“…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
“…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
“…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
“Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
“…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
“…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
“…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
“…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
“Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
AI Summary.The authors estimate AI capital spending of $560bn in 2026 and, in a high-investment case, $3.5tn of net AI capital in service by 2030, requiring roughly $1.3tn in annual infrastructure revenue once depreciation, operating costs and a 15% return are covered. That implies 7.4x growth from current annualized revenues, with downstream revenues of $1.9–2.6tn.
William Gildea and Azeem AzharExponential View
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Beginning with capex projections, Gildea/Azhar derive for their high-growth case a $1.3T annual AI-infrastructure revenue hurdle for 2030. This covers $771B of depreciation and operating costs, plus a 15% return on $3.5T of net capital in service.
How much annual revenue must AI infrastructure generate to justify investment?
Core argument: In a high investment case with $3.5tn of net AI capital in service, the authors estimate AI infrastructure must generate $1.3tn of annual revenue by 2030, requiring 7.4x growth (59% CAGR) from today’s annualized revenues.
We estimate AI CapEx to be $560B in 2026, 64% of the total declared by the hyperscalers. Unfinished facilities can’t generate revenue, so the investment bill and the productive asset base will grow at different speeds. [In the high investment case], by 2030 we see $3.5T of net AI capital in service. The largest component [of the revenue hurdle] is the $555B in compute depreciation. We model lifespans at the current 5-6 years. Shell depreciation and OpEx combined contribute about a further $216B to the required revenue hurdle. [Adding a 15% return on net capital brings required annual infrastructure revenue to $1.3T]. Reaching the $1.3T hurdle would represent 7.4x growth (59% CAGR) from today’s annualized revenues. For its customers to earn 30-50% gross margins, downstream revenues need to be $1.9-2.6T. [Editor’s note: Van Nieuwerburgh’s far larger figure of $3.7T covers mature revenues from projects completed through 2032, using commissioning capital and a 50% infrastructure operating cash-flow margin. This estimate instead charges depreciation and operating costs plus 15% on net capital in service in 2030. Different horizons and cost conventions prevent a direct comparison. Van Nieuwerburgh also has a much higher capex estimate.]
Takeaways by Macro Roundup® AI
In a high investment case with $3.5tn of net AI capital in service, the authors estimate AI infrastructure must generate $1.3tn of annual revenue by 2030, requiring 7.4x growth (59% CAGR) from today’s annualized revenues.
Compute depreciation of $555bn, modeled on 5-6 year lifespans, is the largest component of the 2030 revenue hurdle, with shell depreciation and operating expenses adding about $216bn and a 15% return on net capital completing the $1.3tn total.
Related Articles:
Financing the AI Buildout— The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
What Investment Data Implies about the AI Transition— The five largest U.S. technology firms are scaling AI capital spending about 50% a year, from $155bn to a forecast $755bn. Embedding this in a two-sector model with rare productivity booms, the authors estimate AI adds roughly 5, 20, or 58pp to cumulative growth over a seven-year transition, depending on scenario.
Rear Window— Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.
AI Summary.Demand and supply curves estimated from pre-pandemic data imply relatively flat demand curves in the US and euro area, so adverse supply shifts would produce large output losses but comparatively little inflation. The authors argue explaining the observed combination of high inflation and output requires outward demand shifts, including accommodative monetary policy alongside fiscal expansion.
Domenico Giannone and Giorgio PrimiceriBookings Papers on Economic Activity
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Giannone and Primiceri revisit the relative role of supply vs. demand shocks in generating the post-Covid inflation. Because aggregate demand curves estimated from pre-pandemic data are flat, supply shocks alone would not have generated large inflation in the absence of added demand stimulus.
Did outward demand shifts, not supply shocks alone, drive recent inflation?
Core argument: Demand curves estimated from pre-pandemic US and euro-area data are relatively flat, reflecting central banks’ strong pre-pandemic responses to inflation, so adverse supply shifts produce large output losses but comparatively little inflation.
