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The National Bureau of Economic Research just surveyed 6,000 executives and the results are shocking.
90% of CEOs say AI had zero impact on productivity, yet corporate AI spending hit $250 billion in 2024.
Economists say a 40-year-old paradox explains exactly why this is happening ↓
In 1987, Nobel laureate Robert Solow wrote a famous line:
"You can see the computer age everywhere but in the productivity statistics."
Back then, companies poured billions into mainframes and PCs.
U.S. productivity growth actually slowed, dropping from 2.9% per year to just 1.1% despite massive IT investment.
Sound familiar?
Apollo's chief economist Torsten Slok is now echoing Solow directly, saying AI "is everywhere in the macroeconomic narrative" but "you don't see it in the data."
And just like the computer age before it, the gap between investment and results is widening.
But here's what makes this so puzzling ↓
At the micro level, AI works.
Controlled experiments show individual productivity jumps of 34–40%, especially for less experienced workers. Customer service reps, coders, and writers all show real gains in lab settings.
Yet when you zoom out to the firm level, 80–95% of AI pilots never successfully scale. And the research reveals exactly why:
• Top performers see only marginal gains, sometimes even slight quality declines
• 80% of time saved through AI gets reallocated to other tasks rather than boosting output
• Scaling requires new data infrastructure, process redesign, and worker training that most firms simply haven't committed to
• Most AI use remains shallow: drafting emails, summarizing docs, small time savings that barely register in company-wide metrics
Instead of replacing workers, AI is quietly redistributing what they spend their time on.
So is AI actually useless?
In the 1970s and 1980s, companies invested heavily in computers, but the productivity payoff only became visible in the 1990s once businesses completely redesigned their processes around the technology.
Some analysts believe AI is following the same pattern. Early investment drags productivity down before reorganization eventually pushes it up.
MIT economist Erik Brynjolfsson already points to early signs:
U.S. productivity growth recently hit roughly 2.7%, which may signal firms are finally moving from experimentation to extraction.
The takeaway?
AI hasn't failed.
The organizations using it have simply treated it as a surface-level tool rather than a reason to fundamentally rethink how work gets done.
That's why 90% of firms report zero impact.
Individual workers are getting faster, but the companies around them haven't changed enough for those gains to actually show up in the results.
The paradox won't solve itself.
The leaders who close the gap first will be the ones brave enough to rebuild their entire organization around AI.
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