What happened
The McKinsey Global Institute's new workforce report models how AI and automation reshape U.S. labour demand: MGI estimates 'automation could reduce U.S. labor demand by roughly 36M jobs over the next decade,' while growth in the AI value chain and wider economy 'could create more than 40M' — a net gain, but 'roughly 11 million US workers may need to switch occupations as AI reshapes the economy by 2035—yet only one in seven has a direct pathway.' The report finds nearly half of displaced workers face an 'unpaved' path blocked by credential or skills gaps, and recommends managing by skills rather than titles, making credentials stackable, and funding transitions rather than just training.
Why it matters
Provides the definitive quantification of AI-driven labour reallocation and its bottleneck (unpaved pathways) that C-suite workforce-planning and government reskilling decisions will be anchored to.
Action needed
Use the skill-transition framework to stress-test your workforce plan: identify which roles sit on 'paved' vs 'unpaved' pathways and budget for credential and transition support.