“The United States is likely to be a big winner over the medium term in [AI]. But I do not say this from a parochial perspective. The U.S. is not afraid of productivity-led economic growth, but we do not view the economics of this as zero-sum. We are not rooting for another country to fail. We are rooting for economic growth to be broad-based.” – Kevin Warsh – Chair of the Board of Governors of the Federal Reserve, CNBC policy panel at the ECB Forum on Central Banking 1 July 2026

The real tension in this argument is not whether artificial intelligence can raise output, but whether a central bank should welcome a productivity surge that makes the economy larger while leaving the distribution of gains, the pace of disinflation and the policy stance deeply uncertain. Warsh’s position places AI inside a classical Federal Reserve dilemma: faster productivity can support higher living standards and stronger growth, yet it can also complicate the inflation outlook, shift labour bargaining power and force policymakers to decide whether they are looking at a temporary surge, a structural break, or both at once.^1,7,14

That matters because the Federal Reserve is not only a steward of prices; it is also a narrator of the economy’s capacity. If AI raises productivity materially, then the economy’s non-inflationary speed limit rises with it. In that world, the Fed can potentially tolerate more demand before inflation re-accelerates, and real incomes can grow faster without the usual trade-off tightening. But the same mechanism can destabilise policy if officials misread the timing. The central bank may be forced to act on a productivity shift before the shift is visible in the official data, which is precisely why recent Federal Reserve research has stressed the problem of real-time recognition: trend changes can look obvious in hindsight while remaining elusive as they unfold.¹⁴

Growth without zero-sum thinking

The most important strategic claim is the rejection of a zero-sum frame. Warsh is drawing a line between relative national advantage and absolute global welfare: the United States may be best placed to capture the early gains from AI, but that does not require another economy to lose in order for the U.S. to win.^1,7 That distinction matters because debates over AI have often been framed either as a race for dominance or as a social threat. His language instead treats AI as a general-purpose technology whose spillovers can lift productivity across sectors and countries, even if adoption is uneven and the initial gains are concentrated in the most advanced economies.^5,23

This is a conventional but important macroeconomic argument. Productivity-led growth is usually the cleanest form of expansion because it allows output to rise without a commensurate rise in inflationary pressure. That is why several economists and market strategists have argued that AI could support a new growth phase in the United States while restraining costs.^5,12,18 In that reading, the United States benefits not because others are excluded, but because it has a deeper capital market, stronger compute infrastructure, more flexible firms and a labour market that can reallocate resources faster than many peers.^5,25

The central banking problem behind the optimism

For a central banker, the attractive version of AI is straightforward: more output per worker, better margins, stronger investment and a higher equilibrium level of GDP. The difficult version is that the same productivity wave can arrive through uneven channels. Some firms may cut costs quickly while others remain stuck with legacy systems; some workers may become dramatically more productive while others see wage pressure; some sectors may experience rapid disinflation while others absorb the cost of retraining and capital replacement.^11,20,23

That unevenness is why the policy question is not merely whether AI is good or bad, but how quickly its effects propagate. Recent empirical work suggests that productivity gains are already visible in some firms and sectors, yet the aggregate picture remains narrower than the headline enthusiasm would imply.^11,20 The Kansas City Fed notes that labour productivity has risen above its pre-pandemic trend, but the pickup is not yet broadly based, with a small set of industries accounting for most of the gains.¹¹ That is important because broad-based productivity growth changes the macroeconomy differently from a narrow sectoral boom: if the gains stay concentrated, the Fed sees stronger demand in some areas without a clean economy-wide supply response.

Federal Reserve research has also emphasised that a change in trend productivity affects interest rates only after households and firms become convinced it is durable.¹⁴ In practice, that means AI can lift investment and consumption before it fully alters inflation expectations or policy settings. During that adjustment period, the economy may behave as though it has received a temporary productivity shock even if the underlying change turns out to be permanent.¹⁴ That is one reason Warsh’s comments are strategically significant: they imply that the Fed should be thinking about AI not as a distant technological curiosity, but as a variable that may already be feeding into policy calibration.

