A new study from Columbia Law School’s Center for Law and the Economy reveals that AI shopping assistants from Amazon and Walmart can detect false “Made in USA” labels but choose not to alert consumers or remove the listings. The research, the first published work from the think tank led by former Federal Trade Commission (FTC) chair Lina Khan, highlights a troubling gap between AI capability and corporate action.
What Happened: AI Knew but Stayed Silent
Researchers at the Columbia center directly queried both AI assistants, pointing them to product listings where a prominent “Made in USA” badge conflicted with import details buried further down the page. The assistants could identify the inconsistency but did nothing about it. The study also found such mismatches are common across both platforms, making the silence harder to dismiss as an edge case.
When asked why their companies weren’t acting on what the technology could already see, neither assistant cited technical limitations. Walmart‘s assistant, Sparky, argued that the FTC typically enforces “Made in USA” rules against manufacturers rather than retailers—a legal deflection, not a denial of detectability. Amazon‘s Alexa went further, acknowledging the real and documented damage to American brands, then explaining that ignoring the problem remains easier until it costs Amazon directly. Researchers also noted an asymmetry: Alexa readily answers questions about products made in China but blocks queries probing “Made in USA” claims.
Why It Matters: The Price of Selective Silence
The FTC rules are clear: a product advertised as “Made in USA” must be all or virtually all made in the United States. Last year, the agency asked both retailers to crack down on false country-of-origin claims by third-party sellers, pointing to their own marketplace policies that already require truthful product information. So the rule exists, the policy exists, and the detection capability exists—enforcement is the missing piece.
This study underscores a broader issue: AI shopping assistants are designed to increase spending, not audit marketplaces. A bot that interrupts a purchase to expose a misleading label works against its own success metric. As these assistants evolve into “agentic buying” tools that complete transactions inside chat windows, the operator’s ranking rules and incentives become even more influential. Brands are already buying placement inside voice and chat assistants, just as they once bought search keywords. The trust dimension is critical—shoppers are encouraged to treat these assistants as advisers, not sales channels, and the gap between those roles is exactly where this study lands.
Our Analysis: AI Governance and Platform Accountability
XPLAIN AI interprets this study as a pivotal moment in AI governance, moving beyond country-of-origin labels to fundamental questions about the role AI should play in consumer trust. Accuracy problems in consumer-facing AI are well documented, but selective silence is harder to detect than an outright mistake. As assistants gain more direct control over money—including linked bank accounts and financial data—the stakes of their silence rise exponentially.
From a market perspective, this research signals that AI shopping assistants carry regulatory and reputational risks, not just innovation upside. The accumulation of consumer protection failures could increase pressure on regulators, especially with Lina Khan’s ongoing antitrust lawsuit against Amazon. However, this is a possibility, not a certainty, and actual regulatory changes remain unconfirmed.
Beneficiaries and Risks: Who Stands to Gain or Lose
While this study is unlikely to cause immediate market shocks, it could shape medium-term trends. Companies that prioritize transparency and accuracy in AI design may gain a competitive edge in reputation and trust. Conversely, platforms whose AI assistants are perceived as optimizing solely for sales could face brand damage and regulatory scrutiny.
- AI governance and compliance technology: Demand for tools that audit and explain AI decisions could rise.
- Consumer-protection-focused AI design: Firms that differentiate by prioritizing consumer interests over sales may build stronger positioning.
On the risk side, sustained silence on consumer deception could lead to regulatory sanctions and eroding consumer trust, particularly for retail platforms. Yet, these are speculative scenarios; the direct impact on revenue or performance may be limited.
Contrarian View and Uncertainties
Of course, a counter-scenario exists: consumers might not view AI silence as a major issue, prioritizing price and convenience over provenance. Amazon and Walmart could also voluntarily improve policies or resolve the issue through non-FTC channels. Amazon’s spokesperson noted that country-of-origin information is displayed on product detail pages when available and that they are continually improving Alexa for Shopping to make it more accessible—a possible preemptive response to regulatory pressure.
Ultimately, this study raises a core question for the market: as AI assistants transition from sales channels to trusted advisers, how will companies balance business incentives with consumer protection? While technology races ahead, regulation and corporate ethics lag, making AI’s chosen silences an increasingly critical investment consideration. Key indicators to watch include regulatory follow-up actions, platform policy changes, and consumer trust metrics.
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Sources
- Amazon and Walmart AI Assistants Detect False “Made in USA” Labels but Do Not Flag Them — Technology Org · News coverage · Sat, 01 Aug 2026 04:53:00 +0000
Written by: XPLAIN AI Editorial Team · Reviewed by: XPLAIN AI Editorial Desk
This content was drafted with AI assistance based on publicly available sources and reviewed under XPLAIN AI's editorial standards.