It’s becoming clearer that we are in a perilous financial situation globally. Fears over an “AI bubble” are being cited by the Bank of England, the International Monetary Fund and the boss of JP Morgan, Jamie Dimon.
If you want a sense of how insane the narrative is around AI investments, consider this: Thinking Machines Lab, an AI startup, recently raised $2bn funding on a valuation of $10bn.
The company has zero products, zero customers and zero revenues. The only thing it made public to its investors was the resume of its founder, Mira Murati, formerly chief technology officer at OpenAI. If that’s not hubris meeting market exuberance, what is?
But narrative is crucial here because it’s what’s driving all this insane investment in the future of AI or so-called artificial general intelligence (AGI), and it’s important to examine which narrative you believe in if you are to protect yourself for what’s to come.
If I were to pick between the views of a politician such as UK prime minister Keir Starmer, and a writer such as Cory Doctorow, I’d put my bet on Doctorow. Contrast these two statements and see which you feel more comfortable with…
Doctorow suggests the AI bubble needs to be punctured as soon as possible to “halt this before it progresses any further and to head off the accumulation of social and economic debt”.
He suggests doing that by taking aim at the basis for the AI bubble – namely, “creating a growth story by claiming that AI can do your job”.
AI is the asbestos we are shovelling into the walls of our society and our descendants will be digging it out for generations Cory Doctorow
Claims about jobs disappearing to AI have been around since 2019 with Sam Altman, then leader of venture capital (VC) fund Y Combinator, speaking about radiology jobs disappearing in the future: “Human radiologists are already much worse than computer radiologists. If I had to pick a human or an AI to read my scan, I’d pick the AI.”
Fast forward six years to 2025 and look how that worked out. According to a recent report by Works in Progress, despite the fact that radiology combines digital images, clear benchmarks and repeatable tasks, demand for human radiologists is at an all-time high.
The report authors’ conclusions drive a horse and cart through the current AI/AGI narrative that if left unstopped will cause severe global economic pain: “In many jobs, tasks are diverse, stakes are high, and demand is elastic. When this is the case, we should expect software to initially lead to more human work, not less. The lesson from a decade of radiology models is neither optimism about increased output nor dread about replacement. Models can lift productivity, but their implementation depends on behaviour, institutions and incentives. For now, the paradox has held – the better the machines, the busier radiologists have become.”
Across other sectors too, the mythology around job losses is slowly being interrogated – for example, Yale University Budget Lab found no discernible disruption to labour markets since ChatGPT’s release 33 months ago.
The research goes on to state: “While this finding may contradict the most alarming headlines, it is not surprising given past precedents. Historically, widespread technological disruption in workplaces tends to occur over decades, rather than months or years. Computers didn’t become commonplace in offices until nearly a decade after their release to the public, and it took even longer for them to transform office workflows. Even if new AI technologies will go on to impact the labour market as much, or more dramatically, it is reasonable to expect that widespread effects will take longer than 33 months to materialise”.
Normal technology
In other words, AI is just, well, technology as we have always known it – or as experts Aryind Narayanan and Sayash Kapoor call AI, just “normal technology”.
Importantly in their paper, AI as normal technology – An alternative to the vision of AI as a potential superintelligence, they identify key lessons from past technological revolutions – the slow and uncertain nature of technology adoption and diffusion; continuity between the past and future trajectory of AI in terms of social impact; and the role of institutions in shaping this trajectory. They also “strongly disagree with the characterisation of generative AI adoption as rapid, which reinforces our assumption about the similarity of AI diffusion to past technologies”
A good example of AI as normal technology without all the hype, hyperbole and billion-dollar burn rate, is the City of Austin, Texas. Here, an on-premise AI system helped the local government process building permits in days instead of months.
According to David Stout, CEO of WebAI, this was done “with no spectacle. No headlines. Just efficiency gains that will outlast the market cycle. He said, “That’s the point too often missed in the frenzy. Mega-models attract headlines, consume billions in capital, and struggle to demonstrate sustainable economics. Meanwhile, smaller, domain-specific systems are already delivering efficiency gains, cost savings and productivity improvements. The smart play isn’t to abandon AI, but to pivot towards models and deployments that will endure”.
Technology like we have always known it to be – not the insane fantasy of “superintelligence” that is powering this dangerous bubble.
The question to ask is, given the prediction of at least a 33-month lag before any return on investment, however small, will the markets wait another 33 months for their returns to materialise?
