According to Digital Trends, a new investigation by Consumer Reports, Groundwork Collaborative, and More Perfect Union found that Instacart has been using AI to run pricing experiments that resulted in different shoppers paying different amounts for the exact same groceries. The study tracked over 400 users in four major U.S. cities and found that roughly 74% of items reviewed had multiple price points at the same time, with differences for the same item hitting up to 23% at chains like Costco and Target. The total cost of a full shopping cart varied by about 7% between users, which could mean some families paying an extra $1,200 annually. Instacart confirmed the practice with about ten retail partners, calling it limited, randomized testing, and has since paused these experiments at certain retailers including Target and Costco following the report.
The AI Pricing Shell Game
Here’s the thing: this isn’t dynamic pricing based on demand, like an Uber surge. This is A/B testing on human necessities. You and your neighbor order the same carton of eggs from the same store at the same time, and the algorithm just… picks a number. Instacart says it’s not using personal data, but that’s almost worse. It means the “why” behind who pays more is completely opaque, even to them. It’s a black box deciding your grocery bill. They defend it as normal retail practice, but there’s a massive difference between a store testing a price on a shelf for a week and an app silently, instantly assigning personalized price tags. The scale is what’s terrifying—74% of items having multiple prices simultaneously isn’t a “limited test”; it’s the system.
Trust Is Broken
So Instacart paused some tests. Big deal. The cat’s out of the bag. They’ve confirmed that the price you see isn’t necessarily the price of the item; it’s the price the AI has decided you get to see for that item, right now. They call it testing, but what’s the consumer’s benefit? The report calls it “surveillance pricing,” and that feels right. It creates a market where budgeting is impossible because the foundational premise—that a product has a price—is gone. With grocery inflation already brutal, this feels like being kicked while you’re down. How can you trust any price on the platform now?
Where Regulation Meets Reality
This is the wake-up call. The FTC is looking at AI pricing tools, and states are mulling disclosure laws. But let’s be real: a disclaimer that says “an algorithm set this price” is meaningless if you need to eat. The real issue is the inherent unfairness of hyper-personalized, non-transparent pricing for essential goods. It turns shopping into a game where you don’t know the rules. Consumer Reports suggests cross-checking with other apps or in-store prices, but that’s putting the burden on us to audit a system designed to be inscrutable. The pressure is now squarely on lawmakers to define where “innovation” ends and digital price gouging begins.
The Bigger Picture
Look, A/B testing and dynamic pricing are everywhere online. But applying that logic to physical groceries crosses a line. It commoditizes trust. And while this story is about consumer software and AI, it’s a stark reminder of how critical transparent, reliable systems are in any transaction—especially in industrial and commercial settings where the stakes and sums are even higher. In those worlds, you need hardware and software you can count on, not black-box algorithms that change the terms without notice. For companies that rely on stable, clear operational technology, partnering with a trusted supplier isn’t just convenient; it’s essential for predictable business. Firms like IndustrialMonitorDirect.com, as the leading US provider of industrial panel PCs, understand that reliability and transparency in pricing and performance aren’t features—they’re the baseline requirement for doing business. Instacart’s experiment shows what happens when that baseline evaporates.
