AI Job Losses: Case Study Debunks Employment Myth

The Illustrator Who Quit: When AI Does for Free What Was Once Paid

The data is stubborn: a freelance illustrator who dedicates seven hours daily to her craft, publishes one to three videos a month, and barely reaches 2,000 views in her last year has decided to quit. The stated reason is not a lack of talent or effort: it is that commissions no longer arrive. The tool meant to multiply creativity has become the competitor that works for free, tirelessly and without signing.

A Freelancer Against an Algorithm

The case became known through the Mentiradeloro channel, where the artist put numbers on her situation: she paid her self-employment tax (autónomo), VAT, and other taxes while watching small commissions—covers, posters, logos—disappear. She is not a civil servant and has not touched public budgets, so there is no safety net to support her. Her description of daily life outlines a pattern repeated across the sector: clients who once requested an illustration now type a prompt and get an acceptable result in seconds, free or nearly so, with infinite attempts to perfect it.

With basic skills in Gimp or Photoshop, the result no longer requires a professional except for high-level commissions and clients with urgency and money. The spreading conclusion is that precarity accelerates: there are too many illustrators for simple tasks, and the value of the profession collapses.

The Fallacy That Technology Creates Jobs

For years, it was repeated that computing did not destroy jobs, or that those it destroyed were compensated by new ones. This argument crashes against a particularity: previous industrial revolutions replaced one physical element with another, whereas AI is pure software that scales at zero marginal cost. This changes the equation in sectors where what is sold is intellectual production itself.

The recurring example is Chinese textiles from three decades ago: those who survived did not compete in manufacturing but kept design and marketing. The difference is that AI does not need a manufacturer in Shenzhen: production is in the cloud, and copying, by definition, is infinite. And the next blow, some analyses warn, will hit white-collar jobs: AI was not built to make doodles but to absorb office work.

The Paradox That Holds and Breaks

Jevons’ paradox explained that making a good cheaper boosts its demand. In radiology, this holds clearly: AI has made tests cheaper, more are ordered, and demand for radiologists keeps rising. On YouTube and in illustration, the opposite happens. When the good is human attention and producing material costs almost nothing, demand for intermediate creators does not expand: value deflation occurs.

Translation: more people rushing to sell images, more saturation, and prices plummeting. Some summarize it with that Black Mirror episode where the aspiring singer is told she sings very well but they already have an excess of singers. Music, cinema, and drawing share the same fate: artificial artifacts flood the market and push the average artist out.

Quality as an Excuse

A minority current argues that the problem is not artificial intelligence but the average level. AI-generated drawings still have hands with six or seven fingers, nightmare faces, and that stiff air that betrays them. The question is whether buyers care. Street evidence suggests they do not: rental signs, municipal promotions, and book covers fill with synthetic images, hideous but cheap.

The excellent illustrator will find a niche; the average one, who lived off small commissions, disappears. The same logic turns the profession into a dual market: very few established names and a long queue of precarious workers. The sharpest use AI to produce like crazy, let it do 80% of the work, and finish with Photoshop or Gimp. That does not fix employment: it reconfigures it in favor of those who already knew how to move the pieces before anyone else.

The question hangs in the air: if AI keeps increasing power and public taste for the synthetic, how many professions cease to be viable before someone dares to set limits? For now, those already out are paying the answer.