Why the inflation debate is unavoidable

The most contested part of the AI-growth story is not output, but prices. If AI compresses unit labour costs, expands supply capacity and speeds up innovation, it can help offset inflation even when demand remains firm. That is the optimistic case behind the idea of productivity-based growth.^12,15,18 Yet sceptics argue that the near-term effect may be more ambiguous: firms could spend heavily on AI infrastructure before the productivity dividend shows up, creating demand for chips, data centres, electricity and labour without an immediate matching supply response.^4,20

That tension is visible in the policy debate around Warsh himself. Reuters reported that he entered the ECB Forum after taking a hawkish tone on inflation and signalling commitment to the Federal Reserve’s 2% target.⁷ At the same time, market commentary and analyst notes have connected his AI remarks to the possibility of a more growth-tolerant policy regime if productivity accelerates enough to justify lower rates.^12,15 The implication is not that AI automatically leads to easier money, but that it can widen the set of plausible policy outcomes. A stronger supply side may give the Fed more room to support growth without stoking prices, though only if the productivity gains are real, durable and broad enough to matter at the aggregate level.

That conditionality is why many economists remain cautious. The Dallas Fed, for example, suggests a scenario in which AI boosts productivity growth by around 0,3 percentage points per year over the next decade, a meaningful but not transformative effect.¹⁷ The Penn Wharton Budget Model reaches a similar conclusion in level terms: AI could lift productivity and GDP over time, but the uplift is gradual, concentrated and sensitive to adoption assumptions.⁸ In other words, the best-case macro story is plausible, but the case for dramatic near-term disinflation is still unproven.

Productivity gains may not be evenly shared

Warsh’s emphasis on broad-based growth matters because the benefits of AI are unlikely to be distributed evenly across workers, firms or regions. Research reviews and sectoral studies repeatedly show that gains are concentrated in data-intensive and cognitively routinised activities such as finance, consulting, software and parts of healthcare, while more physical or human-interaction-intensive sectors are less exposed in the short run.^23,25 That does not weaken the long-run case for AI as a growth engine, but it does complicate the political economy of the transition.

The labour-market concern is not simply job loss, but bargaining-power loss. If AI makes some workers much more productive while leaving others behind, wage dispersion can widen even when aggregate employment remains stable.^2,20 One interpretation of the technology is that it raises the premium on complementary skills while flattening demand for mid-level routine tasks. That would fit the pattern seen in earlier technological waves, where the economy created new roles even as it displaced old ones, but not necessarily at the same speed or for the same groups.^2,23 For a central banker, this is crucial because inflation dynamics are shaped not only by productivity, but by wages, expectations and the speed with which labour markets adapt.

This is where the broader research base adds nuance. The Atlanta Fed’s recent work finds a gap between firms’ reported productivity gains from AI and the gains implied by contemporaneous revenue and employment data.²⁰ That suggests companies may be experiencing early efficiency benefits before they fully show up in measured output. It also supports a common pattern in general-purpose technologies: the first wave often reveals managerial and operational gains before the macro statistics catch up.^14,20 A policymaker who waits for perfect measurement may arrive late; a policymaker who reacts too early risks tightening or easing on the basis of incomplete evidence.

Why the U.S. may be structurally advantaged

Warsh’s confidence that the United States could be a major winner over the medium term reflects more than national preference. The U.S. has a dense ecosystem of capital, research universities, hyperscale cloud providers, venture finance and firms willing to deploy capital quickly.^5,25 Those institutional advantages matter because AI adoption is not just a software decision; it requires investment in infrastructure, talent, data governance and organisational redesign. The countries that can fund that stack at scale are likely to capture more of the early returns.²³

That helps explain why much of the current debate has shifted from abstract possibility to concrete investment cycles. If the AI build-out continues, it can support real activity through capital expenditure before productivity gains broaden out into household income and margin expansion.^4,5 That sequencing is important. The market may first observe stronger earnings in the firms supplying chips, cloud capacity and associated infrastructure, while the broader economy benefits later through lower costs and faster output growth. The lag between investment and diffusion is the bridge between the stock market narrative and the macroeconomic narrative.

