commercial transgression. Nobel laureate Daniel Kahneman’s work on fairness theory demonstrates that people will actually reject profitable deals if they perceive the terms as unfair and will pay a cost to punish companies they believe are acting unfairly.
Why Delta Airlines’ AI Pricing Feels Different
“They are trying to see into people’s heads to see how much they’re willing to pay,” said Justin Kloczko of Consumer Watchdog told Fortune. “They are basically hacking our brains.”
Kloczko’s comment captures why AI pricing feels fundamentally different from traditional yield management. When an airline sets prices based on supply and demand, customers understand the logic. When an algorithm analyzes your personal data to extract maximum payment, it feels predatory.
The psychological distinction matters. Traditional pricing discrimination, like student discounts, senior rates, advance purchase fares, etc. feels acceptable because it’s based on transparent and understandable factors. AI pricing that targets you individually based on your perceived willingness to pay and other unknown factors crosses a fairness line. We’ve reached out to Delta for comment.
How Brand Trust Breaks Down
Marketing leaders considering similar AI pricing strategies should understand how trust erosion typically unfolds:
Phase 1: Discovery Shock. The first time customers discover they are quoted two prices based on whether they are logged in or browsing anonymously, the emotional response is immediate. Social media amplifies these discoveries,
Phase 2: Behavioral Adaptation. Customers begin gaming the system—using VPNs, clearing cookies, creating multiple accounts, shopping through third party apps, etc. As travel expert Gary Leff noted in Fortune, this might work in the short-term, but airlines could eventually require logged-in purchases. No longer anonymous, customers would have to “submit to personalized pricing to get extra legroom seats.”
Phase 3: Brand Loyalty Breakdown. When customers realize they must do extra work on every booking to outsmart your pricing algorithm, the relationship fundamentally changes. They shift from brand advocates to adversaries, viewing every interaction through a lens of suspicion. Gartner research showed the corrosive effect of unnecessary customer effort on their loyalty to a brand.
Strategic Implications for CMOs
“AI isn’t just optimizing business operations, but fundamentally rewriting the rules of commerce and consumer experience,” author Matt Britton told Fortune. For marketing leaders, this creates an unprecedented challenge: how do you maintain brand trust while implementing pricing strategies that feel inherently untrustworthy?
1. Transparency as Competitive Advantage
As more companies adopt AI pricing, brands that maintain transparent, predictable pricing could gain significant competitive advantage. The short-term revenue gains from AI optimization may be offset by long-term customer defection to “fair” competitors.
2. The Communication Challenge
Delta told Fortune they have “strict safeguards to ensure compliance with federal law” but wouldn’t specify what those safeguards were. This opacity compounds the trust problem. CMOs implementing AI pricing without damaging customer trust need to be transparent about how the system works, what data it uses, and what protections exist.
3. Segmentation Strategy
Consider limiting AI pricing to specific segments or products where pricing variability is already expected. Delta’s wholesale shift risks alienating their most valuable customers—business travelers who prize predictability.
4. Positive Price Framing
Rather than calculating individual prices for each customers, frame a lower price for some customers as a discount. A customer who is shopping and gets a popup for a “10% Discount, Today Only!” is less likely to see it as hostile manipulation even if they don’t see it the next time.
5. The Loyalty Paradox
Leff predicts airlines might require customers to be “fully within their ecosystem to gain the benefits of that system.” This could make for a dangerous dynamic where your best customers, those with the most data and transactions, may also be the most exploited by pricing algorithms. Loyalty to a brand could be penalized.
The Future Of AI Pricing
Senator Ruben Gallego has already called Delta’s practice “predatory pricing,” signaling potential regulatory measures to restrict it. But regulation may be the least of Delta’s problems from AI pricing. The greater risk is a loss of customer trust and erosion of loyalty.
CMOs considering AI pricing must answer a critical question: Is maximizing revenue from each transaction worth risking the psychological and emotional foundation of customer relationships?
Delta Airline’s AI pricing experiment may indeed produce “amazingly favorable unit revenues” in the short term. But if the practice sparks a trust crisis among customers who feel manipulated or unfairly treated, those gains could be offset by defections and bad publicity.