A Dallas Fed economist, using BLS modeled wage data across 205 occupations and an established AI-exposure index, finds that employment in the top-decile AI-exposed sectors has declined roughly 1 percent since late 2022 while total US employment rose 2.5 percent, with the shortfall concentrated in workers under 25 via a low job-finding rate rather than layoffs. Wage growth in those same sectors is flat to slightly positive overall, but the interaction with occupation-level experience premiums reveals a split: high-experience-premium occupations see AI exposure associated with higher wage growth, while low-experience-premium occupations see a statistically significant wage drag. The structural implication is that AI is compressing the bottom rung of the white-collar career ladder, which disrupts the traditional apprenticeship model through which junior workers acquire tacit knowledge, creating a pipeline risk that financial institutions should factor into workforce planning for AI-exposed functions such as credit analysis, underwriting, and software development. Also reported by: https://www.dallasfed.org/research/economics/2026/0224
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