But there is also a strategic risk in assuming that early leadership guarantees durable advantage. AI diffusion can be fast once the technologies become embedded, and the gains are likely to spread across advanced economies that have the institutional capacity to adopt them.²³ Warsh’s non-zero-sum framing implicitly recognises that even if the U.S. leads, the contest is not only against rivals but against domestic inertia. If firms underinvest, if regulation slows deployment, or if labour-market frictions prevent reallocation, the productivity dividend could be smaller than expected.^5,25

The market implication

The market significance of this view is that it changes the range of interest-rate outcomes investors should consider. If AI materially raises trend productivity, then the neutral rate may be higher than previously assumed, real growth may surprise on the upside and corporate earnings could benefit from both stronger demand and higher margins.^12,15,18 That would be supportive for risk assets over time, even if the transition is volatile. A stronger supply side can also reduce the odds that productivity-led growth becomes inflationary, which matters directly for bond yields and the policy path.

Yet markets are vulnerable to over-interpreting the early signs. Productivity booms are often noisy in the beginning, and the statistical picture can lag lived reality by years.¹⁴ That means investors may oscillate between two extremes: either treating AI as an immediate macro revolution or dismissing it as a narrow capex story. The more defensible position lies between those poles. The evidence points to meaningful medium-term upside, but not a mechanical, straight-line conversion from model capability to national growth.

What makes Warsh’s remark especially consequential is that it places this debate inside the Fed’s policy architecture. If AI boosts growth broadly, then the central bank may have more room to protect the labour market without abandoning price stability. If the gains are slower, narrower or more concentrated than hoped, the Fed will still face the old trade-offs, only with a more complex narrative attached. Either way, the issue is no longer whether AI is relevant to macro policy. It is how quickly the institution can distinguish between a genuine structural shift and a noisy burst of optimism, while markets, firms and workers are already adjusting around it.

 

References

1. https://www.youtube.com/watch?v=Ohg5Sav1kpw – https://www.youtube.com/watch?v=Ohg5Sav1kpw

2. Kevin Warsh ECB forum live updates: Fed chair speaks – CNBC – 2026-07-01 – https://www.cnbc.com/2026/07/01/kevin-warsh-ecb-forum-live-updates.html

3. Workers Are Getting More Productive. How Will Fed Policy Change? – 2025-12-22 – https://www.youtube.com/watch?v=P8fgoHiNTBM

4. Kevin Warsh Downplays Concerns Of Job Losses Due To AI, Says … – 2026-07-01 – https://stocktwits.com/news-articles/markets/equity/kevin-warsh-downplays-ai-job-loss-concerns-not-a-doomer/cZm3LPeR7Kx

5. Fed chief Warsh attends ECB forum with Lagarde, Bailey & Macklem – 2026-07-01 – https://www.youtube.com/watch?v=edlh4dpZcwk

6. The rising tide of AI: How it could lift US productivity, growth, and profits – 2025-11-28 – https://www.wellington.com/en/insights/how-ai-could-power-us-economy-productivity-growth-profits

7. Federal Reserve Nominee Warsh Says AI is Reshaping the Economy – 2026-04-21 – https://www.meritalk.com/articles/federal-reserve-nominee-warsh-says-ai-is-reshaping-the-economy/

8. Fed’s Warsh: Will decide on rate hike when policymakers … – Reuters – 2026-07-01 – https://www.reuters.com/world/europe/warsh-hits-international-stage-with-peers-sharing-an-inflation-problem-2026-07-01/

9. The Projected Impact of Generative AI on Future Productivity Growth – 2025-09-08 – https://budgetmodel.wharton.upenn.edu/p/2025-09-08-the-projected-impact-of-generative-ai-on-future-productivity-growth/