Demand and supply curve slopes are estimated from pre-pandemic data using the essentially definitional restriction that supply shocks move prices and output in opposite directions along demand curves, while demand shocks move them together along supply curves; the plotted slopes represent Bayesian posterior medians rather than uniquely identified estimates. The estimated demand curves are relatively flat in both the US and euro area [Figure 7], reflecting the central banks’ strong pre-pandemic responses to inflation. With those slopes, adverse supply shifts cause large output losses but comparatively little inflation. [To successfully explain] the combination of inflation and output observed in 2022 therefore requires demand to shift outwards too. Strong demand, including unusually accommodative monetary policy [on top of strong fiscal expansion], cushioned the output losses while increasing inflation [Figure 7]. In 2021–22, both inflation and GDP as subsequently revised exceeded forecasts in the US and euro area. That combination is suggestive of unexpectedly strong demand, whereas an adverse supply surprise alone would raise inflation but lower output. [Figure 9].
Takeaways by Macro Roundup® AI
Demand curves estimated from pre-pandemic US and euro-area data are relatively flat, reflecting central banks’ strong pre-pandemic responses to inflation, so adverse supply shifts produce large output losses but comparatively little inflation.
Explaining the 2022 combination of inflation and output requires an outward shift in demand, with strong demand — including unusually accommodative monetary policy atop fiscal expansion — cushioning output losses while raising inflation.
In 2021–22, both inflation and GDP as subsequently revised exceeded forecasts in the US and euro area, a combination suggestive of unexpectedly strong demand, since an adverse supply surprise alone would raise inflation but lower output.
Related Articles:
Are Government Bonds Safe in Times of War and Pandemic?— Government bonds severely underperform in wartime, in absolute terms and relative to equities, housing, and economic growth, unlike in financial crises when bonds tend to outperform stocks. The U.S. and U.K. reduced war-driven debt-to-GDP ratios without explicit default, using surprise inflation and financial repression that shifted fiscal burdens onto bondholders.
Why Did Inflation Rise And Fall In 2021-24? Channels And Evidence From Expectations— Across countries, unexpectedly higher government deficits relative to earlier International Monetary Fund forecasts are associated with unexpectedly higher inflation, measured by each factor's contribution to the increase in public debt, a relationship the author finds statistically significant. This evidence is consistent with a fiscal channel for inflation.
Fiscal Influences on Inflation in OECD Countries, 2020-2022— Across 21 economies, the authors find that headline and core inflation responded positively to a measure of government spending increases scaled by pre-pandemic debt-to-GDP and average debt duration. Estimated coefficients of 0.4–0.5 suggest 40–50% of the extra spending was financed through inflation, with the rest through conventional public finance.
AI Summary.The gap between French and German 10-year government bond yields has widened at a pace matched only during the euro zone sovereign debt crisis. France and the UK have less room than the US to close deficits with tax increases, as tax revenues equal 43.9% of GDP in France and 35.3% in the UK versus 25.2% in the US.
John AuthersBloomberg
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The spread between 10-year French OATs and German Bunds has widened at a pace seen only during the eurozone sovereign-debt crisis. John Authers warns that France “satisfies all the classic conditions for a major debt crisis.”
Do high tax burdens limit France and the UK's deficit options?
Core argument: The spread of 10-year French OATs over German Bunds has risen at a pace matched only during the worst days of the euro-zone sovereign debt crisis in 2011 and 2012, fueling talk of a second crisis centered in Paris.
Only in the worst days of the euro zone’s sovereign debt crisis, in 2011 and 2012, has the [spread of 10-Year French OATS over German Bunds] risen so fast. Talk of a second euro-zone crisis, this time with an epicenter in Paris, is growing, and it’s easy to see why. Why is this more of a problem for France and the UK? Beyond their deficits, they also shoulder much higher tax burdens than the US. Tax revenues are 25.2% of GDP in the US, the lowest of the major developed economies - but 35.3% in the UK and 43.9% in France. It’s hard to imagine after decades of tax-cutting, but a US politician could deal with the deficit fairly easily with a tax hike. It’s not clear that option is open to French lawmakers, even if they could somehow persuade voters to go along with them. The populist politicians of left and right, who currently look well placed in next year’s presidential elections, are in any case unlikely to try.
