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US AI spending needs 9% of GDP by 2032 to justify capital boom

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For the ongoing wave of artificial intelligence investment in the US to yield a financial return, businesses and consumers would need to spend approximately 9% of national income on the technology, according to calculations.

This proportion is equivalent to the entire budget the American public allocates to food, double all energy expenditures, or roughly seven times the total amount paid for telephone, internet, and digital streaming services.

A study prepared by Columbia University finance professor Stijn Van Nieuwerburgh and presented at the Brookings Institution, reported by The Wall Street Journal (WSJ), revealed that artificial intelligence infrastructure construction has become the largest investment drive in US history.

Based on current data centre construction plans, average costs, potential project cancellations, and an expected 10% unleveraged return on capital, calculations show that the sector must generate $3.5 trillion in revenue by 2032.

Under the assumption of 4% annual nominal growth, this figure corresponds to 8.8% of US gross domestic product (GDP).

Capacity expansion may lower prices

The foundation of current revenue projections rests on the assumption that artificial intelligence companies such as OpenAI and Anthropic will be able to sustain existing processing power prices into the future.

Stating that the current deficit in processing capacity is keeping profit margins high, Van Nieuwerburgh noted that companies will not be able to sustain today’s scarcity pricing in an intense competitive environment by 2032, when capacity is projected to quadruple.

Sharp price declines seen in past technology investments show that comparable crises have occurred before.

As a result of laying new lines and expanding capacity, bandwidth prices on transatlantic fibre-optic links between London and New York plunged by 96% between 1997 and 2001, a process that triggered the bankruptcy of numerous telecommunications companies.

Could falling prices boost demand?

While the processing capabilities of artificial intelligence models double every four to five months, data from Epoch AI show that the cost for a given capability level has been falling by 47% per quarter since 2023.

Optimists, drawing on the concept known in economic literature as Jevons’ Paradox, argue that expanding capacity and lower costs will multiply demand, thereby driving corporate revenues higher.

The $300 billion combined annual revenue estimate set for 2030 for OpenAI and Anthropic by an expert panel led by Ezra Karger of the Federal Reserve Bank of Chicago has already been surpassed.

The annualised combined revenue run rate of the two companies has reached approximately $180 billion and continues to post double-digit growth each quarter.

Against advocates who view the technology as a third factor of production alongside capital and labour, forecasts indicate that the growth rate will decelerate and the law of diminishing returns will take effect as the system becomes widespread.

Productivity gains do not translate directly into revenue

Following the price drops and productivity surge seen from 1966 onwards during the personal computer revolution, corporate computer expenditures flattened out at around 0.8% of GDP by approximately 1984.

A recent study conducted by Harvard University doctoral students Fiona Chen and James Stratton, examining software projects on the Jellyfish platform, pointed to a similar structural ceiling.

The researchers determined that artificial intelligence assistants increased the number of lines of code written by 12%, while autonomous software agents increased it by 30%.

Conversely, because users spent more time reviewing, interpreting, and modifying code, the ultimate contribution to completed projects remained low and was found to be “statistically insignificant”.

Experts emphasise that even if artificial intelligence boosts productivity, this outcome may not translate directly into the massive profit and revenue figures anticipated by investors.

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Unauthorised AI agents access customer accounts at major US banks

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Incidents have been detected at the largest US banks in which unauthorised artificial intelligence agents gained access to customer accounts.

According to a report by Axios based on sources, some of these AI agents attempted to take actions that were not included in user instructions.

Institutions facing risks arising from such agents include leading lenders such as Morgan Stanley, Bank of America, JPMorgan, Wells Fargo, and Citi.

In some cases, AI software entered customer accounts using usernames and passwords directly with user consent.

In contrast, security rules at most banks require users to log in to their accounts personally.

According to Axios, in other instances, AI agents designed to carry out tasks on behalf of customers contacted bank call centres directly or tried to take independent steps without receiving any instruction from the user.