10. AI & the U.S. Productivity Wave with Kevin Warsh and Sadi Khan – 2025-12-04 – https://www.youtube.com/watch?v=6LtRcC-JgBI

11. Warsh Only Briefly Talks Rates, but Is ‘Recommitted’ to the … – Barron’s – 2026-07-01 – https://www.barrons.com/articles/kevin-warsh-europe-federal-reserve-inflation-fb47cb0f

12. A New U.S. Productivity Chapter? What Industry Data Say About AI – 2026-02-11 – https://www.kansascityfed.org/research/economic-bulletin/a-new-us-productivity-chapter-what-industry-data-say-about-ai/

13. What Kevin Warsh Could means for Rates, Inflation and AI – 2026-02-11 – https://www.citizensbank.com/private-banking/insights/new-fed-chair-kevin-warsh-impact-on-markets.aspx

14. Fed Chairman Kevin Warsh thinks the AI boom and massive capital … – 2026-07-01 – https://www.instagram.com/reel/DaQSH4TkvMe/

15. Productivity Growth and the Challenge of Real-Time Policymaking – 2026-05-28 – https://www.newyorkfed.org/newsevents/speeches/2026/wil260528

16. Kevin Warsh Pitched a Case for Fed Rate Cuts. His Future … – WSJ – 2026-04-20 – https://www.wsj.com/economy/central-banking/fed-interest-rates-warsh-ai-bc92f894

17. How can we shape Europe’s future, and what role do innovation … – 2026-06-23 – https://www.facebook.com/christinelagarde/videos/how-can-we-shape-europes-future-and-what-role-do-innovation-growth-and-stability/2573238053081878/

18. Advances in AI will boost productivity, living standards over time – 2025-06-24 – https://www.dallasfed.org/research/economics/2025/0624

19. Kevin Warsh confident AI will generate ‘productivity-based growth’ – 2026-07-01 – https://www.ft.com/content/05dd7853-6fab-4a22-8644-8b3f1522f5ad

20. Fed Chairman Kevin Warsh responds to the market thinking he’s … – 2026-07-01 – https://www.instagram.com/reel/DaQZkCDjQ7D/

21. [PDF] Artificial Intelligence, Productivity, and the Workforce: Evidence from … – 2026-03-25 – https://www.atlantafed.org/-/media/Project/Atlanta/FRBA/Documents/research/publication/working-paper/2026/03/25/04-artificial-intelligence-productivity-and-the-workforce-evidence-from-corporate-executives.pdf

22. Warsh’s AI task force could reshape Fed economic models – Facebook – 2026-06-23 – https://www.facebook.com/TheStreet/posts/warshs-ai-task-force-could-reshape-fed-economic-modelswarshs-quiet-ai-move-could/1550754776645901/

23. 2026 ECB Forum – Speakers – European Union – 2026-07-01 – https://www.ecb.europa.eu/press/conferences/ecbforum/html/speakers_and_papers.en.html

24. Productivity, growth and employment in the AI era: a literature review – 2025-09-09 – https://economic-research.bnpparibas.com/html/en-US/Productivity-growth-employment-AI-literature-review-9/9/2025,51822

25. Can AI Help the U.S. Economy Grow Faster Without Igniting Inflation? – 2026-02-02 – https://thepeopleseconomist.substack.com/p/americas-economic-speed-limit-can

26. AI, Productivity, and Labor Markets: A Review of the Empirical … – 2026-02-05 – https://laweconcenter.org/resources/ai-productivity-and-labor-markets-a-review-of-the-empirical-evidence/

27. Fed nominee Kevin Warsh thinks AI is “the most disruptive moment … – 2026-04-21 – https://www.facebook.com/yahoofinance/posts/fed-nominee-kevin-warsh-thinks-ai-is-the-most-disruptive-moment-in-economic-hist/1324791259515649/