AI-Generated Assets Flood Marketplaces, But Buyers Prefer Human Touch
Source: Fortune. Casualplayhub News adds summary, context, and editorial framing while linking back to the original report.
About a year ago, CGTrader, an online marketplace for 3D models, began allowing designers to upload AI-generated assets alongside their handcrafted works. The platform hosts over two million digital models that serve as building blocks for architects, video producers, game designers, and other creatives. But the experiment has revealed a stark disconnect: despite a surge in AI-generated listings, buyers remain reluctant to pay for them.
A recent internal report from CGTrader found that while one in six models uploaded to the site is now AI-generated, these assets brought in just 2.6% of total sales. For every $90 in revenue, only $1 came from AI-created items. “AI is entering the catalog rapidly, but buyers aren’t yet opening their wallets for it,” the report noted. The data, drawn from marketplace sales between June 2025 and May 2026, also showed that only 5% of customers who tried an AI model found it satisfactory, compared to 20% who found the assets inadequate.
CGTrader’s CEO, Dalia Lasaite, attributed the lukewarm reception to a simple factor: buyers value quality. “Buyers are looking for really high quality when they are shopping at the marketplace,” she told Fortune. “As a result, they tend to prefer human-created 3D models, at least at this point.” Lasaite noted that while creators initially feared AI, attitudes have shifted as the technology made production faster and cheaper. “Over time, we all realized that AI will be some kind of part of our life, and we adapt,” she said. “Maybe we can be more productive and just keep the best parts of our job to ourselves, and use the AI to help with the rest.”
Consumer sentiment toward AI remains mixed. A 2025 Stanford University study found that when given a choice between AI-generated and human-produced art, participants gravitated toward AI pieces, causing the number of generative AI images on the platform to rise quickly. But a Pew Research Center poll from last year revealed that half of Americans liked a painting less after learning it was made by AI. In a report published Tuesday, Pew found that 52% of American adults are now “more concerned than excited” about greater AI use in daily life, up from 38% in 2022.
Dennis Zhang, a professor of marketing and supply chain, operations, and technology at Washington University in St. Louis’s Olin Business School, sees deeper implications. “One side of economists always tells you, ‘Don’t worry about AI. For every technology revolution in human history, people re-pivot to something else to do,’” Zhang told Fortune. “What we’re saying is something else: It’s not only people as workers will re-pivot to something else to do, it’s also people as consumers will re-pivot to the dimension that humans will matter more.”
In his recent working research, Zhang measured the impact of coding agents like Claude Code and Codex on smartphone app launches. Comparing 2023 and 2024, he found a steady increase in the number of apps released, a trend that continued through 2026. After controlling for other variables, he estimated that coding agents caused a 160% increase in app production by April 2026 compared to two years prior. However, when he examined user engagement, the number of apps receiving more than 10 reviews dropped sharply after the AI launches, suggesting that people engaged less with AI-generated apps. Zhang cautioned that these results were not causal, but they point to a pattern: “There is some slight evidence showing that the products that are helped by AI in production are less attractive than the products where we had observed before, where it’s mostly human-crafted on the coding side.”
Zhang hypothesized that for apps where humans still played a major role in concept and development, the lower popularity may stem from the fact that these apps are not as refined as those built by experienced programmers. In other words, AI has enabled more “vibe coders” to create apps, but lack of experience leads to lower quality. For apps that are obviously completely AI-generated, consumers may be snubbing them because they value product scarcity and seek out tools with human-added value. Put together, Zhang believes these attitudes paint a picture of the future: “I would actually think people’s affection or judgments of products is going to shift from the parts which are created by AI to the parts which are less likely to be created by AI.”
Zhang sees evidence that AI will transform labor rather than largely displace jobs. Consumer responses in the marketplace—not completely rejecting AI but valuing human touches—affirm humans’ place in the economy. Both Zhang and Lasaite agree that the path forward involves integrating AI as a tool to enhance productivity while preserving the craftsmanship that buyers still prize.
Article commentary
The CGTrader report offers a telling snapshot of the current state of AI in creative marketplaces. Despite a rapid influx of AI-generated assets, buyers are voting with their wallets—and they are choosing human-made products. This is not a wholesale rejection of AI; rather, it reveals a nuanced consumer calculus that weighs quality, authenticity, and perceived value. One key takeaway is the disparity between supply and demand. While AI can churn out models at a fraction of the time and cost, the market has not responded with equal enthusiasm. Only 5% of CGTrader’s customers found AI models satisfactory, compared to 20% who found them lacking. This suggests that the technology, at least in this domain, has not yet reached a quality threshold that matches human craftsmanship. The CEO’s observation that buyers “are looking for really high quality” underscores a fundamental challenge: AI-generated content may be plentiful, but it is not yet good enough to command premium prices. Zhang’s research on app marketplaces adds another layer. The 160% surge in app production after the release of coding agents is a classic example of how AI lowers barriers to entry. But the subsequent drop in user engagement indicates that more products do not automatically mean better products. The apps that succeeded were likely those that still relied on human expertise in design and user experience. This mirrors the “vibe coder” phenomenon—inexperienced developers using AI to produce software that lacks polish. The lesson is that AI is a multiplier of human effort, not a substitute for skill and judgment. The consumer psychology angle is equally important. Zhang’s hypothesis that buyers value product scarcity and human-added value resonates with broader trends in the economy. In an era of mass-produced digital goods, authenticity and human touch become differentiating factors. The Pew poll showing rising concern about AI’s role in daily life suggests that this skepticism is not limited to niche markets. As AI becomes more pervasive, consumers may increasingly seek out products that signal human involvement as a mark of quality and trust. However, the picture is not one-sided. The Stanford study showed that when participants were unaware of an artwork’s origin, they gravitated toward AI-generated pieces. This indicates that bias against AI can be overcome when the output is indistinguishable from human work. But the CGTrader data suggests that in practical, professional settings—where buyers need reliable, high-quality assets—the preference for human-made products remains strong. Looking ahead, the coexistence of AI and human labor is likely to evolve. Lasaite’s comment that “AI will be some kind of part of our life” captures the inevitability of integration. The key will be to strike a balance: using AI to handle repetitive or time-consuming tasks while preserving the creative and quality control roles that humans excel at. Zhang’s prediction that consumer judgments will shift toward the parts of products that are less likely to be automated offers a roadmap for businesses. Companies that can clearly communicate the human value embedded in their offerings may gain a competitive edge. Ultimately, the CGTrader case study is a reminder that technology adoption is not linear. Market forces, consumer preferences, and the quality of output all play roles in shaping how quickly AI gains traction. The current data suggests that buyers are not rejecting AI, but they are demanding more. For AI to truly succeed in creative marketplaces, developers must focus on improving quality, not just quantity. The human touch, it seems, still matters.