Takeaways by Macro Roundup® AI
The spread of 10-year French OATs over German Bunds has risen at a pace matched only during the worst days of the euro-zone sovereign debt crisis in 2011 and 2012, fueling talk of a second crisis centered in Paris.
Tax revenues equal 25.2% of GDP in the US, the lowest among major developed economies, versus 35.3% in the UK and 43.9% in France, leaving American politicians more room to close the deficit with a tax hike.
Populist politicians of left and right, currently well placed for France’s presidential election, are unlikely to attempt tax increases to address the deficit.
Related Articles:
French PM to Freeze Emmanuel Macron’s Pension Reform Until 2027— France's prime minister said he would suspend the plan to raise the retirement age to 64 until the next presidential election, while asking parties to agree on other savings. He outlined a €30bn package of spending cuts and tax rises to cut the deficit to 4.7% of national output from 5.4%.
Soaring Bond Yields, Gaping Deficits and Towering Debts: What Could Go Wrong?— An analysis of 22 rich countries estimates that if each refinanced its entire debt at current five-year bond yields, Britain would need the largest primary surplus to stabilize its debt-to-GDP ratio, about 1.5%, followed by Italy at 1.4%, France at 1.2% and America at 1%.
Global Debt Report 2026— Gross central government borrowing across OECD countries rose 7% to a record $17tn, about 23% of GDP, and is projected to reach roughly $18tn, or 24% of GDP. The United States and Japan account for close to 80% of the area's refinancing requirements, with the US share rising from 57% to 70%.
AI Summary.The Institute of International Finance reports global debt as a share of output rose less than 10 percentage points between 2018 and mid-2026, peaking at 337% in early 2021 before falling 27 percentage points by the end of 2023. Inflation eroded the debt burden, as it did in the UK after the Second World War.
Martin WolfFinancial Times
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Wolf notes that the global debt-to-GDP ratio rose by less than 10pp btw 2018 and June 2026: after peaking at 337% in early 2021, it fell by 27pp by the end of 2023, as inflation boosted nominal GDP and eroded the value of existing debt.
Does inflation reduce the global debt burden?
Core argument: IIF data show the global debt-to-output ratio reached a post-Covid peak of 337% in early 2021 before falling by 27 percentage points by the end of 2023, with inflation identified as the force that eroded it.
The IIF shows that between 2018 and June 2026, the rise in the ratio of global debt to output was less than 10 percentage points. The story is striking: the ratio reached a post-Covid peak of 337% in early 2021, before falling by 27 percentage points by the end of 2023. What was this magical “debt-buster”? Good old-fashioned (and supposedly “unexpected”) inflation. This is — to put it mildly — not the first time inflation has wiped out debt. It was, to take one of countless examples, an important part of the UK’s elimination of its post-second-world-war debt. For countries able to print the money in which their debt is denominated, that is often what happens.
Takeaways by Macro Roundup® AI
IIF data show the global debt-to-output ratio reached a post-Covid peak of 337% in early 2021 before falling by 27 percentage points by the end of 2023, with inflation identified as the force that eroded it.
Between 2018 and June 2026, the IIF shows the ratio of global debt to output rose by less than 10 percentage points.
Inflation has wiped out debt before, forming an important part of the UK’s elimination of its post-second-world-war debt, and often does so for countries able to print the currency in which their debt is denominated.
Related Articles:
Are Government Bonds Safe in Times of War and Pandemic?— Government bonds severely underperform in wartime, in absolute terms and relative to equities, housing, and economic growth, unlike in financial crises when bonds tend to outperform stocks. The U.S. and U.K. reduced war-driven debt-to-GDP ratios without explicit default, using surprise inflation and financial repression that shifted fiscal burdens onto bondholders.
The Coming Great Repression?— Across countries and over time, higher public debt burdens are associated with lower relative returns on government bonds, the opposite of standard risk-premium predictions. The authors estimate financial repression—making banks captive bond buyers and loading them with low-return reserves—contributed 90.7 percentage points of GDP to Britain's postwar debt reduction, versus 20.3 from surprise inflation.
