Jim Farley, chief executive of Ford Motor Company, issued a blunt warning to business and political leaders: the U.S. does not have enough blue‑collar workers to match the scale of its AI ambitions. “Nothing to backfill the ambition,” Farley told Fortune, pointing to the thousands of megawatts of data center capacity and new manufacturing lines that firms are planning to support advanced AI workloads.

The comment underscores a growing mismatch between capital investment and labor supply as the AI industry accelerates. Market forecasters estimate the global AI ecosystem could grow into a roughly $4.8 trillion market by 2033, a projection that implies a substantial build‑out of hyperscale data centers, fiber networks, power infrastructure and factory capacity. Those projects rely not on software engineers alone but on electricians, HVAC specialists, fiber splicers, heavy equipment operators and skilled assemblers — occupations where employers report chronic recruitment and retention difficulties.

Manufacturing employment in the United States has not returned to its mid‑20th century peaks; roughly 12½ million Americans worked in manufacturing in recent years, while construction employment hovers in the mid‑7 millions. Many employers say those pools are stretched thin. The pattern is reflected in industry surveys showing prolonged vacancies for specialized trades and in anecdotal accounts from site managers who delay starts or pay premiums to source labor.

Policy moves intended to revive domestic industry have so far produced mixed results. The Biden administration’s subsidies and the Inflation Reduction Act helped spur investment in clean‑energy manufacturing and semiconductor fabs, while President Donald Trump’s tariff policies aimed to shield factories from foreign competition and boost onshore production. Yet tariffs and incentives do little to address the underlying workforce shortfall: younger workers have flowed into service sectors, vocational training has eroded in many states, and a large cohort of skilled tradespeople is reaching retirement age.

Economists warn that without concerted action the labor gap will impose tangible costs. Shortages can raise project timelines and construction premiums, which in turn lift the cost of cloud services and delay commercial AI deployments. For manufacturers, constrained staffing could limit the ability to ramp up production for electric vehicles or chips, blunting the intended economic effects of industrial policy.

Farley and other executives propose a three‑pronged response: expand apprenticeships and community‑college partnerships, incentivize private training through tax credits, and use targeted immigration to fill shortages in specialized trades. Those measures, they argue, would be less blunt and more scalable than across‑the‑board protectionism.

Longer term, the economy faces structural choices. Automation can substitute for some labor, but it also creates new kinds of operating and maintenance roles that require technical skills. Filling that pipeline will depend on reversing decades of declining investment in vocational pathways, aligning incentives for firms to invest in workers, and accepting that higher wages and benefits may be necessary to attract and retain the workforce modern industry demands.

Fortune brings these debates to the fore at its Global Forum in Riyadh on Oct. 26–27, 2025, where CEOs and policymakers will confront how to align human capital with the capital spending that underpins the AI era. Farley’s warning is a reminder that ambition without workers is an expensive bottleneck.