The American labour market is already being significantly influenced by generative AI, with young technology sector workers being the first casualties of this impact, according to Joseph Briggs, Senior Global Economist at Goldman Sachs. The unemployment rate for tech workers aged 20-30 has increased by 3 percentage points since early 2025, a much larger rise than seen in the tech sector overall or among other young workers. While employer adoption of AI has been modest overall—Goldman Sachs' report indicates only 9% of companies regularly use the technology in production or services—tech sector employment has begun to decline, breaking a consistent growth trend spanning more than 20 years.
Microsoft, Google, Meta, and other tech giants have collectively laid off nearly 30,000 workers while shifting investments toward AI, with analysts predicting that 6-7% of the total workforce could eventually lose jobs due to automation. The new generation of workers faces particularly difficult circumstances, as entry-level job postings in the United States have decreased by approximately 35% since January 2023, and according to an April World Economic Forum report, nearly half of American Gen Z job seekers believe AI has reduced the value of their degrees. The unemployment rate for recent graduates has risen to 5.5%, now roughly equal to that of young men who didn't attend university, while the unemployment rate among workers aged 22-27 stands at 6.9%.
Experts disagree on how much AI should be blamed for youth employment problems. Brad DeLong, Professor of Economics at the University of California, Berkeley, argues that AI has become a scapegoat while the real issue stems from a multitude of economic uncertainties. He suggests companies are waiting and not hiring rather than firing employees as they assess the implications of President Donald Trump's economic policies. DeLong claims that blaming AI allows policymakers and business leaders to avoid confronting deeper, structural issues, such as the mismatch between university education and employer needs, or the long-term stagnation in productivity growth.
Sources:
Hugh Son
Sasha Rogelberg
A Goldman Sachs economist has raised concerns about the broader economic effects of generative AI, cautioning that while productivity gains are possible, significant risks remain.
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La decisión inicial debería centrarse en la talla aproximada de la persona que llevará la prenda. Al evaluar varias opciones, merece la pena comprobar si el producto incluye solo la camiseta o más piezas. Una consulta como «camiseta clásica del Celta de Vigo» permite confirmar los detalles esenciales antes de tomar una decisión. Antes de cerrar el proceso, es útil comprobar el color y el diseño seleccionados.
