Why Most Economists Say AI Won’t Buy the Fed Faster Rate Cuts

• TL;DR
• Nearly 60% of 45 surveyed macroeconomists expect AI’s net effect on inflation and the neutral interest rate over the next 24 months to be essentially zero.
• Most forecast under a 0.2 percentage‑point change to PCE inflation and the neutral rate from AI in the near term; a sizable minority think AI could push rates higher.
• Practical takeaway for leaders: treat AI automation and AI agents as strategic, long‑term productivity plays — don’t assume immediate cheaper financing from Fed rate cuts.

Why this finding matters for businesses

Executives who hear forecasts of an “AI productivity boom” must decide whether to change capital plans, hiring, and M&A assumptions. The poll of 45 U.S. macroeconomists run by the University of Chicago’s Clark Center and the Financial Times found most experts are skeptical that generative AI will deliver quick, measurable disinflation or a lower neutral interest rate (r*) within two years. That has direct implications for borrowing costs, project economics, and strategy around AI for business — from deploying AI agents and ChatGPT‑style automation to scaling data centers and cloud infrastructure.

What the poll actually found

Key results are straightforward:

• Nearly 60% of respondents expect AI’s impact on PCE inflation (personal consumption expenditures, the Fed’s preferred inflation measure) and the neutral interest rate to be close to zero over the next 24 months.
• Most economists expect AI to reduce both PCE inflation and the neutral rate by less than 0.2 percentage points over two years.
• Roughly one‑third of respondents think AI could push the neutral rate slightly higher, driven by near‑term investment and demand pressures.
• More than 75% favored taking the Fed’s balance sheet below $6 trillion within two years — but conditionally (market stability and adequate liquidity required). Quantitative tightening previously reduced assets from roughly $9 trillion to $6.6 trillion.
• Over 60% said loosening financial regulation would offer little short‑term growth boost and could raise systemic risk.

How AI can affect inflation and the neutral rate: three channels

Economists’ split view reflects three competing mechanisms — each with its own timing and uncertainty.

1) Productivity (disinflation) channel

AI automation (including AI agents and AI for sales) can raise output per worker, lower unit labor costs, and shrink margins for firms that pass savings to consumers. But productivity gains from software often arrive unevenly: process redesign, training, and integration take time. Large, economy‑wide gains require widespread adoption, standards, and organizational change — not just point deployments of ChatGPT‑style systems.

2) Demand (inflationary) channel

Scaling AI takes capital: data centers, servers, networking, power upgrades, and skilled workers. Those near‑term investments create demand for construction, equipment, and energy that can lift prices while physical capacity catches up. Fed officials, including Vice Chair Philip Jefferson (paraphrase), warned that an immediate spike in AI‑related demand could temporarily raise inflation even if long‑run productive capacity ultimately increases.

3) Financial (policy) channel

Monetary policy tools — the policy rate and the Fed’s balance sheet — interact with AI’s macro effects. Quantitative tightening (QT) can put upward pressure on long‑term yields; combining aggressive balance‑sheet reduction with rapid rate cuts would be an unusual policy mix and could push mortgage and corporate borrowing costs higher if markets perceive liquidity risks.

Where the disagreement comes from

A conservative majority in the poll expects the productivity payoff to be gradual and therefore insufficient to shift Fed policy quickly. A meaningful minority worry that concentrated capex and tight labor markets in AI‑heavy sectors could raise the neutral rate in the short run. As Notre Dame economist Jane Ryngaert (paraphrase) put it: there’s a lot of uncertainty — strong conclusions are premature.

“I don’t see the near‑term AI surge as a clear disinflationary shock — nor as strongly inflationary in the short run.”
— Jonathan Wright (paraphrase)

“Even if AI raises long‑run productive capacity, an immediate increase in AI‑related demand could temporarily lift inflation.”
— Philip Jefferson (paraphrase)

“The AI boom could either lead to booming growth, smaller deficits, higher neutral rates and comfortable balance‑sheet shrinkage — or cause a market crash, deep recession, larger deficits, near‑zero rates, dollar weakness and renewed balance‑sheet expansion.”
— Robert Barbera (paraphrase)

Fed policy, politics, and balance‑sheet tradeoffs

At the time of the survey the federal funds target was around 3.5%–3.75%. Political voices pushed for much lower rates (some arguing rates near 1%), while the Fed’s projection was for a modest 0.25% cut that year. Economists’ skepticism about rapid AI‑driven disinflation undercuts arguments — like those made by Kevin Warsh during his Fed chair nomination — that AI alone should justify faster, larger rate cuts.

Most poll respondents support further balance‑sheet reduction to below $6 trillion, but nearly all condition that on market stability. Harvard economist Karen Dynan (paraphrase) summarized the conditional view: shrinking the Fed’s asset holdings can be reasonable if markets remain orderly and liquidity is sufficient. Aggressive QT without clear market resilience could raise long‑term borrowing costs and further pressure housing affordability.

Case example: AI automation that didn’t change the financing story

A mid‑sized retailer implemented AI agents to automate customer service, reducing full‑time equivalent hours by 20% in a year and improving conversion rates through AI‑augmented sales scripts. Operational margins improved, but the firm’s capital needs rose because it invested in cloud contracts, new monitoring systems, and cybersecurity. Short‑term cashflow improved, but debt maturity and refinancing plans remained unchanged: cheaper credit did not materialize because macro rates and long‑term yields stayed elevated. The AI investment paid off on margins and competitive positioning — but it didn’t change the firm’s cost of capital immediately.

What leaders should do now

Plan on two horizons. Near term (0–24 months): assume limited macro relief from AI and model financing accordingly. Medium term (2–10 years): capture structural gains from AI automation that will compound if adoption and complementary investments continue.

Action steps for CFOs and strategy leaders

• Stress‑test debt under higher-rate scenarios. Model budgets assuming policy and market rates remain 1–2 percentage points above pre‑COVID norms for 12–24 months.
• Prioritize AI projects with <18‑month payback or durable revenue boosts. Favor automation that improves margins, reduces churn, or directly lifts sales (AI for sales use cases, for example).
• Measure process‑level ROI, not just hype. Track unit labor costs, cycle times, and conversion lift from AI agents to isolate productivity gains.
• Plan capex with sequencing in mind. Balance near‑term infrastructure needs (cloud, observability, security) against their inflationary footprint and timing.
• Watch policy signals and specific data. Key indicators: core PCE (exclude volatile items and shelter), unit labor costs, productivity per hour, tech CAPEX, and AI‑sector hiring and construction activity.

What to watch next

• Core PCE and productivity trends: sustained declines in core PCE driven by productivity improvements would be the clearest sign that AI is materially cooling inflation.
• Tech CAPEX and data‑center build rates: if capex surges faster than capacity growth, expect transitory inflation pressure.
• Fed communications and balance‑sheet guidance: conditional QT plans give a useful signal about how much room the Fed believes it has to cut rates without destabilizing markets.
• Adoption breadth: are AI gains concentrated in a few firms/sectors or spreading across service and manufacturing industries? Broader diffusion accelerates macro impact.

Bottom line for executives

AI automation, AI agents, and tools like ChatGPT are real strategic levers for companies. They will reshape workflows, customer engagement, and competitive dynamics. However, most macroeconomists do not expect those changes to translate into immediate Fed rate relief or materially lower neutral rates within two years. Business leaders should invest in AI where it improves margins, revenue, or strategic positioning — but budget and finance teams should plan assuming higher borrowing costs persist until clear macro evidence proves otherwise.