Consumer apprehension grows as US retailers adopt AI-assisted pricing tools

Read the original at Toronto Star ↗
Cite

D'innocenzio, A., & Durbin, D. a. (2026, October 18). Consumer apprehension grows as US retailers adopt AI-assisted pricing tools. Toronto Star. https://www.thestar.com/news/world/united-states/consumer-apprehension-grows-as-us-retailers-adopt-ai-assisted-pricing-tools/article_42d15fc7-3b87-529d-a402-35a943826a45.html

Dated from the outlet's own feed. Check the original for its byline.

Toronto Star · collected 2026-10-18 · by Anne D'innocenzio, Dee-ann Durbin

Quick Summary

Consumers are growing increasingly concerned about the use of AI and digital tools by retailers for pricing products. Digital price tags and AI algorithms predict customer responses and set prices dynamically, leading to confusion over whether different customers see varying prices for the same items. Walmart’s CEO has defended their use of digital price tags as a way to keep prices updated without raising them based on individual shopper data or external factors like weather. However, lack of transparency about how personal data is used by companies has fueled consumer suspicion and misinformation online.
Written locally by qwen2.5:14b on 2026-10-18, using this article's own text rather than the other coverage of the same event (that is the story summary below).

AI analysis runs on qwen2.5:14b, locally

Story summary

As of October 18, 2026, U.S. consumers are increasingly frustrated and confused by retailers' adoption of AI-assisted pricing tools. Digital price tags in grocery aisles are rapidly replacing traditional paper ones, while algorithms predict customer responses to set prices dynamically. Terms like "dynamic pricing" and "surveillance pricing" are causing anxiety on social media, with users questioning if different people receive different prices for the same product. Americans accustomed to fluctuating prices for travel bookings are now concerned about everyday spending influenced by opaque algorithms that collect personal data without clear consent. Katie Thomas from Kearney’s internal consumer behavior think tank highlights tensions over who holds power in this AI-driven pricing environment: companies or shoppers. Companies argue that some of these concerns arise from misunderstandings about how their technology works, but the National Conference of State Legislatures is considering legislation to address growing public apprehension.

Written for “Consumer Concern Over Ai Pricing Tools” on 2026-10-18, grounded in this article and the 0 other(s) covering the same event.
Why this leaning score
The article's own words the score was based on. Each is quoted verbatim and was checked against the article text before being stored, so you can find it in the original.
Reading Leans left (beta estimate) Confidence high 1 quote(s) discarded as not found in the article
Leaning: leans left for article 88432 (high confidence, 4 verified quotes) · logged 2026-10-18

Story

📰 Consumer Concern Over Ai Pricing Tools
Economy/Business · 1 article(s) covering the same event.

Compared with similar articles

This article reads leans left and hedges 12% of its claims. Each row says how that neighbour differs.
CBS News
⚖️ Leans left 🔴 50% hedged 1 of 2 📰 publisher trust 66
“The articles discuss similar concerns but cover different time periods and contexts regarding AI in retail pricing.”
How this article was measured signals, leaning charts, publisher record, byline, topics and claims

Signals How these are calculated →

Claims extracted
64
sentences that state something as happening or true
Uncertain
12%
8 of 64 hedged ("reportedly", "may", "according to")
Leaning
Leans left
of the writing, not the subject · beta estimate
Publisher signals
63/100
Toronto Star's corrections and hedging, across everything collected from it. Not a measure of accuracy.
Outlets on this story
1
Economy/Business
Same framing elsewhere
1
articles that frame the event the way this one does
Analyzed 2026-10-18 · how these are computed

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Publisher

Toronto Star · 8000 article(s) · 22 correction(s) detected
Running correction rate · 22 correction(s)
2026-10-07
Correction
2026-09-24
Correction

