Fed's Daly Says AI Valuations Require Productivity Gains, Not Bubble
6h ago|4 min read1Standard
Fazen Markets Editorial Desk
Collective editorial team · methodology
artificial-intelligence
Fazen Markets Editorial Desk
Collective editorial team · methodology
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San Francisco Federal Reserve President Mary Daly stated on May 29, 2026, that the current valuation of artificial intelligence technology does not constitute a bubble if the sector delivers tangible productivity gains. The remarks, reported by SeekingAlpha, come as major AI-related stock indices and companies have seen historic gains. The Nasdaq-100 index has surged over 120% from its October 2022 low, driven largely by AI enthusiasm. Nvidia, a primary beneficiary of the AI infrastructure buildout, has seen its market capitalization increase by more than 500% over the same period, briefly surpassing $3 trillion.
Daly's comments arrive at a critical juncture for technology valuations and monetary policy. The Federal Reserve is currently in a pause phase, with the benchmark federal funds rate holding at a range of 4.50% to 4.75%. The 10-year Treasury yield is trading near 4.2%, providing a higher discount rate for future earnings than during the zero-rate era of the early 2020s. This backdrop makes the justification for premium valuations more challenging, placing greater emphasis on realized earnings and productivity.
The catalyst for renewed scrutiny is the sheer magnitude and speed of the AI-driven market rally. The last comparable technology-led valuation surge was the dot-com bubble of the late 1990s. The Nasdaq Composite index rose over 400% from 1995 to its peak in March 2000, before collapsing by 78% by October 2002. A key difference cited by analysts is the current cohort of leading AI firms, like Nvidia and Microsoft, already generating substantial revenue and profit, unlike many dot-com era companies.
Current debate centers on whether AI adoption will follow an S-curve of rapid productivity improvement or face implementation lags. Daly's framing directly addresses this uncertainty by linking market stability to measurable economic output. Her position as President of the San Francisco Fed, which oversees the technology-rich Twelfth District, lends weight to her assessment of sector-specific risks and opportunities.
Concrete metrics illustrate the scale of the AI investment surge and the high expectations embedded in valuations. The Nasdaq-100 index closed at 19,842 on May 28, 2026, representing a 120% gain from its October 14, 2022, low of 9,006. The forward price-to-earnings ratio for the index stands at 28.5, compared to a 10-year average of 22.7. The S&P 500 Information Technology sector trades at a forward P/E of 30.1, a 65% premium to the broader S&P 500's 18.2.
Key AI infrastructure stocks show even more pronounced multiples. Nvidia's forward P/E is 37.2, while Advanced Micro Devices trades at 31.5. These valuations imply sustained high-double-digit earnings growth for years. Capital expenditure forecasts support this growth narrative. Global data center capital spending is projected to reach $500 billion in 2026, up from $300 billion in 2023, with AI-related spend constituting over 40%.
A comparison of enterprise value to sales ratios highlights the concentration of premium valuations.
| Company | EV/Sales (2026E) |
|---|---|
| Nvidia (NVDA) | 18.2x |
| Broadcom (AVGO) | 10.1x |
| Microsoft (MSFT) | 9.8x |
| S&P 500 Index | 2.4x |
Investment flows confirm the trend. The iShares Semiconductor ETF (SOXX) has seen net inflows of $12.4 billion year-to-date, while technology sector funds globally have attracted over $85 billion in 2026.
Daly's productivity test creates clear winners and losers across sectors. Primary beneficiaries are companies enabling measurable efficiency gains. This includes semiconductor capital equipment firms like Applied Materials (AMAT) and Lam Research (LRCX), which supply the tools to build advanced chips. Enterprise software providers integrating generative AI into workflows, such as Salesforce (CRM) and ServiceNow (NOW), also stand to gain if they demonstrably reduce operational costs for clients.
Sectors facing headwinds include those with high labor costs and slower AI integration pathways. Healthcare services and certain industrial subsectors may underperform if investors reallocate capital toward proven productivity engines. The risk is a bifurcated market where capital flows exclusively to firms with clear AI monetization, leaving other sectors behind. A counter-argument to Daly's framework is that financial markets can remain disconnected from fundamental productivity metrics for extended periods, as seen in previous technology manias. Speculative capital can inflate asset prices well ahead of any measurable economic impact.
Positioning data from the Commodity Futures Trading Commission shows asset managers have built significant net long positions in Nasdaq-100 futures. Hedge funds, however, have increased short exposure to single-name technology stocks, betting on dispersion and a shakeout among weaker AI narratives. Flow analysis indicates rotation within the tech sector from pure-play AI software names toward hardware and infrastructure providers with more tangible order books.
Markets will monitor several imminent catalysts to assess the productivity thesis. The next Federal Open Market Committee decision on June 18, 2026, will provide updated dot plots and economic projections, including potential revisions to long-run growth estimates that could reflect AI optimism. The July 2026 earnings season, commencing with major banks on July 14, will offer the first broad look at Q2 corporate spending on AI integration and any early efficiency gains in profit margins.
Key levels to watch include the Nasdaq-100's 50-day moving average, currently at 19,200, as a near-term support gauge. A sustained break below this level could signal a reassessment of growth expectations. For bond markets, the 10-year Treasury yield holding above 4.5% would increase pressure on equity valuations by raising the discount rate for future earnings, making Daly's productivity requirement more urgent. Sector rotation will be evident in the relative performance of the Technology Select Sector SPDR Fund (XLK) versus the Industrial Select Sector SPDR Fund (XLI).
Productivity is measured as output per hour worked. The Bureau of Labor Statistics publishes quarterly Labor Productivity data. A sustained acceleration in this figure, particularly in the nonfarm business sector, would validate the AI investment thesis. Historical precedent shows the 1990s tech boom contributed to a productivity growth surge averaging 2.5% annually from 1995-2004, double the rate of the prior two decades. Early indicators include software and intellectual property investment within GDP reports.
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