When Allbirds, Inc. announced that it would exit its footwear business and reemerge as “NewBird AI,” an aspiring player in the AI compute infrastructure space, the reaction was pretty predictable: equal parts intrigue, confusion, and skepticism. Writing for Reuters, tech columnist Robert Cyran said the company “lacks footing for [a] dramatic AI pivot,” pointing to its unclear place in an already crowded, capital-intensive market.
The skepticism is not simply about Allbirds’ ability to execute. It reflects something broader: “AI” has become a proxy for future growth and valuation in certain segments of the market. The term now carries strategic weight in a way that goes well beyond its technical meaning, functioning as a signal of innovation, scalability, and in some cases, reinvention. That dynamic is beginning to draw scrutiny, particularly as companies lean more heavily on AI to frame their strategy and value.
Enter: AI Washing
The proliferation of retail companies touting themselves as AI-forward may be new, but the underlying dynamic is not. Sustainability claims and “innovation” narratives have routinely run ahead of what companies could substantiate, eventually drawing scrutiny – and in some cases, regulatory enforcement actions and consumer-initiated litigation – over how those claims were framed. The dynamic was not about whether companies were investing in sustainability or innovation, but how those efforts were presented to the market.
AI is following a similar path. Across the retail sector, brands now invoke AI to describe everything from personalization and inventory management to customer service and marketing. In some cases, those references reflect meaningful deployment of machine learning tools. In others, they amount to a reframing of existing systems (automation, analytics, or rules-based workflows) under language that may imply a level of sophistication or autonomy that is not fully supported by the underlying systems. That disconnect is where marketing language can give rise to legal exposure under consumer protection and securities laws.
Enter: “AI washing.” At its core, this involves companies overstating their AI capabilities, use of AI, or the technological or business impacts of AI, creating potential legal and reputational risk, and regulators are increasingly treating it as such. U.S. authorities, including the Securities and Exchange Commission, have made clear that AI-related representations fall within existing disclosure and anti-fraud frameworks.
There is no separate standard for emerging technology, meaning that claims about AI – whether in investor materials or consumer-facing marketing – must be accurate, supportable, and not misleading.
Where AI Meets Accountability
That regulatory stance matters because those claims are becoming increasingly central to how companies are valued and understood in the market. References to AI now appear regularly in earnings calls, investor decks, and brand messaging, often as shorthand for efficiency, scalability, and future growth.
As those claims take on more weight, they are increasingly being tested – by regulators, investors, and consumers alike. Investors are paying closer attention to whether AI-related statements translate into measurable performance, while consumers, particularly after years of sustainability messaging, are less inclined to accept broad or undefined claims at face value. Assertions about being “AI-powered” or “AI-driven” are increasingly met with follow-up questions rather than automatic credibility.
There is also a structural issue underneath it. Within retail organizations, AI initiatives are typically spread across multiple functions – product, logistics, marketing, while external messaging presents a single, cohesive narrative. What is described as a unified AI capability is often a mix of tools, processes, and human oversight, with key limitations left unaddressed.
What distinguishes AI from earlier “washing” cycles is how closely it ties to performance. Sustainability claims tend to shape brand perception. AI claims go further, touching on efficiency, margins, and growth, and can feed directly into how a company is valued and how its prospects are assessed. That linkage helps explain why regulators are moving earlier. The SEC’s focus on AI-related disclosures reflects a broader shift toward treating tech claims as material statements rather than marketing language. Other jurisdictions are taking a similar approach, reinforcing the expectation that companies will need to substantiate how AI is being used and what it delivers.
For retail companies, the focus is shifting from whether AI is being adopted to what is being claimed about its impact and how those claims stand up under scrutiny.
THE BOTTOM LINE: “AI-forward” may still function as a useful signal in the market. But it is no longer just positioning. It is a claim that companies will be expected to substantiate.
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