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Iran Conflict 2026
30MAR

NBER: nine in ten firms untouched by AI

2 min read
08:00UTC

A multinational survey of 6,000 executives found most companies see no employment effect from AI. Inside those same firms, bosses and workers hold opposite forecasts.

ConflictDeveloping
Key takeaway

Bosses expect AI to cut jobs while their own employees expect it to create them.

A survey of nearly 6,000 senior executives across the United States, United Kingdom, Germany, and Australia, published by the National Bureau of Economic Research, found that 90% of firms report no impact on employment or productivity from AI so far. 1 Sixty-nine per cent of the surveyed firms actively use the technology. Nine in ten see nothing happening.

The contradiction sits inside the forecasts. Executives at these firms predict a 0.7% employment decline over the next three years. Employees at the same companies predict a 0.5% increase. 2 One group expects cuts. The other expects growth. They work in the same buildings, use the same tools, and hold irreconcilable views of what comes next.

During the 1990s offshoring wave, management planned relocations years before workers learned their roles would move overseas. Approximately 3.4 million US manufacturing jobs were lost between 1995 and 2005. Workers could not prepare because they did not know. The NBER data, spanning four countries with different labour market systems, suggests this gap is structural, not cultural . If executives act on private bearish forecasts without informing staff, displacement will arrive as a shock rather than a managed transition.

Deep Analysis

In plain English

A research body surveyed nearly 6,000 bosses across the US, UK, Germany, and Australia and asked whether AI has yet affected hiring or productivity at their companies. Nine in ten said no. But the same bosses predict employment at their firms will fall slightly over the next three years. Workers at those same companies predict it will rise slightly. Someone is wrong. Given that bosses set hiring plans, their forecast is more likely to be self-fulfilling.

Deep Analysis
Root Causes

Information asymmetry within firms is the structural cause. Executives have access to strategic planning documents, vendor capability assessments, and board-level restructuring discussions that do not reach workers. The 1.2-percentage-point forecast gap (0.7% decline vs 0.5% increase) is more consistent with deliberate non-disclosure than with genuine disagreement.

The 69% active AI adoption rate combined with the 90% null employment impact suggests a deployment phase that is currently affecting task structure without reducing headcount. The NBER finding by Humlum and Vestergaard that LLM adoption produces occupational switching without net changes in hours or earnings supports this reading: impact is happening below the level of employment statistics.

Measurement lag is also structural. Employment surveys capture headcount but not task composition or hiring freeze effects. The Dallas Fed found displacement operating primarily through collapsed job-finding rates among workers under 25, a mechanism invisible to standard employment impact questions.

What could happen next?
  • Risk

    The executive-employee forecast gap may widen as deployment accelerates, producing a shock dynamic similar to 1990s offshoring where workers had no preparation time.

    Medium term · Medium
  • Consequence

    Policymakers relying on current employment statistics will underestimate displacement risk because the primary mechanism is hiring suppression, not firing, which appears later in official data.

    Short term · High
  • Meaning

    The 90% null result at 69% adoption rates confirms the technology is in a pre-deployment productivity phase; the employment shock, if it arrives, will be sudden rather than gradual.

    Long term · Medium
First Reported In

Update #3 · The AI jobs data contradicts itself

NBER (Yotzov, Barrero, Bloom, Bunn, Davis et al)· 28 Mar 2026
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NBER: nine in ten firms untouched by AI
The largest cross-country executive survey reveals a dangerous information gap: employers expect job losses while their own workers expect gains.
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