Protracted crisis
A recent report on MarketWatch suggests the AI bubble is now ”seventeen times the size of the dot com frenzy and four times the sub-prime bubble”. MarketWatch quotes financial analyst Julien Garran, who previously led UBS’s commodities strategy team, who said “AI now accounts for over four times the wealth trapped in the 2008 sub-prime mortgage bubble, which resulted in years of protracted crisis across the globe”.
Warnings from the Bank of England in its semi-annual Financial Policy Committee report are equally stark: “Uncertainty around the global risk environment increases the risk that markets have not fully priced in possible adverse outcomes, and a sudden correction could occur should any of these risks crystallize.”
The bank also warned of “the risk of a sharp market for global financial markets amid AI bubble risks and political pressure on the Federal Reserve.”
What a sudden correction means is that a collapse of the AI investment bubble will take trillions of investment with it, impacting us all.
Even more worrying is the issue of debt financing among those competing in the AI race – that is, all the tech bros. It now appears, according to Axios, that these companies are turning to private debt markets and special purpose vehicles for cash, which means this kind of borrowing does not have to show on their balance sheets.
Meta, for example, recently sought $29bn from private capital firms for its AI datacentres. This off-book debt financing should ring more alarm bells that something is terribly wrong with the AI growth narrative.
After all, as pointed out by the Axios analysts, “If hugely profitable tech companies need to mask their borrowings to fund AI spending, it signals they’re not confident that they’ll soon get the returns needed to justify such investments. That suggests the very spending powering today’s earnings boom can’t last forever.”
Unit economics
To go back to Cory Doctorow’s argument, we are not in the early days of the web, or Amazon, or other dot com companies that lost money before becoming profitable: “Those were all propositions with excellent unit economics. They got cheaper with every successive technological generation and the more customers they added, the more profitable they became”.
AI companies do not have excellent unit economics – in fact they have the opposite, according to Doctorow: “Each generation of AI has been vastly more expensive than the previous one, and each new AI customer makes the AI companies lose more money”.
[Only] about 5% of tasks will be able to be profitably performed by AI within 10 years Daron Acemoglu
And if that’s not sobering enough for the VC and private equity firms, then the circular investing going on between these tech firms should be a huge concern.
Microsoft is investing $10bn in OpenAI by giving free access to its servers. OpenAI reports this as an “investment,” then redeems these tokens at Microsoft datacentres, which Microsoft books as $10bn in revenue.
Bain & Co says the only way to make today’s AI investments profitable “is for the sector to bring in $2tn by 2030,” which, according to the Wall Street Journal, is more than the revenue of Amazon, Google, Microsoft, Apple, Nvidia and Meta – combined.
Taking a closer look at US economic growth is surely more cause for concern.
According to Harvard economist Jason Furman’s analysis, GDP growth in the first half of 2025 was driven almost entirely by investment in information processing equipment and software. This spending was largely tied to the rapid expansion of AI infrastructure and datacentres.
While these tech sectors only made up 4% of total GDP, they contributed a staggering 92% of growth. Absent this investment, Furman estimates US GDP growth would have hovered around 0.1% on an annualised basis – barely above zero.
There is a lot riding on a technology that’s supposed to be godlike and all powerful but which, according to MIT Institute professor Daron Acemoglu, is far less likely to achieve the insane hyperbolic claims being made by the tech bros in an effort to win an unwinnable race.
Acemoglu estimates the 10-year effect of AI in the US will be that only “about 5% of tasks will be able to be profitably performed by AI within that timeframe,” with the GDP boost likely to be closer to 1% over that timespan. If that’s not a recipe for stock market collapse, what is?
Emperor’s new clothes
Going back to the AI booster narrative and how it’s driving things, Doctorow is again incisive: “The most important thing about AI isn’t its technical capabilities or limitations. The most important thing is the investor story and the ensuing mania that has teed up an economic catastrophe that will harm hundreds of millions or even billions of people. AI isn’t going to wake up, become super intelligent and turn you into paperclips – but rich people with AI investor psychosis are almost certainly going to make you much, much poorer”.
I’m not an economist, so I did what we are all supposed to do now for our enlightenment. I gave the machines built by the tech bros all the same prompt: “What fable best encapsulates the current AI bubble?”
Gemini, Perplexity and ChatGPT were all in agreement with nearly the same explanation of why they all picked the same story: “The emperor’s new clothes remains the best classic fable to explain the AI bubble, as it encapsulates the collective willingness to believe in – and profit from – an imagined reality, until facts and external shocks eventually break the spell.”
