AI pricing in airlines raises big questions. Here's what we told The Independent

As Delta Air Lines accelerates toward AI-driven pricing, aiming to algorithmically price 20% of flights by year’s end, industry voices are weighing in on what this means for passengers and the broader future of personalized pricing. Among those quoted in The Independent’s recent feature on the topic is Priceagent board member Philip Carls, who brings deep pricing expertise from his previous leadership roles at Amazon and Walmart.

Philip’s perspective adds a critical layer of context to what many are calling an inflection point in travel pricing. While Delta and its AI partner Fetcherr promote this as a “super-analyst” approach to match fares to willingness to pay, Philip sees both opportunity and red flags. He says that this is terrible news for passengers but good news for shareholders, as it moves pricing to a far more granular level based on individual browsing behavior and income estimates.

Pricing: smarter or sneakier?

Delta’s model is a hyper-personalized extension of dynamic pricing. Today’s airline prices already fluctuate by day, route, and demand. But Delta’s next-gen system will analyze data such as past purchases, loyalty status, and even web cookies to determine what you personally might be willing to pay.

Philip acknowledges there may be upsides for deal-seekers, telling The Independent:

‍"There may be lower prices for some customers. For instance, budget-conscious travelers may see discounted fares to incentivise bookings, and frequent fliers could get exclusive discounts or upgrades, with some customers benefitting from dynamic deals if Delta uses data to offer last-minute discounts to fill seats."

But the flip side is equally important. He told us that there will be higher prices for others, such as business travelers, last-minute bookers, and high-income users who may face inflated fares.

Trust on the line

One of the biggest risks, according to Philip, is passenger trust. Unlike traditional pricing, passengers won’t know if they’re getting a fair deal, or being targeted. This growing perception of opacity could spark backlash, especially when two people sitting in adjacent seats paid wildly different fares based on algorithmic profiling.

It’s a concern echoed across the industry. “If Delta's AI knows you consistently book premium cabins, why wouldn’t it test higher price points?” asked another expert in the same article.

Philip points out the potential for broader reputational damage: The largest risk is from class action lawsuits of customers being unfairly targeted by AI. It may be, for instance, that where specific races, classes or genders feel they are being unfairly treated, they will sue.

Data privacy and regulatory risk

The AI model fueling Delta’s pricing relies heavily on behavioral tracking, raising serious privacy concerns. Using extensive data tracking, from purchase history to location and browsing habits, raises GDPR and ethical questions.

That’s particularly thorny when viewed through the lens of global regulation. While this type of AI-driven pricing is broadly legal in the United States, its use in the EU and UK is more restricted due to GDPR and tighter consumer regulations.

Strategic uncertainty ahead

Even beyond privacy and pricing ethics, there are unresolved questions about implementation. How will AI-based pricing interact with travel aggregators, third-party sellers, or alliance partners like Air France or KLM? What happens if competitors adopt similar models? Philip says there’s only so much upside Delta can charge before someone switches and flies a different airline.

Why it matters

Philip’s comments come at a pivotal moment for brands across industries exploring AI in pricing. His warning: if these models sacrifice transparency and fairness for short-term profit, the long-term damage to brand trust, customer loyalty, and legal standing could be significant.

At Priceagent, we believe the future of pricing must balance innovation with integrity. AI can be a powerful tool, but only when grounded in transparency, consumer protection, and ethical data use.

Delta’s experiment may set the tone for what’s ahead. Whether it’s a leap forward or a cautionary tale will depend on how (and for whom) the algorithm ultimately serves.

‍