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Anthropic study finds AI adoption remains well below its technical potential in the workforce

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Anthropic has published a research report introducing a new framework for measuring how artificial intelligence is affecting the workforce.

While earlier studies focused on what large language models could potentially do, the report reveals that real-world AI adoption rates remain substantially below the technology’s total technical potential.

The authors note the prediction that occupations with high AI exposure, such as computer programming and customer service, will see slower employment growth over the coming decade.

Despite those projections, the data compiled in the report shows no systematic increase in aggregate unemployment linked to AI exposure since late 2022.

The occupation currently most exposed to AI is computer programming, with an “observed exposure” rate of 74.5%, as the writing, updating and maintenance of software programs undergoes extensive automation.

Customer service representatives follow closely, with an exposure rate of 70.1%. Their core tasks, such as engaging with customers and handling complaints, are becoming increasingly automated.

The remaining top ten occupations with the highest AI exposure are:

Data entry operators (67.1%): at high risk due to significant automation of core tasks such as reading source documents and entering data into systems.

Medical records specialists (66.7%): at risk due to the automation of compiling, summarising and coding patient data.

Market research analysts and marketing specialists (64.8%): at risk in tasks involving report preparation, data visualisation and the conversion of complex findings into written text.

Sales representatives (wholesale and manufacturing, excluding technical and scientific products) (62.8%): at high risk in tasks involving contacting customers to promote products and take orders.

Financial and investment analysts (57.2%): tasks involving the analysis of financial information to forecast business, industry or economic conditions in order to guide investments.

Software quality assurance analysts and testers (51.9%): at risk due to tasks involving modifying software to correct errors or improve performance.

Information security analysts (48.6%): exposed to AI automation in tasks related to conducting risk assessments and testing data processing security.

Computer user support specialists (46.8%): focused on answering user questions concerning computer software or hardware.

By contrast, approximately 30% of workers currently fall outside the scope of AI, either because their tasks are highly physical or because they do not appear with sufficient frequency in AI usage data to meet the minimum threshold.

Occupations with zero AI exposure include cooks, electricians, nurses, motorcycle mechanics, lifeguards, bartenders, dishwashers and dressing room attendants.

Workers with high AI exposure tend to be slightly older.

Data comparing workers with zero AI exposure to those in the top quartile of exposure shows that the most heavily exposed group has an average age of 42.9, compared with an average age of 41.0 for the unexposed group.

Women are significantly more likely to be in occupations with high AI exposure. Women account for 54.4% of the most highly exposed group, but only 38.8% of the unexposed group.

AI exposure correlates strongly with higher levels of education. The most AI-exposed workers are far more likely to have advanced educational attainment.

By contrast, those with less formal education are overwhelmingly concentrated in unexposed roles.

Individuals with a master’s degree comprise 17.4% of the high-exposure group, but only 4.5% of the unexposed group.

Individuals with a bachelor’s degree account for 37.1% of the most exposed workers, but only 13.3% of unexposed workers.

Workers whose highest level of education is a high school diploma or less are far more prevalent in the unexposed group (52.1% in total) than in the top quartile of exposure (20% in total).

Workers in the top quartile of AI exposure earn an average of $32.69 per hour.

That figure is 47% higher than the average hourly wage of $22.23 for workers with zero AI exposure.

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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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Anthropic posts $80.7bn loss ahead of IPO as computing costs soar

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Anthropic, developer of the artificial intelligence model Claude, reported a net loss of $80.7 billion for the first six months of 2026 ending 30 June.

According to a report by The Wall Street Journal citing the company’s draft initial public offering prospectus, this recorded loss nearly doubled the $42 billion loss incurred across the entirety of 2025.

The vast majority of that enormous figure, accounting for $72 billion, stemmed from accounting-driven book-value write-downs.

In contrast, the company saw a sharp surge in revenue, with turnover in the first half of the year climbing to $16.3 billion from $1.1 billion in the same period of the prior year.

During this period, Anthropic spent approximately $9 billion on computing power and infrastructure needs, surpassing in just six months the $7.3 billion spent across the whole of 2025.

The company has commitments to pay roughly $450 billion over the next seven to 10 years under cloud service contracts.

Under these obligations, contracts are planned for $111 billion with Google Cloud, $110 billion with Amazon Web Services, and $31 billion with Microsoft.

Anthropic will also spend up to $86 billion by 2033 and 2034, respectively, to lease Nvidia chips through smaller AI-focused cloud providers Nscale and Lambda.

The company could spend an additional $750 billion in the coming years to expand its computing capacity.

Roughly a third of the draft IPO prospectus was dedicated directly to risk factors.

The document highlighted the possibility that models could cause tangible real-world harm, noting that artificial intelligence could exhibit a “self-preservation” tendency and produce responses resembling “blackmail”.

Anthropic warned that the scale of damage caused by an AI-driven “catastrophic event” could render insuring against such risks impossible.

According to market expectations, Anthropic’s IPO could rank among the largest transactions in history, potentially surpassing SpaceX’s record.

Following the market debut, the company’s market valuation is projected to reach up to $2 trillion.

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