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Pete Hegseth, the secretary of the Department of Defense, said in a recent press conference that the operation could last as long as eight weeks. President Donald Trump himself said in a press conference on March 2 that the administration projected the operation would last four or five weeks but had “the capability to go far longer than that.”
This week Iran has responded in turn, attacking Israel, regional US embassies and military bases, and other sites across the Middle East. Iran has peppered neighboring countries with hundreds of drone and ballistic missile strikes since the operation began. While many of these have been intercepted, over a thousand people have died in the region and multiple buildings have been damaged, including luxury hotels in Dubai, US military bases and embassies, and international airports and marine ports.
Israel has also started bombarding Lebanon, following strikes at the country by the Lebanese militant group Hezbollah.
The Trump administration has given various, and at times seemingly contradictory, justifications for the military action, citing everything from potential “nuclear threat” to unverified claims that Iran attempted to interfere in the 2020 and 2024 US presidential elections. As of March 5, Congress, which in the US has the sole power to declare war, has not done so.
The attacks have already disrupted supply chains, creating uncertainty for the oil and gas and fertilizer industries as key infrastructure has been targeted or shut down out of caution. Shipping traffic has halted along the Strait of Hormuz, a critical route.
As the conflict continues to escalate and expand, WIRED is tracking which countries have been affected and how. This article was last updated on March 5.
Iran
As of March 4, Iranian state media estimates that over 1,000 people have died in the country since the US-Israeli attacks began. Several schools and hospitals have been hit, according to Al Jazeera. The Israeli Air Force says it has struck Iran with over 5,000 munitions since the beginning of the operation.
Israel
Israel has faced retaliatory strikes from Iran. As of March 4, at least 11 people have died and over 40 buildings have been damaged in Tel Aviv, according to Al Jazeera.
Azerbaijan
On March 5, Azerbaijan said drone attacks launched from Iran had crossed over the country’s borders and damaged an airport building and two civilians. President Ilham Aliyev of Azerbaijan said that the country’s military forces “have been instructed to prepare and implement appropriate retaliatory measures,” according to Reuters. Iran has denied responsibility for the attacks, according to Al Jazeera.
Bahrain
Missile and drone strikes have targeted different locations in Bahrain, including a US naval base, according to the BBC. On March 2, Amazon reported that a drone strike occurred in close proximity to one of its data centers in the country. CNBC later reported that Iranian state media said that Iran had targeted the data center because of the company’s support of the US military.
Cyprus
On March 2, a drone strike hit a British air base in Cyprus, according to Reuters. It caused limited damage and no casualties. Greece, the UK, and France have lent defensive support to the country, according to a Bloomberg report.
Iraq
Since February 28, there have been reports of multiple Iranian strikes aimed at a US military base near the Erbil International Airport, according to the nonprofit monitoring group Armed Conflict Location and Event Data.
Jordan
Jordan’s armed forces have intercepted dozens of missiles since the start of the conflict. At least one Iranian-backed militant group in Iraq has claimed responsibility, according to the Associated Press. On March 2, the US Embassy in the country announced that all its personnel had temporarily departed.
Kuwait
Kuwait has endured multiple waves of Iranian missile and drone attacks since February 28. On March 2, US Central Command said in a statement that three US fighter jets were accidentally struck down by Kuwaiti air defenses during an attack that included Iranian aircraft, missiles, and drones.
Lebanon
Israel attacked southern Lebanon after the militant Lebanese group Hezbollah launched rocket and drone attacks against them. Lebanon prime minister Nawaf Salam subsequently banned Hezbollah’s military and security activities, according to Al Jazeera.
Oman
Oman’s Duqm commercial port has been hit by several drone attacks, according to Al Jazeera. Omani authorities have said at least one oil tanker off the country’s port of Khasab in the Strait of Hormuz has been attacked.
Qatar
On March 2, QatarEnergy posted on X saying that it would halt production of liquified natural gas following a military attack on its operational facilities in the country. It did not attribute the attack to any particular country. On March 3, it posted again, saying that it would also stop the production of additional products, including urea, polymers, methanol, and aluminum.
Saudi Arabia
Infrastructure in Saudi Arabia has been targeted with projectiles. On March 3, the US embassy in Riyadh, the country’s capital, was damaged following an attack. On March 4, Reuters reported that one of the Saudi Aramco’s largest domestic refineries of Saudi Aramco, the majority state-owned oil company, was targeted by an attempted drone attack.