Bank executives worry that such software with access to credentials could make unauthorized purchases or transfer funds.

Following these risks, banks are moving to restrict third-party AI agents from accessing their platforms. While Morgan Stanley has begun blocking such software, JPMorgan, Bank of America, and Citi are also introducing similar restrictions.

Banks are also considering offering a financial access model that gives AI agents read-only permissions while completely cutting off transaction capabilities.

Sources speaking to Axios point out that it is extremely difficult for banks to determine whether an agent is acting on user instructions or accessing the account entirely on its own initiative.

Regulators hold emergency meeting with systemically risky banks

According to reports by Bloomberg and the Financial Times citing sources, US Treasury Secretary Scott Bessent and Federal Reserve Chair Jerome Powell held an extraordinary meeting in April with top executives of the country’s largest banks over concerns about cyber threats that could be posed by a new AI model developed by Anthropic.

Sources providing details on the talks stated that US officials wanted to gauge bank awareness regarding risks tied to the Claude Mythos model and inspect the measures they have taken to protect their systems.

Senior executives from Citigroup Inc., Bank of America Corp., Wells Fargo & Co., Goldman Sachs Group Inc., and Morgan Stanley attended the meeting.

Organised at short notice, the summit indicated that regulatory authorities view this new breed of cyber attack as one of the greatest threats to the financial sector.

All of the banks represented at the table are classified as systemically important institutions within the global financial architecture.

Axios reported that leading AI firms, including Anthropic and OpenAI, harbour concerns that an AI-driven “catastrophic event” could take place over the next 6 to 12 months.

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US wealthy demolish multimillion-dollar mansions for land

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Wealthy buyers in the US are tearing down multimillion-dollar homes shortly after purchasing them for hundreds of millions of dollars.

According to a report by The Wall Street Journal, the trend is driven by a shortage of land in prestigious locations, particularly along coastlines.

For ultra-wealthy buyers, the prime factor has become the land’s location rather than the structure standing on it. After the acquired properties are flattened, newer, more modern homes are built on the cleared lots.

Drawing attention to the shift in the luxury real estate market, the report noted:

“The home itself, formerly the primary driver of an expensive real estate purchase, is now almost beside the point. Buyers are competing first and foremost for well-located land, situated on the ocean or a mountaintop.”

The newspaper cited moves by US billionaire William Lauder as an example. Lauder purchased the oceanfront estate of radio host Rush Limbaugh, who died in March 2023, for $155 million and had it completely demolished in July.

Lauder had previously torn down two homes situated on roughly 1.2 hectares of land along the Palm Beach coast. Having initially planned to construct his own residence on the parcel, Lauder subsequently sold the cleared plot for approximately $200 million.

Jonathan Miller, a real estate appraiser, stated that such transactions are becoming increasingly common as land prices rise.

Amid this momentum, estate agents have also begun marketing luxury homes directly as teardown lots.

Listings use artificial intelligence-generated imagery to showcase how the land would look without the structures on it.

Marketers avoid using the word “demolition” directly, resorting instead to terms such as “adaptive reuse”.

Teardown listings rise across luxury housing market

The trend is not confined to the coast and is spreading to other regions across the US.

Data from property brokerage Redfin reveals that references to demolishing buildings are becoming more frequent in sales listings.

The share of such listings exceeds 15% in the Bunker Hill Village area of Houston, while standing at 6.67% in Pimmit Hills, Virginia.

Dina Goldenteyer, a real estate agent working in Miami, remarked that serial demolitions have become more frequent because buyers no longer appreciate homes older than a decade.

Former retail executives Jamie Dooley and Christine Scott spent $3.7 million in 2020 to demolish a seaside home near Destin, Florida.

Although the couple spent five years building a modern home on the cleared site, they listed the resulting new structure with a demolition condition, citing the fact that no one wanted to buy the property as it stood.

