Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
Upside of Inequality Oxford Unintended Consequences

AI Summary. Corporate profit margins, long regarded as one of the economy's most reliably mean-reverting series, have risen continuously so far this century. Measured through the national income accounts used in calculating GDP, profits now take a larger share of the economy than on the eve of the 1929 crash.

John Authers Bloomberg
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Since 2000, post-tax corporate profits as a share of GDP have trended upward across cyclical setbacks and are now near an all time high, above their 1929 level.

Have corporate profit margins stopped reverting to the mean?

Core argument: Corporate profits measured in the National Income and Product Accounts take a larger share of the U.S. economy than on the eve of the 1929 Great Crash.

Throughout the 20th century, profit margins were regarded as one of the purest mean-reverting series in the economy. So far this century, however, margins have done nothing but rise. Measured with the National Income and Product Accounts, part of the GDP calculation, profits are currently taking a bigger share of the economy even than on the eve of the Great Crash in 1929. The series comes with a lag, so we can assume the profit share on this basis is comfortably at a record by now.

Takeaways by Macro Roundup® AI

  1. Corporate profits measured in the National Income and Product Accounts take a larger share of the U.S. economy than on the eve of the 1929 Great Crash.
  2. Profit margins were regarded throughout the 20th century as one of the purest mean-reverting series in the economy, yet so far this century they have done nothing but rise.
  3. The National Income and Product Accounts profits series comes with a lag, so the profit share on this basis can be assumed to be comfortably at a record.

Related Articles:

  • US Focus: The Effect Of Soaring Profits — US nominal pre-tax corporate profits in the national accounts grew 23% over the past year, a pace not seen outside post-recession spikes since the mid-2000s. Wider margins were the key driver, as domestic profit growth far exceeded the 8% rise in corporate value added, pushing margins near all-time highs while the labor share hit new lows.
  • The Post‑COVID Decline in the Labor Share — The share of US national income paid to workers fell 1.6 percentage points below its pre-pandemic level, reaching a post-war low. The authors find this decline stems mainly from changes within industries rather than shifts in activity across sectors, following cyclical patterns seen in earlier recessions.
  • Are US Corporate Profit Margins Too High? — US after-tax non-financial corporate profit margins remain elevated by historical standards, estimated at 7.6% versus a post-1949 high of 8.2%, while employee pay as a share of non-financial corporate gross value added has fallen from 66% to 56%. One argument holds that subdued demographic growth leads companies to prioritize maximizing margins over expanding capacity.

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 Azhar Exponential 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

  1. 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.
  2. 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. 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 Authers Bloomberg
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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

  1. 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.
  2. 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.
  3. 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 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 Staff Congressional 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

  1. 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.
  2. 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.
  3. 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 Sløk Apollo
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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

  1. 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.
  2. 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.
  3. 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.

AI Summary. Foreign investors made a record $942bn in net purchases of US stocks and investment fund shares over 12 months, the highest rolling 12-month total in Treasury data going back to 1985. Foreign demand for US debt securities moved in the opposite direction, falling to a net $188bn in the second quarter from $314bn in the first.

Michael Taffe and George Steer Financial Times
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Foreign investors bought a record net $426B of US equities and fund shares in Q2, up 62% y/y, part of a record $942B in the 12 months through July. Overseas investors bought a net $188B of US debt securities in Q2, down from $314B in Q1.

Are foreign investors shifting from US debt into US stocks?

Core argument: Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, the highest rolling 12-month total in Treasury data going back to 1985.

Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, accelerating a shift in overseas investment towards American stocks and away from debt. The flows represented the highest rolling 12-month total in Treasury data going back to 1985. Net purchases of US equities and investment fund shares by foreign investors jumped to $426bn in the second quarter, up 62% from the same period in 2025, and surpassing the previous quarterly record of $299bn in 2022, according to the Bureau of Economic Analysis. Foreign demand for US debt moved in the opposite direction. Overseas investors bought a net $188bn of US debt securities in the second quarter, down from $314bn in the first.

Takeaways by Macro Roundup® AI

  1. Foreign investors made a record $942bn in net purchases of US equities and investment fund shares in the 12 months to July, the highest rolling 12-month total in Treasury data going back to 1985.
  2. Net foreign purchases of US equities and investment fund shares reached $426bn in the second quarter, up 62% from the same period in 2025 and above the prior quarterly record of $299bn in 2022, according to the Bureau of Economic Analysis.
  3. Overseas investors bought a net $188bn of US debt securities in the second quarter, down from $314bn in the first.

Related Articles:

  • World’s Unusually High Dollar Exposure Risks Fueling Selloff — Pension funds and insurers in Canada, Denmark, Australia, Taiwan, Japan and Finland hedged just 41% of their foreign-currency exposure, the lowest share since at least 2015. With some of the largest holders of US assets carrying little protection against a weaker dollar, the currency is at risk of steeper declines if sentiment turns.
  • Foreign Investors Prefer US Stocks To Treasuries As Debt Worries Grow — International flows into US stocks averaged 2.8% of US GDP over a year, overtaking flows into US Treasuries at 2% of GDP for the first time this century outside brief episodes during the Covid-19 pandemic and after the global financial crisis, according to Deutsche Bank analysis of US Treasury data.
  • 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.

