The proliferation of generative AI has ushered in a transformative era in visual content creation. Capable of producing photorealistic images from text prompts in seconds, tools like Midjourney, DALL·E, and Adobe Firefly are reshaping how businesses and individuals source images. By August 2024, 39.5% of U.S. adults aged 18 to 64 had used generative AI, a rate of adoption that surpassed that of personal computers and the internet during their early years. Particularly in marketing, where demand for fast, customized visuals is high, 39% of marketers use AI to create social media visuals, and 36% to generate website imagery. The accessibility and sophistication of these tools are rapidly eating into the traditional domain of stock photography.
The global stock photography market was valued at $4.65 billion in 2024 and is projected to grow to $6.97 billion by 2030. In parallel, the AI image generator market is on an exponential growth trajectory: from $300 million in 2023, it is projected to reach anywhere between $917 million and $60.8 billion by 2030, with compound annual growth rates ranging from 17.4% to 38.2%. While the stock image market grows steadily, AI image generation is accelerating at a vastly higher rate, signaling a disruptive force that could overtake significant portions of traditional licensing.
Major players like Shutterstock and Getty Images offer a window into this disruption. Shutterstock reported full-year 2024 revenues of $935.3 million (up 7%), partly driven by the acquisition of Envato and $104 million in AI content licensing revenue—a figure projected to rise to $250 million by 2027. Meanwhile, Getty Images’ Creative revenue declined by 4.5% in 2024 despite overall corporate growth. This decline in core stock licensing, offset by growth in editorial and AI-related services, suggests an internal shift rather than expansion.
While neither agency explicitly attributes losses to AI competition, their financial pivots and public emphasis on AI development imply a strategic redirection in response to emerging threats.
Illustrators and creatives in adjacent fields are already facing measurable displacement. According to the Society of Authors, 26% of illustrators lost work due to AI by early 2024, and 37% reported reduced income. A separate survey (Book An Artist) found that 54.6% of visual artists feared income loss from AI. In audiovisual production, a global study estimated a 21% revenue risk by 2028. While photography-specific figures are scarce, the parallels suggest traditional visual content creators face similar pressures.
Using conservative modeling, if generative AI displaces just 5% to 15% of demand for stock images, that represents $232 million to $698 million in potential annual loss globally. With photo agencies estimated to command 40–60% of the market, their share of the loss would range from $93 million to $418 million per year. These figures are not yet publicly acknowledged by agencies, but they emerge as logical extrapolations from adjacent industry signals and declining trends in creative revenue segments.
Even where revenue remains stable, profit margins are under pressure. AI-generated imagery offers unique advantages: instant production, total customization, and guaranteed originality—addressing long-standing client concerns about stock images being overused. Anecdotes from industry professionals confirm the shift: one French photographer reported losing a €15,000 campaign to an agency offering an entirely AI-generated visual campaign.
Industry sentiment is increasingly uneasy. Terms like “death spiral” and “panic” have surfaced on forums and among commentators. AI-focused platforms predict stock images will be the first creative assets replaced en masse. While agencies maintain a public front of resilience, their strategic investment in AI integration and data licensing suggests anticipation of further erosion.
Shutterstock’s Q3 2024 earnings call noted no “material displacement” of traditional licensing by AI—yet. But this could reflect a lag in financial reporting or a reluctance to disclose weakening licensing demand. Growth in AI revenue and data licensing may be masking stagnation or decline in core licensing revenue.
The uncertain legal status of AI-generated content and the sources used for training further complicates the situation. Currently, no specific legislation requires companies to pay for licenses when using content to train AI models. Several lawsuits are ongoing, and many countries are debating clearer regulations on the issue.
In the meantime, agencies with extensive content libraries, such as Shutterstock and Getty Images, are exploring AI licensing as a new revenue stream. They are legitimately (pending legislation) licensing their archives of images, videos, and metadata to companies developing foundation models, looking to protect themselves against potential litigation.
For example, Shutterstock reported $104 million in revenue from this activity in 2023 alone and expects to reach $250 million by 2027, primarily by licensing content to major tech companies like OpenAI and Meta. Getty has also signed similar agreements with Nvidia, Bria, and others, positioning itself as a provider of legally safe, high-quality datasets.
These partnerships offer agencies a short-term revenue boost and a strategic foothold in the AI economy, but they also carry a risk: cannibalizing traditional licensing streams. After all, the companies acquiring these licenses (OpenAI, Meta, Nvidia, Adobe) are the same ones building image generators that directly compete with the agencies’ historical business models.
Legal clarity will be essential to define future revenue models — and may either strengthen or cut off this new income stream. In any case, one question remains: how long will this market last, knowing that once models are trained, they no longer need to repeat the process?
The traditional photo agency model is undergoing fundamental change. While publicly disclosed figures do not yet quantify the loss directly attributed to generative AI, surrounding data paint a clear picture: generative tools are displacing demand, pressuring margins, and rerouting revenue. For an industry that once defined the visual language of media, marketing, and publishing, this disruption is not speculative—it is already underway, and it’s measurable in millions.
Paul Melcher is a highly influential and visionary leader in visual tech, with 20+ years of experience in licensing, tech innovation, and entrepreneurship. He is the Managing Director of MelcherSystem and has held executive roles at Corbis, Gamma Press, Stipple, and more. Melcher received a Digital Media Licensing Association Award and has been named among the “100 most influential individuals in American photography”
This article originally appeared on Kaptur.co. You can read the full piece here: The Silent Collapse – Generative AI’s Erosion of Photo Licensing Revenue