William Paddock, an employee at the environmental consultancy WAP Sustainability, pointed to the environmental damage caused by this construction cycle.

Paddock emphasized that tearing down a home of roughly 1,000 square metres and replacing it with a new building of approximately 2,700 square metres generates a carbon footprint equivalent to the annual emissions of an average 250 American households.

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US inflation reaches 3.7% as midterm election campaign intensifies

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An uptick in September inflation as the US midterm elections approach has pushed the cost-of-living debate back to the centre of the agenda for Democrats seeking to regain control of Congress from Republicans.

Annual inflation stood at 3.7% in September, according to the Consumer Price Index published by the Bureau of Labour Statistics, with energy, petrol, and electricity costs rising on a monthly basis.

Food prices remained flat from August to September, recording a 2.5% increase compared with the same period last year.

Democrats are anchoring their election campaigns to pledges of easing the cost of living, blaming the price increases on President Donald Trump’s tariffs and the war with Iran.

Trump and Republicans, pointing to the numerous left-wing candidates who won primary elections this year, contend that the opposition has become captive to “communists” within the party.

When annual inflation stood at 2.4% in February, the US and Israel launched the Iran war on the final day of that month, and prices continued to climb throughout the conflict.

The recent acceleration has not entirely reversed the retreat from the 40-year peak of 9.1% recorded in June 2022; however, the rate has remained above the Federal Reserve’s 2% target for over five years.

Fed policymakers raised the benchmark interest rate by a quarter of a percentage point last month, citing the battle against stubborn inflation. Officials will convene again next week to consider whether to raise rates or hold them within the 3.75% to 4% target range.

Energy and fuel record sharpest increase since first month of war

In September, energy prices posted their largest monthly jump since March, the first full month of the war with Iran, climbing 20.4% year-on-year. Energy costs had risen 2.1% from July to August, after falling 1.5% from June to July and 5.7% from May to June.

Recent escalations in Iranian attacks on oil tankers in the Strait of Hormuz, alongside more frequent strikes by Ukrainian forces against Russian refineries, have strained global crude oil and refined product markets, driving up US petrol and diesel prices.

Petrol prices also recorded their sharpest monthly increase since the first month of the war, climbing 9.1% from August to September, bringing the annual increase to 35.3%.

American Automobile Association (AAA) data shows the average price of regular petrol across the US stands at $4.26 per gallon; while below the level of roughly $4.48 recorded a month ago, it remains more than $1.20 higher than a year earlier. Average gallon prices exceed $6 in California and $5 in both Washington state and Nevada.

Electricity prices rose 0.2% from August to September, offsetting the 0.2% decline between July and August, and were up 4.4% year-on-year.

Heavy power demand from new data centres is feeding through into local household electricity bills. Trump argued that companies must cover the cost of the electricity required by their data centres themselves.

In a post on Truth Social, Trump claimed that he was requiring large data centres to generate their own power and feed the surplus back into the local grid, suggesting this could bring about “a major drop” in electricity prices.

Used vehicle market posts monthly rise as food costs stabilise

The cost of food at home fell 0.1% month-on-month in September, while dining out increased 0.2%.

Egg prices dropped to $2.27 a dozen, falling roughly 35% compared with September 2025 and remaining well below the 20-year peak of $6.23 recorded in March 2025.

Ground beef prices rose roughly 2.4% compared with September 2025, but at $6.48 a pound, they remained below the 20-year high of $6.98 reached in June.

Chicken held steady at its year-earlier level of $2.06 per pound last month, having fluctuated between $2.01 and $2.09 since November 2024.

Used car and truck prices fell 1.5% compared with September 2025, but rose 0.7% month-on-month in September following 0.4% increases in both July and August.

Heather Long, chief economist at Navy Federal Credit Union, noted that the sector faces severe pressure stemming from a combination of expensive replacement parts and a shortage of skilled labour.

Speaking to The Hill, Long emphasised that every cost pressure across the market is being felt directly at local auto repair shops.

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