AI Summary. An analysis estimates that for US data center owners to break even on AI investments, the sector would need about $3.725tn in annual compute revenue by 2032 — roughly 9.2% of projected 2032 GDP. The estimate assumes 183 GW of US capacity completed, a $9.61tn capital base, a 10% discount rate, and a 50% operating cash flow margin.

Hanno Lustig The Two Cents
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The US AI-buildout is projected to average ~3.6% of GDP over 2025–32. Lustig notes data-center operators will need ~$3.725T in annual compute revenue by 2032, 9.2% of projected GDP, to earn a 10% unlevered return on the buildout.

How much annual revenue must AI data centers generate to break even?

Core argument: Stijn’s baseline estimate holds that data center owners would need $3.725 trillion of annual revenue by 2032 — roughly 9.2% of projected 2032 GDP — to break even on AI investment at a 10% discount rate.

What do you have to believe about future revenue in order for all data center owners to to break even on their AI investment? Using a 10% discount rate, Stijn’s baseline number is 3.725 trillion of annual revenue by 2032, which would amount to roughly 9.2% of projected 2032 GDP. This number is the top line earned from selling compute in aggregate by whoever operates the 182.7 GW of US capacity completed by 2032.2. The assumptions behind that number: 183 GW of U.S. data-center capacity completed between 2025 and 2032. $8.54 trillion of construction cost, grossed up to a $9.61 trillion capital base to account for the return on capital tied up during construction. A 10% discount rate. A 6-year life for IT equipment (68% of cost) and a 20-year life for everything else (32%). A 50% operating cash flow margin.

Takeaways by Macro Roundup® AI

  1. Stijn’s baseline estimate holds that data center owners would need $3.725 trillion of annual revenue by 2032 — roughly 9.2% of projected 2032 GDP — to break even on AI investment at a 10% discount rate.
  2. The break-even calculation assumes 183 GW of U.S. data-center capacity completed between 2025 and 2032 at $8.54 trillion of construction cost, grossed up to a $9.61 trillion capital base for return on capital tied up during construction.
  3. The estimate assumes a 6-year life for IT equipment, which accounts for 68% of cost, a 20-year life for the remaining 32%, and a 50% operating cash flow margin.

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.
  • 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.
  • 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. 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.

Stijn Van Nieuwerburgh Brookings Papers on Economic Activity
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Stijn Van Nieuwerburgh projects ~$10.3T will be spent on the AI buildout over 2025–2032, averaging 3.63% of GDP. He estimates 2/3 of that spending reflects IT equipment and one-third real estate and associated power infrastructure.

How much of the planned data center pipeline gets built?

Core argument: Using Cleanview project-level data from July 2026, the authors estimate roughly 57 GW of operating U.S. data center capacity against a planned development pipeline of roughly 509 GW, which they stress is not a completion forecast.

The required investment is enormous. A representative 200 MW AI training campus costs roughly $8.2 billion, about two-thirds of which reflects IT equipment and one-third the real estate and associated power infrastructure. We estimate that 183 GW is completed by 2032 with a further 118 GW completed after 2032. This pipeline will trigger about $10.3 trillion dollars of investment over 2025–2032. At an average of 3.63% of GDP per year, the projected buildout would be larger relative to the economy than the major U.S. canal, railroad, electrification, highway, and telecommunications investment booms. It would double the electricity consumption of the entire U.S. residential sector.

Takeaways by Macro Roundup® AI

  1. Using Cleanview project-level data from July 2026, the authors estimate roughly 57 GW of operating U.S. data center capacity against a planned development pipeline of roughly 509 GW, which they stress is not a completion forecast.
  2. The authors’ central scenario allocates the announced pipeline so that 182.8 GW of additional U.S. capacity becomes operational during 2025–32, including 19.0 GW tied to projects already operational in 2025 or 2026.
  3. The authors’ scenario has 117.2 GW of planned data center capacity completed after 2032 and 226.9 GW never completed, applying lower realization rates to more distant and less fully documented projects.

Related Articles:

  • 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 Set to be Largest CapEx Cycle Ever … and Soon Majority Externally Financed — Hyperscaler and data-center investment is tracking toward $1.5tn annually by 2030, which in real terms would exceed the 2005-06 housing boom, the 1990s fiber peak, and the 1882 railroad peak combined. External debt and equity are projected to fund close to 90% of the buildout, making it dependent on credit markets.
  • The Summer I Turned Pretty — A warning sign in a boom cycle is when companies closest to final demand weaken while capital spending beneficiaries keep thriving, as when telecom operators' shares rolled over while communications equipment stocks kept rising. Semiconductor stock prices and free cash flow are soaring while large cloud providers' shares stagnate and their free cash flow plummets.