A recent amendment to New York State’s advertising laws, intended to bring transparency to the use of artificial intelligence in imagery, is drawing criticism for its potential to hinder generative AI innovation and impose significant regulatory burdens on retailers, particularly small businesses. The legislation, sponsored by State Senator Michael Gianaris (D) and Assemblywoman Linda Rosenthal (D), mandates clear disclosures when advertisements feature AI-generated images of people. While the stated intent is to inform consumers, critics argue that the mandated notice effectively acts as a warning label, undermining the efficacy of AI-generated visuals and creating an uneven playing field in the e-commerce landscape.
The legislative measure, identified as an amendment to New York State General Business Law § 396-b, requires that any advertisement containing an AI-generated image of a person must include a conspicuous notice to that effect. This disclosure is designed to alert consumers that the depicted individual is not real. However, the practical implication of this requirement, according to industry observers, is that it may discourage consumers from trusting or engaging with these otherwise lawful images. This could significantly diminish the effectiveness of AI-generated photography, a burgeoning tool for businesses seeking to create diverse and cost-effective marketing materials.
Amazon’s Proactive Response and Broader E-commerce Implications
The impact of New York’s new law is already being felt across the e-commerce sector, with major online marketplaces taking steps to comply. CNBC reported in late July 2026 that Amazon has begun instructing its third-party sellers to identify and flag product content that includes AI-generated images of people before uploading them. This directive suggests that the e-commerce giant may implement a notification system for shoppers, though the precise nature of these labels—their timing and prominence—remains to be fully detailed by Amazon.
This proactive stance by Amazon underscores how a single state’s legislation can ripple through national e-commerce practices. The complexity arises from the challenge of definitively identifying AI-generated imagery. Sellers may not always know the geographic location of every potential customer, and Amazon itself faces difficulties in distinguishing between photographs of real people, AI-generated individuals, or images that have been substantially altered through traditional or AI-assisted post-production techniques. By requiring sellers to provide this information, Amazon aims to mitigate its own regulatory risk and ensure compliance with the New York statute.
However, this requirement places a substantial burden on merchants. They are now tasked with identifying "synthetic" individuals within their visual content, reviewing existing creative assets, maintaining detailed production records, updating metadata, and ultimately accepting the potential diminishment of their image’s effectiveness due to the mandated disclosure. For small and medium-sized businesses (SMBs), which often operate with leaner resources, these additional compliance steps represent a significant operational challenge.
A Patchwork of AI Regulation: Precedents and Parallels
While New York’s law is notable for its application to commercial advertising, it is not an isolated instance of regulatory action concerning AI-generated content. The landscape of AI regulation is rapidly evolving, with various states enacting laws to address specific risks associated with synthetic media. For example, several states have implemented regulations governing AI-generated political communications, aiming to prevent the spread of misinformation and protect the integrity of electoral processes. Other legislative efforts target fabricated testimonials, non-consensual intimate imagery (often referred to as "deepfakes"), and the unauthorized replication of identifiable individuals’ likenesses.
These diverse regulations, though addressing distinct concerns, collectively contribute to a fragmented compliance environment for businesses operating across state lines. Merchants engaged in national commerce must navigate, interpret, and adhere to a growing patchwork of state-specific requirements, adding layers of complexity and potential legal exposure. The lack of a unified federal framework for AI regulation exacerbates this challenge, forcing businesses to maintain a vigilant watch on legislative developments in each jurisdiction where they operate or market their products.
The Ambiguity of "Advertisement" in the Digital Age
A key point of contention surrounding New York’s law is its broad interpretation of what constitutes an "advertisement." The statute applies to advertisements concerning the use of people in products for sale. This raises a fundamental question: is every product image an advertisement?
Industry professionals argue that images displayed on a product detail page serve a different purpose than a television commercial, a social media ad, or a sponsored placement. Product images are often intended to provide factual information about an item’s appearance, dimensions, functionality, or fit. An AI-generated model wearing a shirt, for instance, can fulfill the same merchandising role as a traditional mannequin, an illustration, or a catalog model. In this context, the model’s purpose is to showcase the product, not necessarily to endorse it, claim ownership, or express a personal opinion.
Despite this distinction, the legal risk remains significant. Regulators could interpret these product showcase images as persuasive tools aimed at influencing consumer purchasing decisions, thereby classifying them as advertisements. Amazon’s reported policy of applying the disclosure requirement to product listings featuring images of people reinforces this possibility. This broad interpretation could inadvertently capture a wide range of visual content that businesses use primarily for informational purposes.
