{"id":9711,"date":"2026-01-24T15:33:43","date_gmt":"2026-01-24T15:33:43","guid":{"rendered":"https:\/\/journals.law.unc.edu\/ncjolt\/?p=9711"},"modified":"2026-01-24T15:33:43","modified_gmt":"2026-01-24T15:33:43","slug":"are-you-paying-more-than-your-neighbor-a-look-into-algorithmic-pricing","status":"publish","type":"post","link":"https:\/\/journals.law.unc.edu\/ncjolt\/blogs\/are-you-paying-more-than-your-neighbor-a-look-into-algorithmic-pricing\/","title":{"rendered":"Are You Paying More Than Your Neighbor? A Look into Algorithmic Pricing"},"content":{"rendered":"\n

10:33 AM, Jan. 24, 2026<\/strong><\/p>\n\n\n\n

As Artificial Intelligence (\u201cAI\u201d) rapidly integrates into day-to-day life, this new technology requires humans to grapple with complex questions centered on data privacy and consumer protection. In response to these questions, legislators at the state and federal levels<\/a> have begun introducing and developing a range of bills to regulate AI.<\/p>\n\n\n\n

Prior to AI, businesses had to conduct painstaking market research manually. However, with the advent of AI, businesses can now create algorithms that develop pricing strategies capable of predicting market fluctuations and optimizing revenue<\/a> based on customers\u2019 previous searches, preferences, and experiences.<\/p>\n\n\n\n

Recent advances in technology allow businesses to pursue fluid pricing grounded in \u201cmarket demands, competitive pressures, and broader economic indicators.\u201d<\/a>\u00a0Modern AI algorithms have the ability to change prices in real time for consumers. There are two main types of algorithmic pricing:<\/a> dynamic pricing and personalized pricing.<\/p>\n\n\n\n

Dynamic pricing<\/a> is where prices adjust in real time in response to market fluctuations. An example of dynamic pricing is Uber<\/a> changing prices based on car availability. A recent controversy involving dynamic pricing occurred in August 2025, when Delta<\/a> issued a statement in response to allegations<\/a> that it was using personal data in its AI pricing algorithms. In its statement<\/a>, Delta asserted that its AI algorithm did not set individualized prices based on consumers\u2019 personal data but instead relied on market factors such as customer demand, jet fuel prices, and route performance.<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

Personalized pricing, on the other hand, means customers are charged different prices based on their stored personal data.<\/a> Businesses do this by using personal information, such as current location<\/a>, search history, device type, or recent purchases, to potentially charge different amounts for the same item<\/a>. While personalized pricing offers benefits<\/a>, it also raises concerns for consumers. A common concern<\/a> is that \u201c[a]lgorithmic pricing is usually invisible to consumers, who typically see only the prices and fees they\u2019re offered.\u201d<\/p>\n\n\n\n

In December 2025, a Consumer Report study<\/a> found that Instacart was using pricing algorithms to charge customers different prices for the same item. The study revealed that the same basket of food in Seattle<\/a> could cost up to $10 more than the lowest total grocery bill on Instacart\u2019s platform. This can amount to a difference of approximately $1,200 per year<\/a>. In response to the study\u2019s publication, Instacart paused<\/a> its use of the technology that allowed its app to charge different customers different prices. <\/p>\n\n\n\n

As businesses like Instacart rapidly implement AI pricing algorithms into their products,\u00a0legislators\u00a0<\/a>have backed efforts to prevent AI algorithms from unfairly affecting consumers. For instance, a letter from seven U.S. senators to\u00a0the Federal Trade Commission (\u201cFTC\u201d) stated<\/a>,\u00a0\u201cWe are deeply concerned that Instacart\u2019s pricing tactics may result in higher food prices, less competition, fewer opportunities to comparison shop, more incentives for companies to collect sensitive personal data, and increased customer confusion\u2014potentially in violation of the FTC Act.\u201d<\/p>\n\n\n\n

Such concern raises a question: Should the government merely require transparency when companies implement algorithmic pricing, or should the government prohibit the use of consumers\u2019 data altogether?\u00a0<\/p>\n\n\n\n

In November 2025, New York\u2019s Algorithmic Pricing Disclosure Act (\u201cAct\u201d) went into effect. The Act<\/a> requires that companies using algorithmic pricing must display a disclosure stating \u201c[t]his price was set by an algorithm using your personal data.\u201d Based on this Act, a question remains as to whether disclosure requirements alone are sufficient to protect consumers or whether additional measures are needed.<\/p>\n\n\n\n

[A]lgorithmic pricing is usually invisible to consumers, who typically see only the prices and fees they\u2019re offered<\/p><\/blockquote>\n\n\n\n

In December 2025, the One Fair Price Act (\u201cFair Price Act\u201d), introduced in the U.S. Senate by Senator Ruben Gallego, provided a partial answer to this question. The Fair Price Act<\/a> aims to \u201cprevent companies from being able to use customers\u2019 personal data to set individualized prices,\u201d thus going one step further than New York\u2019s law. The Fair Price Act would still permit dynamic pricing, allowing businesses to modify prices based on supply and demand, while also providing \u201cguardrails for when pricing differences are allowed\u201d<\/a> for specific groups such as military members, seniors, or students.<\/p>\n\n\n\n

Without proper legal safeguards, the hidden nature of these AI pricing algorithms leaves individual consumers in the dark with respect to the prices they see. Over time, as more companies implement this technology in their pricing models, consumers\u2019 privacy may further erode. Therefore, to protect consumers’ privacy and prevent hidden costs, lawmakers must decide whether New York\u2019s Algorithmic Pricing Disclosure Act is sufficient or whether outright limits on personalized pricing, such as those proposed in the One Fair Price Act, are needed to prevent consumer harm.<\/p>\n\n\n\n

Nicholas Ristaino<\/strong><\/p>\n\n\n\n

Nicholas received his undergraduate degree from NC State University, where he majored in Political Science and Business Administration with a concentration in Finance. At the UNC School of Law, Nicholas is a staff member on the North Carolina Journal of Law and Technology. In his free time, he enjoys watching the Carolina Panthers and UNC basketball.<\/p>\n","protected":false},"excerpt":{"rendered":"

Algorithmic pricing is usually invisible to consumers, who typically see only the prices and fees they\u2019re offered<\/p>\n","protected":false},"author":4,"featured_media":9712,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[51],"tags":[676,679,678,623,680,677],"_links":{"self":[{"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/posts\/9711"}],"collection":[{"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/comments?post=9711"}],"version-history":[{"count":2,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/posts\/9711\/revisions"}],"predecessor-version":[{"id":9714,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/posts\/9711\/revisions\/9714"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/media\/9712"}],"wp:attachment":[{"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/media?parent=9711"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/categories?post=9711"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.law.unc.edu\/ncjolt\/wp-json\/wp\/v2\/tags?post=9711"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}