Essentials: pace
How fast will the impact arrive? The key papers, numbers, people and newsletters, sized to the time you have. The full question page. Picks are chosen for their weight in the debate and span its sides; they are refreshed every two weeks, last on 29 Oct 2026. The reasons are AI-written and evidence-cited; no rankings or scores.
Five papers, the numbers with their exact quotes, five people and three sources.
Papers to read
- AI and Growth: Where Do We Stand?Philippe Aghion and Simon Bunel · Federal Reserve Bank of San Francisco · 2024 · Evidence for the claim
Compares AI with past technological revolutions: 0.8 to 1.3 points more productivity growth a year over the next decade.
The authors estimate AI's effect on productivity growth over the next decade with two approaches. Comparing AI with past technological revolutions gives 0.8-1.3 percentage points of extra annual productivity growth, while a task-based approach in the spirit of Acemoglu (2024), using their own reading of the evidence, gives a median of 0.68 percentage points of extra TFP growth.
- The Productivity J-Curve: How Intangibles Complement General Purpose TechnologiesErik Brynjolfsson et al. · American Economic Journal Macroeconomics · 2020 · Evidence against the claim
Why gains from a general-purpose technology show up late: the productivity J-curve of unmeasured complementary investment.
Argues that general-purpose technologies like AI require large, often-intangible complementary investments that official statistics undercount, producing a 'Productivity J-curve': measured productivity growth is understated early in a technology's diffusion and overstated later as those investments pay off. Applying the model to U.S. data on computer hardware and software, the authors estimate 2017 total factor productivity was 15.9% higher than official figures once intangible capital is included — a key reference point for economists arguing today's modest measured AI productivity gains understate its eventual impact.
- Thousands of AI Authors on the Future of AIKatja Grace et al. · Journal of Artificial Intelligence Research · 2025 · Mixed evidence
2,778 AI researchers put even odds on machines beating humans at every task by 2047, 13 years earlier than a year before.
A survey of 2,778 researchers who published in top AI venues in October 2023 put a 50% chance on machines outperforming humans at every task by 2047, 13 years earlier than the 2022 survey. Full automation of all occupations was not expected to reach 50% probability until 2116, and most respondents expressed substantial uncertainty about long-term impacts.
- Past Automation and Future A.I.: How Weak Links Tame the Growth ExplosionCharles I. Jones and Christopher Tonetti · Working paper · 2026 · Evidence against the claim
A 2026 growth model in which weak links keep incomes only 4% higher by 2050, even as growth accelerates.
- Longitudinal Expert AI Panel, Wave 6: Economic Effects of AIConnacher Murphy et al. · Forecasting Research Institute, LEAP Report 6 · 2026 · Mixed evidence
Experts, forecasters and the public expect about 2.5% growth to 2030 by default, and more under rapid progress.
Of these 3 papers: 1 with evidence for the claim, 1 with evidence against, 1 mixed.
Of these 5 papers: 1 with evidence for the claim, 2 with evidence against, 2 mixed.
Of these 5 papers: 1 with evidence for the claim, 2 with evidence against, 2 mixed.
Figures to know
- 2047AI researchers' 50% year for machines outperforming humans at every task (2023 survey)
Katja Grace et al., 2025 · Pace“the chance of unaided machines outperforming humans in every possible task was estimated at 10% by 2027, and 50% by 2047”
- 2061AI researchers' 50% year for AI outperforming humans at all tasks (2016 survey)
Katja Grace et al., 2017 · Pace“when the aggregate prediction put 50% probability at 2061, i.e. 45 years out”
- 2026Earliest year “powerful AI” could arrive
Dario Amodei, 2024 · Pace“I think it could come as early as 2026, though there are also ways it could take much longer.”
- +0.04 pp a yearPermanent effect on annual productivity growth (upper bound)
Alex Arnon, 2025 · Pace“with a permanent effect of less than 0.04 percentage points due to sectoral shifts”
- 11%S&P 500 firms with AI deeply integrated into business processes, 2025, 2025
Yang Yu et al., 2026 · Pace“In 2025, 11% of S&P 500 enterprises had AI deeply integrated into their business processes”
Every number is quoted from its source and linked to the paper; estimates differ in method and horizon, so they are not directly comparable.
People to follow
- Erik Brynjolfsson agreesEconomist, Stanford University
Co-author of the productivity J-curve, which explains why a technology's gains can arrive with a delay.
Key work: Race Against the Machine: How the Digital Revolution is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy; The Productivity J-Curve: How Intangibles Complement General Purpose Technologies
- Daron Acemoglu leans disagreeEconomist, Massachusetts Institute of Technology
Has a documented position that transformative effects will take longer than a decade.
Key work: Robots and Jobs: Evidence from US Labor Markets; The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment
- Arvind Narayanan leans disagreeComputer scientist, Princeton University
Princeton computer scientist and co-author of 'AI Snake Oil', who argues AI will spread like a normal technology.
Key work: AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference; Leakage and the reproducibility crisis in machine-learning-based science
- Yoshua Bengio leans agreeComputer scientist, Université de Montréal
Has a documented position that transformative effects could arrive within about a decade.
Key work: Deep learning; Generative adversarial networks
- Anton Korinek leans agreeEconomist, University of Virginia
Models fast and slow paths to highly capable AI and what each would mean for growth.
Key work: Artificial Intelligence and Its Implications for Income Distribution and Unemployment; Excessive Volatility in Capital Flows: A Pigouvian Taxation Approach
Of these 3 people: 1 agrees, 2 leans disagree. Documented, cited positions only.
Of these 5 people: 1 agrees, 2 leans agree, 2 leans disagree. Documented, cited positions only.
Of these 5 people: 1 agrees, 2 leans agree, 2 leans disagree. Documented, cited positions only.
Newsletters and sources
- Justified Posteriors (Andrey Fradkin)Newsletter · 7 posts in this guide
Discusses forecasts of AI's economic effects as they appear.
- Ghosts of Electricity (Alex Imas)Newsletter · 2 posts in this guide
Compares how fast AI is spreading with how past technologies spread.
- Stanford AI Index ReportStanford Institute for Human-Centered AI · report · outside this guide
A yearly measure of AI capabilities, adoption and investment, useful for tracking the pace.
- Our World in Data: Artificial IntelligenceOur World in Data · dataset · outside this guide
Long-run charts of AI training compute, capabilities and adoption.