Global Debt Report 2026— Gross central government borrowing across OECD countries rose 7% to a record $17tn, about 23% of GDP, and is projected to reach roughly $18tn, or 24% of GDP. The United States and Japan account for close to 80% of the area's refinancing requirements, with the US share rising from 57% to 70%.
AI Summary.Entrepreneurship by businesses with employees is flat or declining, including in AI-intensive information and professional services, where establishment entry has been flat or falling and young-firm employment in AI-exposed industries is falling. Applications for likely solo businesses with no employees rose steeply in those AI-intensive sectors, but self-employment as a main job is flat, suggesting side hustles.
Nathan GoldschlagEconomic Innovation Group
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Nathan Goldschlag finds that available federal data do not yet establish that AI is boosting entrepreneurship. “Across different cuts of the data, there is no clear evidence of AI affecting entrepreneurship, either for likely employers or nonemployers.”
Is AI driving a boom in new employer businesses?
Core argument: Business applications likely to become employer businesses were flat in 2025 and began rising in 2026, with fewer applications of the kind having the highest chance of becoming an employer business.
Employer entrepreneurship is at best rising modestly, and at worst has been falling for several years already. The number of business applications likely to become an employer business was flat in 2025 and began rising in 2026. Fewer of those applications have been the kind that have the highest chance of becoming an employer. Nonemployer entrepreneurship, or “solopreneurship,” is likely rising, but not as the main job of the solopreneurs. These are probably side hustles. Likely nonemployer business applications rose significantly in 2025 and early 2026. But the share of workers claiming to be self-employed nonemployers in their main job — in other words, business owners with no employees — is flat (though noisy). AI-intensive sectors and industries are no exception. Establishment entry in AI-intensive sectors (information and professional services) has been flat or falling in recent years.
Takeaways by Macro Roundup® AI
Business applications likely to become employer businesses were flat in 2025 and began rising in 2026, with fewer applications of the kind having the highest chance of becoming an employer business.
Likely nonemployer business applications rose significantly in 2025 and early 2026, going vertical in the most AI-intensive sectors of information and professional services, while other sectors kept pace until early 2026 and then flattened.
The share of workers reporting self-employment as nonemployers in their main job is flat, though noisy, including among workers in AI-exposed occupations in 2025 and early 2026.
Related Articles:
The Age Of The Solopreneur— A surge in US business formation is being driven by solo entrepreneurs, with growth in AI tool usage and in solopreneur activity in high-AI-adoption sectors suggesting artificial intelligence accounts for a meaningful portion of the increase. The authors argue AI is lowering barriers to starting and growing a business by expanding what one-person firms can do.
America Has Become An Entrepreneur’s Paradise— US growth in new-business applications is concentrated in professional services (up 25% over four years), retail (18%), and health care and social assistance (18%) rather than artificial-intelligence startups. The share of applications the Census Bureau deems likely to hire at least one employee has fallen to 30% from 38%.
Which Entrepreneurs Boost Productivity?— The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
AI Summary.U.S. survey data on high school students show the share of 9th graders identifying as lesbian, gay, or bisexual fell from 17% to 11% over two years, compared with a decline from 18% to 16% among 12th graders. The drop was concentrated among girls, from 27% to 22%, versus 9% to 7% among boys.
Jean TwengeGeneration Tech
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Among US high-school students, the LGB share fell btw 2023 to 2025 by 5pp for girls (27% to 22%), and 2pp for boys (9% to 7%). The preceding rise was likewise larger for girls: +128% from 2015 to 2021, versus +99% for boys to 2023.
Are younger teens less likely to identify as lesbian, gay, or bisexual?
Core argument: The share of U.S. 9th graders identifying as lesbian, gay, or bisexual fell from 17% in 2023 to 11% in 2025 in the CDC’s Youth Risk Behavior Survey, while 12th graders declined from 18% to 16%.