Who wrote this

Anne D'innocenzio
5 article(s) here · 1 carrying a prediction
🔮 Artificial intelligence tools help businesses decide what to charge by predicting how customers might respond.
🔮 The Trump administration on Monday plans to release new fuel economy standards that would relax regulatory requirements for automakers to control pollution from gasoline-powered cars and light trucks.
🔮 In a statement posted on the company’s website, Walmart Inc.‘s CEO John Furner vowed that the Bentonville, Arkansas-based retailer isn’t using personal information like income, shopping history or a customer’s willingness to pay to set prices, and it won’t be doing so in the future either.
Also by Anne D'innocenzio
Nothing else under this byline is closely related to this article, so these are simply their most recent.
Dee-ann Durbin
5 article(s) here · 1 carrying a prediction
🔮 Artificial intelligence tools help businesses decide what to charge by predicting how customers might respond.
🔮 Shoppers may not be spared indefinitely, though.
🔮 Starbucks is facing a consumer lawsuit over claims that the protein drinks labeled “sugar-free” on its cafe menus may actually contain more sugar than a Reese’s peanut butter cup.
🔮 But a taste for a cheap, crowd-pleasing meal may be something the two leaders share.
Also by Dee-ann Durbin
Nothing else under this byline is closely related to this article, so these are simply their most recent.

Topics

Americans Kearney U.S. Walmart the National Conference of State Legislatures

Subjects

U.S. GPE · 4× Walmart ORG · 3× Americans NORP · 1× Furner PERSON · 1× John Furner PERSON · 1× Katie Thomas PERSON · 1× Kearney ORG · 1× The Federal Trade Commission ORG · 1× Thomas PERSON · 1× the National Conference of State Legislatures ORG · 1×

Narrative

“There are major tensions happening right now between who’s really going to have the power with some of these algorithms and usage of bots and AI: the companies or the shopper,” said Katie Thomas, who leads an internal consumer behavior think tank at the management consulting firm Kearney.
framing: assertive · carried by 1 article(s) · first seen 2026-10-18
🔮 Artificial intelligence tools help businesses decide what to charge by predicting how customers might respond.
2026-10-18 · Toronto Star
Consumer apprehension grows as US retailers adopt AI-assisted pricing tools · assertive framing

Claims (64 extracted, 8 hedged)

