Companies Spent $443B on AI. The GDP Data Says It Didn't Work.

Will national productivity statistics still show no measurable AI-driven acceleration through end of 2028?

Companies are spending billions on AI tools. The economy-wide numbers say it's not working yet.

Target: Dec 2028(1030 days until resolution)

Assessed Probability

50%

More likely than not

Based on 2 expert predictions, 3 evidence items

Community Forecast

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Your Prediction

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5%95%

50% — More likely than not

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The Solow paradox debate just split wide open. Economist Erik Brynjolfsson, writing in the Financial Times in February 2026, now argues the AI productivity take-off IS visible in US data — BLS revised payroll growth down by 403,000 jobs while real GDP stayed robust at 3.7%, a classic decoupling of output from labor. His updated analysis shows US productivity grew roughly 2.7% in 2025, nearly double the 1.4% decade average. Former Obama CEA chair Jason Furman agrees: 2.5% over two years, the second-best productivity cycle since 1973. But the counter-evidence is equally strong: an NBER study of 6,000 executives found over 90% report no impact from AI on jobs or output. Average AI usage among those who do use it is just 1.5 hours per week. Apollo chief economist Torsten Slok says AI is 'everywhere except in the incoming macroeconomic data.' This is genuinely the most actively contested topic among economists right now — we're moving from 'likely no signal' to 'genuinely uncertain.'

Scenarios

Current value: 2.2% average annual productivity growth (2025); Q3 2025 at 5.2% (exceptional quarter); 89% of firms report no measurable AI gains

S-curve position: Pre-inflection — like IT in 1990s, productivity gains may take 10-15 years to appear in macro statistics

Bear Case

No macro signal through 2030 (Solow paradox repeats, gains captured as profits not productivity)

Base Case

Flat through 2028, first signals in 2029-2030 (matches IT productivity lag)

Bull Case

Visible acceleration by 2027 (AI adoption faster than IT, measurement improves)

How We'll Know

What we measure: US Bureau of Labor Statistics quarterly labor productivity growth (nonfarm business sector) compared to 2015-2023 trend
Confirmed if: US labor productivity growth through 2028 remains below 2.5% annually sustained for 4+ quarters with no statistically significant AI-attributable acceleration
Refuted if: Productivity growth exceeds 3% annually for 2+ consecutive quarters with AI clearly cited as contributor
Data sources: BLS Productivity and Costs reports
NBER working papers on AI and productivity
OECD productivity statistics
Federal Reserve economic data (FRED)

Evidence Trail

Evidence For

Mar 7, 2026
NBER: 89% of firms report no measurable productivity gains. IT productivity paradox lasted 15 years. BLS data shows no sustained break from trend. PwC: 56% of CEOs say they've gotten 'nothing out of' AI investments. Federal Reserve: only 1.9% excess cumulative productivity since ChatGPT launch.→ Probability: 65%

Evidence Against

Mar 7, 2026
2025 annual productivity 2.2% (above decade average). Q3 2025 at 5.2%. Individual studies show 20-40% task-level efficiency gains. Coding productivity up 30-50%. Customer service resolution times down 30-50%. AI adoption is faster than IT adoption was — the paradox may resolve faster.
Mar 7, 2026
Brynjolfsson (Feb 2026 FT): US productivity grew 2.7% in 2025, nearly double the decade average. BLS revised payroll down 403K while GDP at 3.7% — output-labor decoupling. Furman: 2.5% over 2 years, best since 1973. Block cut 40% workforce. Dev freelance rates -36%. Cursor $2B ARR / 12 employees. 54,694 AI-attributed layoffs. Goldman Sachs: AI completes 95% of IPO prospectus in minutes (was 2 weeks, 6 people), expects 3-4x gains across divisions. Software job postings at 5-year low (-35% from pre-pandemic). These are real economic signals that should show in productivity data.→ Probability: 50%

What Experts Say

Sam Altman

CEO, OpenAI

Track record: 7/10

“30-40% of current economic tasks will be done by AI in the not-very-distant future”

Jan 2026 | blog

We assess this claim as 50% more likely than not

Mustafa Suleyman

CEO of Microsoft AI

Track record: 6/10

“Most professional tasks involving sitting at a computer will be fully automated by AI within 12-18 months”

Feb 2026 | interview

We assess this claim as 5% very unlikely

What Could Go Wrong

AI productivity gains appear in macro data sooner than expected because adoption is genuinely faster than IT. A structural break in 2027-2028 (3%+ sustained growth) would refute this. Measurement methodology improves to capture AI-driven quality improvements that BLS currently misses.