[New data from the Youth Risk Survey of U.S. 9th to 12th graders from the CDC shows] for 12th graders, 17 and 18 years old, identifying as LGB declines only a few percentage points between 2023 and 2025 (from 18% to 16%). But the headline result is for 9th graders (14 and 15 years old): Identifying as LGB absolutely plummets between 2023 and 2025, from 17% to 11%. That really does look like a free fall. The decline appears to be driven almost entirely by girls. Identifying as LGB dropped from 27% in 2023 to 22% in 2025 among girls, and from 9% to 7% among boys. [In terms of the share of high school students reporting engaging in same-sex activity] most high school students are not sexually active, so this is only a subsample of the larger group. For boys, there’s been a fairly steady rise in same-sex partners, not too different from the pattern of identifying as LGB among boys. The story is different for girls, where having non-heterosexual sex peaked in 2021 and then fell steeply.
Takeaways by Macro Roundup® AI
The share of U.S. 9th graders identifying as lesbian, gay, or bisexual fell from 17% in 2023 to 11% in 2025 in the CDC’s Youth Risk Behavior Survey, while 12th graders declined from 18% to 16%.
The decline appears driven almost entirely by girls, whose LGB identification fell from 27% in 2023 to 22% in 2025, compared with a drop from 9% to 7% among boys.
Among sexually active teens, the share of boys reporting at least one same-sex partner has risen fairly steadily, while for girls it peaked in 2021 and then fell steeply.
Related Articles:
Is There Really a Generational Difference in Identifying as Lesbian, Gay, or Bisexual?— General Social Survey data show that increases among young American adults appear in same-sex sexual behavior as well as in identification, with 20% reporting a same-sex partner versus 18.5% identifying as lesbian, gay, or bisexual. The increases are larger among 27- to 41-year-olds.
Teens Used To Be Happier. What Changed?— The share of US high school seniors describing themselves as "very happy" peaked at 24.8% and remained around 24.4% before falling to 11.4% at its low, recovering only to 12.7%, well below the 17.9% recorded before the pandemic. The decline coincided with smartphones and social media becoming pervasive.
US College Students’ Well-Being— A study of US college students finds moderate-to-severe depression reported by 26% of students at one elite institution, 22% reporting moderate-to-severe anxiety and 10% contemplating suicide. Poorer mental health is associated with being female, little exercise, low grades, and financial aid; financial stress is associated with higher suicidal thoughts.
AI Summary.The Congressional Budget Office projects that if interest rates rose to 1 percentage point above its baseline, federal debt held by the public would reach 222% of GDP by 2056, 47 percentage points above baseline, with primary deficits averaging 2.3% of GDP and annual growth 0.1 percentage point slower.
CBO StaffCongressional Budget OffIce
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If interest rates rise 1pp above CBO’s current extended baseline (a mean rate of 4% over 2026–2056), CBO projects federal debt held by the public will be 222% of GDP in 2056, versus 175% under the current baseline.
How much would higher interest rates raise projected federal debt?
Core argument: CBO projects that under a scenario in which interest rates rise to 1 percentage point above its extended baseline, debt held by the public would reach 222% of GDP in fiscal year 2056, 47 percentage points above the extended baseline.
Under a scenario in which interest rates increased until they were 1 percentage point higher than in CBO’s extended baseline, primary deficits—that is, deficits excluding net outlays for interest—would average 2.3% of GDP over the 2026–2056 period, 0.2 percentage points larger than in the extended baseline. Debt held by the public would grow to 222 percent of GDP in fiscal year 2056, 47 percentage points larger than in the extended baseline. Average annual GDP growth over the 2026–2056 period would be 0.1 percentage point slower than in CBO’s extended baseline, and the average interest rate on federal debt would be 0.7 percentage points higher.
Takeaways by Macro Roundup® AI
CBO projects that under a scenario in which interest rates rise to 1 percentage point above its extended baseline, debt held by the public would reach 222% of GDP in fiscal year 2056, 47 percentage points above the extended baseline.
Primary deficits, which exclude net outlays for interest, would average 2.3% of GDP over 2026–2056 in CBO’s higher-interest-rate scenario, 0.2 percentage points larger than in its extended baseline.
Under CBO’s higher-interest-rate scenario, average annual GDP growth over 2026–2056 would be 0.1 percentage point slower and the average interest rate on federal debt 0.7 percentage points higher than in its extended baseline.