U.S. consumers aren’t just frustrated with high prices. asserted
consumers → frustrate → prices
They’re angry and confused about the increasingly high-tech ways that restaurant chains and major retailers are setting those prices. asserted
chains → ’re → prices
Digital price tags are rapidly replacing paper ones in grocery aisles. asserted
tags → replace → aisles
Artificial intelligence tools help businesses decide what to charge by predicting how customers might respond. uncertain
customers → help → what
Terms like “dynamic pricing” and “surveillance pricing” are stirring anxiety on social media, where users wonder if different people are getting different prices for the same product. asserted
people → stir → product
Americans have grown accustomed to changing prices when booking flights, hotel rooms and rides, but the prospect of everyday spending shaped by algorithms they don’t understand and personal data they may not realize they’re sharing has touched a nerve. uncertain
they → grow → nerve
“There are major tensions happening right now between who’s really going to have the power with some of these algorithms and usage of bots and AI: the companies or the shopper,” said Katie Thomas, who leads an internal consumer behavior think tank at the management consulting firm Kearney. asserted
who → be → firm
Companies using the technology say some concerns stem from misconceptions about how their pricing tools work. asserted
tools → use → misconceptions
Walmart CEO John Furner said in a blog post last month that digital price tags save workers’ time and keep prices up to date. asserted
tags → say → date
He said the labels aren’t used to raise prices based on the weather, time of day or individual shopper. asserted
labels → say → day
“We price the product, not the person,” Furner wrote. asserted
Furner → price → product
But companies aren’t always transparent about the customer data they collect and how it’s used, which has made consumers suspicious and led to speculation. asserted
consumers → collect → speculation
For example, social media posts falsely imply that electronic shelf labels Walmart plans to put in all its U.S. stores scan shoppers’ faces or cellphones to set individualized prices, Thomas said. asserted
Thomas → imply → prices
Lawmakers and regulators are taking action. asserted
Lawmakers → take → action
Legislators in at least 30 states have considered pricing bills this year, including measures addressing algorithmic and personalized pricing, according to the National Conference of State Legislatures. uncertain
Legislators → consider → Legislatures
The Federal Trade Commission has proposed an enforcement policy warning businesses that failing to disclose their use of personal data to set individualized prices could violate consumer protection law. uncertain
failing → propose → law
Here are some of the pricing practices and technologies drawing scrutiny. asserted
some → draw → scrutiny
Dynamic pricing can raise and lower prices What it is: Dynamic pricing means adjusting prices in response to changing market conditions, including supply and demand. asserted
pricing → raise → supply
An airline that adjusts ticket prices as departures approach is using dynamic pricing. asserted
departures → adjust → pricing
Uber’s practice of lifting fares when demand outstrips the supply of available drivers, such as during rush hour, is a type of dynamic pricing known as surge pricing. asserted
demand → lift → pricing
Why it matters: Frequent price changes extend well beyond food. asserted
changes → matter → food
Decodo, a web data company, tracked price changes in 2025 across products ranging from electronics to clothing and home improvement supplies. asserted
Decodo → track → clothing
About half the U.S. changes it recorded were decreases, contrary to consumers’ assumptions that dynamic pricing only raises prices, said Gabriele Vitke, a senior product marketing manager. asserted
Vitke → record → prices
Digital price labels are coming to more US stores What they are: Digital displays that let stores update shelf prices electronically instead of replacing paper tags. Why it matters: asserted
it → come → tags
Digital price labels, long used in Europe and Asia, are drawing more attention as they spread to major U.S. retailers like Walmart and Whole Foods. asserted
they → use → Walmart
Consumer advocates have argued that digital labels could eventually be used for surge pricing or personalized pricing. uncertain
labels → argue → pricing
Labor unions also have opposed the technology. asserted
unions → oppose → technology
The electronic shelf labels make frequent changes easier but don’t necessarily lead to higher prices during periods of strong demand. asserted
changes → make → demand
Retailers typically update electronic shelf prices on a regular schedule, often weekly, because shoppers value consistency, said Asa Farquhar of Relex Solutions, a retail technology company. asserted
Farquhar → update → Solutions
Researchers who tracked prices at an unnamed grocery chain found “virtually no surge pricing” after the labels were introduced. “Changing prices throughout the day, the way airlines or rideshare apps do, is exceedingly rare in grocery and general merchandise today,” Farquhar said. asserted
Farquhar → track → merchandise
Personalized pricing, also called surveillance pricing, draws on customer data What it is: Personalized pricing means offering customers different prices and discounts based on their locations, incomes, web-browsing habits and other information about individuals or groups of shoppers. asserted
pricing → call → shoppers
Some advocacy groups and regulators use the term “surveillance pricing” for the same practice. asserted
groups → use → practice
Why it matters: asserted
it → matter → ?
It’s unclear how widely businesses use personal information to customize prices. uncertain
businesses → ’ → prices
An FTC staff report released in January 2025 found that intermediaries offering tools that can tailor prices and promotions worked with at least 250 clients, including grocery and clothing retailers. asserted
that → release → retailers
Lawmakers in Maryland, New Jersey and Connecticut recently enacted restrictions on using shoppers’ personal data to determine what they pay. asserted
they → enact → what
The Maryland and New Jersey laws focus on groceries, with exceptions for certain loyalty discounts and other promotional offers. asserted
laws → focus → discounts
Connecticut’s legislation covers a broader range of retail purchases. asserted
legislation → cover → purchases
California prosecutors sued Target in 2022, alleging that the retailer’s app displayed lower prices before shoppers entered stores and raised them once they were inside. asserted
they → sue → them
Target agreed to a $5 million settlement and a ban on using so-called geofencing technology to increase prices. asserted
Target → agree → prices
…and 24 more, not listed.
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