EXPLAINERFeatures|Science and Technology‘Surveillance pricing’: Why you might be paying more than your neighbourAre retailers using AI to access customers’ personal data and set higher prices for those they think will pay more?

AI and Dynamic Pricing in the Retail Sector

In July, Delta Air Lines disclosed that approximately 3% of its domestic fare pricing is determined using artificial intelligence (AI), with plans to expand this figure to 20% by the end of the year. This announcement has sparked concerns about the potential use of customer data in determining prices. In response, US Senators Mark Warner, Ruben Gallego, and Richard Blumenthal have requested further information from Delta regarding its AI-driven pricing strategies.

Delta has confirmed the use of AI in pricing but denies employing it for discriminatory pricing practices. Former Federal Trade Commission Chair Lina Khan has noted that some companies can utilize personal data to predict a consumer's "pain point," the maximum price they are willing to pay for a product or service.

Surveillance Pricing: Definition and Mechanisms

Surveillance pricing refers to the practice of monitoring consumer data to set individualized prices, aiming to maximize profits. Access to personal information allows retailers to charge consumers the highest price they are perceived to be willing to pay. This practice is enabled by big data and algorithmic price discrimination, which categorizes consumers into finer subgroups, each with tailored pricing.

Technical Aspects of Surveillance Pricing

Retailers gather data through various means, such as account registrations, email sign-ups, and online purchases. Additional tracking involves web pixels that monitor digital signals like IP addresses, device types, and browsing habits. This data is used to assess consumer behavior and set prices accordingly.

Targeting Specific Consumer Behaviors: Retailers may use data to target inexperienced buyers, rushed consumers, or exclude loyal customers from discounts. Analyzing Consumer Interactions: Actions like adding items to a cart without purchasing can indicate price sensitivity. Video Engagement and Advertising: Retailers can use video engagement metrics to target consumers more likely to make purchases.

Surveillance pricing raises questions about legality and fairness. In 2025, US state legislators introduced numerous bills aimed at regulating algorithmic pricing. Notable legislation includes New York's ban on undisclosed personalized pricing and Ohio's requirement for businesses to disclose algorithmic pricing to consumers. The UK's Digital Markets, Competition and Consumers Act empowers regulators to fine companies for unfair pricing practices.

Consumers can protect themselves from price discrimination by utilizing private browsing, opting out of tracking, and clearing cookies. However, these measures may not fully prevent data collection due to advanced tracking technologies like device fingerprinting. Advocacy groups recommend demanding transparency from retailers about their data usage in pricing decisions.

Based on reporting by Al Jazeera.