Related Articles:
The Budget and Economic Outlook: 2026 to 2036— The Congressional Budget Office projects the federal deficit will grow from $1.9tn (5.8% of GDP) to $3.1tn (6.7%) over a decade, above the 3.8% averaged over the past 50 years, with rising net interest costs driving much of the increase. Federal debt held by the public is projected to rise from 101% to 120% of GDP.
How Might Fiscal Policy Respond to the Rise of Artificial Intelligence?— The Congressional Budget Office estimates that a permanent 0.5 percentage point increase in annual productivity growth would lower publicly held federal debt after 30 years by 39% of GDP, offsetting roughly half the projected rise from 101% of GDP to 175%. Higher revenue and slower spending growth outweigh higher interest costs.
Soaring Bond Yields, Gaping Deficits and Towering Debts: What Could Go Wrong?— An analysis of 22 rich countries estimates that if each refinanced its entire debt at current five-year bond yields, Britain would need the largest primary surplus to stabilize its debt-to-GDP ratio, about 1.5%, followed by Italy at 1.4%, France at 1.2% and America at 1%.
AI Summary.Wall Street analysts covering technology project the sector's operating cash flow will more than double to roughly $2.4tn by 2028, a gain of over $1.2tn, while analysts covering the rest of the S&P 500 — technology's customers — project those firms will add far less cash flow. These sector-by-sector forecasts are internally inconsistent.
Torsten SløkApollo
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Tech analysts expect sector operating cash flow to more than double to ~$2.4T by 2028. Analysts covering other S&P 500 sectors (tech’s customers) see far less cash growth in their sectors. Slok “raises the question of who exactly will be writing all those checks to buy AI services.”
Are tech cash flow forecasts inconsistent with customers' projected growth?
Core argument: Analysts covering the tech sector expect its operating cash flow to more than double to roughly $2.4tn by 2028, an increase of over $1.2tn.
Wall Street equity analysts work in sector silos, and when you add up their forecasts, the numbers are internally inconsistent. The analysts covering tech expect the sector's operating cash flow to more than double to roughly $2.4 trillion by 2028, an increase of over $1.2 trillion. Meanwhile, the analysts covering the other sectors in the S&P 500, which are tech's customers, expect those companies to add much less operating cash flow. In other words, the tech silo is betting on a future in which demand for AI and tech services explodes, while the silos covering the companies that would pay for those services see a much more modest outlook. Both cannot be right at the same time. The bottom line is that either tech's customers will generate a lot more cash than their analysts expect, or tech's cash flow forecasts are too optimistic, which raises the question of who exactly will be writing all those checks to buy AI services.
Takeaways by Macro Roundup® AI
Analysts covering the tech sector expect its operating cash flow to more than double to roughly $2.4tn by 2028, an increase of over $1.2tn.
Analysts covering the other S&P 500 sectors, which are tech's customers, expect those companies to add much less operating cash flow, leaving the combined forecasts internally inconsistent.
Either tech's customers will generate much more cash than their analysts expect, or tech's cash flow forecasts are too optimistic, which raises the question of who will pay for AI services.
Related Articles:
A Catalyst For The AI Bubble Break— Historically, controlling for valuations, a 1% rise in the share of the market represented by initial public offerings has been associated with roughly a 4% decline in prices. With large artificial-intelligence company listings expected and share issuance exceeding buybacks, equity supply could shift from shrinking about 1% a year to growing near 5%, implying returns roughly 20% below average.
Financing the AI Buildout— The authors estimate roughly 57 gigawatts of operating US data center capacity against a planned development pipeline of about 509 gigawatts, which is not a completion forecast since projects may be delayed, scaled back, or abandoned. Their central scenario has 182.8 gigawatts of added capacity becoming operational through 2032, 117.2 gigawatts completed later, and 226.9 gigawatts never completed.
Rear Window— Major cloud providers posted annual revenue growth of 37% at Amazon Web Services, 43% at Microsoft Azure and 82% at Google Cloud, with rising revenue backlogs of $514bn and $496bn respectively at Google Cloud and Amazon Web Services. Earnings growth appears highly contingent on continued hyperscaler capital spending and research, which rose from $460bn to $870bn.