Uneven Application and the Disadvantage for Smaller Businesses
A critical aspect of the New York regulation that has drawn particular criticism is its perceived uneven application. The law appears to create a disparity in treatment between large retailers and smaller businesses, based on the method of image production rather than the potential for consumer deception.
Large retailers often possess the resources to engage in extensive, high-cost production processes. This can involve hiring models, photographers, stylists, studio crews, retouchers, advertising agencies, and legal counsel. The resulting images from such elaborate photoshoots can undergo significant manipulation, including compositing, reshaping, color correction, the use of artificial lighting, and the insertion of digital backgrounds. As long as the production process maintains a demonstrable link to a real human performer, even if extensively modified, it may bypass the scrutiny applied to fully AI-generated models.
In contrast, a smaller retailer might leverage generative AI to create a comparable product image from a single product photograph. However, under the New York law, this more affordable and accessible AI-generated image may be required to carry a disclosure notice. This mandated warning is likely to negate the image’s effectiveness, rendering the investment in its creation largely futile.
This differential treatment means that expensive, human-led production methods are subject to standard commercial practices, while more cost-effective AI-driven processes face potentially damaging scrutiny. The distinction, critics argue, hinges less on whether consumers are being misled about the product itself and more on the chosen method of image creation and its associated production costs.
Generative AI: A Catalyst for Innovation and Democratization
The advent of generative AI has been hailed as a transformative force in e-commerce, dismantling one of the industry’s longest-standing competitive barriers: the high cost of professional product photography. For nearly three decades, creating polished and compelling product imagery, especially lifestyle and model shots, required substantial financial investment. Large retailers could afford extensive visual campaigns, giving them a significant advantage over smaller merchants who were often limited to basic product shots.
Generative AI has fundamentally altered this dynamic. With a high-quality product photograph as a starting point, smaller businesses can now generate a wide array of visual content in minutes and at a fraction of the cost. This includes model images, lifestyle settings, seasonal campaigns, localized variations for different markets, social media content, and product-in-use scenarios. This capability represents a significant democratization of creative resources, leveling the playing field between small businesses and large corporations by reducing the reliance on expensive studio shoots and professional models.
New York’s new law, by potentially stigmatizing and devaluing AI-generated imagery, risks stifling this crucial wave of innovation. The ability for smaller businesses to compete visually with larger enterprises through affordable AI tools is a key driver of economic opportunity. Regulations that create undue burdens or disincentives for the use of these technologies could inadvertently hinder market competition and limit the growth of independent businesses.
The Economic and Technological Landscape
The global market for generative AI is projected for significant expansion in the coming years. Analysts at Grand View Research, for instance, estimated the global generative AI market size at USD 15.88 billion in 2023 and projected it to grow at a compound annual growth rate (CAGR) of 37.7% from 2024 to 2030. This rapid growth is fueled by advancements in machine learning and the increasing accessibility of AI tools across various industries, including e-commerce, marketing, and content creation.
The economic implications of New York’s law extend beyond individual businesses. By potentially hindering the adoption of a technology that lowers production costs and increases market access, the regulation could impact overall economic dynamism within the state and beyond. Small businesses that rely on AI-generated imagery for their online presence may find themselves at a competitive disadvantage if they are forced to choose between compliance costs and effective marketing.
Future Outlook and Industry Concerns
The long-term implications of this New York law remain a subject of ongoing discussion within the e-commerce and technology sectors. Industry groups are closely monitoring the implementation and enforcement of the regulation, as well as the potential for similar legislation to emerge in other states. Concerns are being raised about the feasibility of accurate AI detection, the potential for overreach in regulatory definitions, and the unintended consequences for businesses that are striving to innovate and compete in an increasingly digital marketplace.
As generative AI technology continues to evolve, so too will the debate surrounding its ethical and legal implications. Striking a balance between consumer protection and fostering technological advancement will be crucial. The New York law, while well-intentioned, may represent an early attempt to navigate this complex terrain, highlighting the need for carefully considered, adaptable, and harmonized regulatory approaches that support both innovation and consumer trust. The challenge lies in crafting legislation that addresses genuine risks without inadvertently stifling the very technologies that promise to democratize commerce and empower businesses of all sizes.
