Generative artificial intelligence is not just automating routine tasks—it is creating a fundamentally new segment of demand for human labor. This involves refining and "reviving" content that neural networks produce with errors, hallucinations, or visual defects. Analytics from the largest freelance platforms demonstrate explosive growth in such orders, which is radically reshaping the landscape of remote work.
From August 2025 to June 2026, the number of job postings on Freelancer.com containing phrases like "fix AI," "AI hallucination," or "AI error" increased by 87%, reaching 10,760 listings. The largest volume of such tasks falls under graphic design, followed by video editing, proofreading, and copywriting.
Platforms record multi-fold growth
On Upwork, demand for specialists who fix AI-generated content grew by 70% year-over-year. Meanwhile, since 2023, the number of such job postings in the development sector has increased 8.3 times, and in the design and creative category—7.9 times. Fiverr shows even more striking dynamics: the number of search queries for "AI cleanup" services grew more than 20-fold from 2023 to 2026.
These are not one-off spikes but a sustained trend. Clients—from small businesses to large corporations—increasingly use ChatGPT, Claude, and image generators to create a draft version, then hire people to bring the product up to commercial quality. For example, a graphic designer from Spain working under the pseudonym Lisa notes that by 2025, about 90% of new requests in the logo and packaging categories involved fixing generated images. This activity brought her 60-70% of her annual income. Typical tasks include increasing resolution for print, eliminating visual defects, and preparing files for production. However, according to the designer, some source files were so poor in quality that it was easier to create them from scratch: "It was just soulless," she admits.
The hidden costs of "savings"
The key paradox of the new market is that fixing AI work often takes no less time than creating content from scratch. Clients, believing the neural network has already done the "heavy lifting," expect a significant discount. Illustrator Todd Van Linda turned down a $500 order to fix 13-15 images for a children's book: the client expected 15 minutes per picture, whereas the actual work takes hours or even days. Multimedia editor Nathan McConnell encountered a batch of 100 images of humanoid animals for a tarot deck, where every picture had extra fingers and incorrect limbs. Fixing a single illustration took two to three hours, and some materials were simply impossible to restore.
Structural reshaping of the market
Freelancer.com CEO Matt Barrie explains this phenomenon by noting that entrepreneurs use AI for the first version of a product but cannot fix errors themselves. As a result, the initial savings in time and money are "eaten up" at the stage of preparing for commercial use. At the same time, the base of traditional creative orders is shrinking: research from Management Science showed that in the first eight months after ChatGPT's launch, the number of freelance job postings in automatable categories fell by 21%. After the spread of image generators, orders for visual content dropped by 17%. Competition is also intensifying: in 2025, a single project on Freelancer.com averaged 54 bids—8% more than the year before.
Forecasts diverge
Experts assess the future of this segment differently. Editor Kim Dunbar, who spends 60% of her working time fixing AI texts, finds the work interesting but allows that demand for "humanizing" content will disappear within five to ten years as models improve. "It's a shame we even have to do this," she says. McConnell, by contrast, is confident that professional review will remain in demand: an inexperienced user will not notice brand guideline violations or "shifting" objects in a frame. Some specialists are already returning to original creative work. Van Linda stopped taking orders to fix AI art and is again receiving requests for hand-drawn illustrations. Lisa also indicated in her profile that she refuses to work with generated images, although offers continue to come in.
There is also a degradation of skills among developers themselves: programmers from Big Tech complain that neural network code contains errors, and reviewing it takes more time than writing from scratch. At the same time, demand for specialists who can skillfully work with AI in the UK has reached record levels.
My view: the market for "cleaning up after AI" is a transitional phase, not a new economic reality. As long as models generate "drafts," human oversight will remain critical, but betting on a long-term career in this niche is risky. Instead, professionals should invest in skills that AI cannot replicate: strategic thinking, aesthetic taste, and a deep understanding of context. Those who use AI as an assistant rather than a replacement for their craft will come out ahead.