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extract: 2026-02-01-mit-sloan-ai-productivity-j-curve-manufacturing #1214

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inbox/archive/2026-02-01-mit-sloan-ai-productivity-j-curve-manufacturing.md
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@ -7,11 +7,15 @@ date: 2026-02-01
domain: ai-alignment domain: ai-alignment
secondary_domains: [internet-finance] secondary_domains: [internet-finance]
format: paper format: paper
status: unprocessed status: null-result
priority: medium priority: medium
triage_tag: evidence triage_tag: evidence
tags: [j-curve, productivity-paradox, manufacturing, ai-adoption, adjustment-period, complementary-investment] tags: [j-curve, productivity-paradox, manufacturing, ai-adoption, adjustment-period, complementary-investment]
flagged_for_rio: ["J-curve in manufacturing AI adoption — 1.33pp productivity decline initially, recovery after 4 years. Only digitally mature firms see strong gains."] flagged_for_rio: ["J-curve in manufacturing AI adoption — 1.33pp productivity decline initially, recovery after 4 years. Only digitally mature firms see strong gains."]
processed_by: theseus
processed_date: 2026-03-18
extraction_model: "anthropic/claude-sonnet-4.5"
extraction_notes: "LLM returned 0 claims, 0 rejected by validator"
--- ---
## Content ## Content
@ -46,3 +50,15 @@ MIT Sloan researchers analyzing tens of thousands of U.S. manufacturing firms. P
## Curator Notes ## Curator Notes
PRIMARY CONNECTION: the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it PRIMARY CONNECTION: the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it
WHY ARCHIVED: Provides manufacturing-sector evidence for competitive pressure driving premature adoption. The "abandoned management practices" finding parallels organizational deskilling. WHY ARCHIVED: Provides manufacturing-sector evidence for competitive pressure driving premature adoption. The "abandoned management practices" finding parallels organizational deskilling.
## Key Facts
- MIT Sloan researchers analyzed tens of thousands of U.S. manufacturing firms using Census Bureau data, published 2026
- AI adoption in manufacturing initially reduces productivity by average 1.33 percentage points (raw analysis)
- Selection-bias-adjusted impact: negative up to approximately 60 percentage points
- Recovery period: 4 years before AI-adopting firms outperform non-adopters
- Earlier adopters (pre-2017) show stronger growth conditional on survival
- ~1/3 of productivity losses attributed to firms abandoning KPI monitoring and other management practices
- Only digitally mature firms see strong gains from AI adoption
- U.S. productivity jumped ~2.7% in 2025, nearly doubling the 1.4% annual average (Brynjolfsson claim)
- Apollo Chief Economist Slok counter-claim: 'AI is everywhere except in the incoming macroeconomic data'