Syria
Tom Fletcher, the United Nations undersecretary-general for humanitarian affairs and emergency relief, says that civilians and civilian infrastructure were under attack in several countries including Syria.
Turkey
On March 4, the Turkish Ministry of National Defence announced that NATO had intercepted ballistic munitions launched from Iran, and that munition fragments had fallen into Hatay, a province that borders the Mediterranean Sea and Syria. Iran has denied any missile launch towards the country.
United Arab Emirates
As of March 4, UAE Ministry of Defence officials say that the country has intercepted hundreds of drone and missile attacks from Iran. Despite the relatively high rate of interceptions, debris created by the fallout has still damaged areas of the country. In Dubai, the luxury hotel Burj Al Arab was struck by debris, as well as the Palm Jumeirah, a man-made island home to high-end hotels and apartments. On March 2, Amazon Web Services announced that two of its facilities were directly struck in the country, causing “elevated error rates and degraded availability.”
Countries Evacuating Citizens
On March 2, US assistant secretary of state for consular affairs Mora Namdar posted on X urging Americans to depart from several middle eastern countries due to “serious safety risks.” On March 4, Reuters reported that the US military has offered seats on military transport planes to Americans trying to leave the region.
Over a dozen countries have announced that they will be evacuating their citizens from the area or sponsoring repatriation flights, including the UK, Ireland, Germany and Italy.
OpenAI CEO Sam Altman is still in the hot seat this week after his company signed a deal with the US military. OpenAI employees have criticized the move, which came after Anthropic’s roughly $200 million contract with the Pentagon imploded, and asked Altman to release more information about the agreement. Altman admitted it looked “sloppy” in a social media post.
While this incident has become a major news story, it may just be the latest and most public example of OpenAI creating vague policies around how the US military can access its AI.
In 2023, OpenAI’s usage policy explicitly banned the military from accessing its AI models. But some OpenAI employees discovered the Pentagon had already started experimenting with Azure OpenAI, a version of OpenAI’s models offered by Microsoft, two sources familiar with the matter said. At the time, Microsoft had been contracting with the Department of Defense for decades. It was also OpenAI’s largest investor, and had broad license to commercialize the startup’s technology.
That same year, OpenAI employees saw Pentagon officials walking through the company’s San Francisco offices, the sources said. They spoke on the condition of anonymity as they aren’t licensed to comment on private company matters.
Some OpenAI employees were wary about associating with the Pentagon, while others were simply confused about what OpenAI’s usage policies meant. Did the policy apply to Microsoft? While sources tell WIRED it was not clear to most employees at the time, spokespeople from OpenAI and Microsoft say Azure OpenAI products are not, and were not, subject to OpenAI’s policies.
“Microsoft has a product called the Azure OpenAI Service that became available to the US Government in 2023 and is subject to Microsoft terms of service,” said spokesperson Frank Shaw in a statement to WIRED. Microsoft declined to comment specifically on when it made Azure OpenAI available to the Pentagon, but notes the service was not approved for “top secret” government workloads until 2025.
“AI is already playing a significant role in national security and we believe it’s important to have a seat at the table to help ensure it’s deployed safely and responsibly,” OpenAI spokesperson Liz Bourgeois said in a statement. “We’ve been transparent with our employees as we’ve approached this work, providing regular updates and dedicated channels where teams can ask questions and engage directly with our national security team.”
The Department of Defense did not respond to WIRED’s request for comment.
By January 2024, OpenAI updated its policies to remove the blanket ban on military use. Several OpenAI employees found out about the policy update through an article in The Intercept, sources say. Company leaders later addressed the change at an all-hands meeting, explaining how the company would tread carefully in this area moving forward.
In December 2024, OpenAI announced a partnership with Anduril to develop and deploy AI systems for “national security missions.” Ahead of the announcement, OpenAI told employees that the partnership was narrow in scope and would only deal with unclassified workloads, the same sources said. This stood in contrast to a deal Anthropic had signed with Palantir, which would see Anthropic’s AI used for classified military work.
Palantir approached OpenAI in the fall of 2024 to discuss participating in their “FedStart” program, an OpenAI spokesperson confirmed to WIRED. The company ultimately turned it down, and told employees it would’ve been too high-risk, two sources familiar with the matter tell WIRED. However, OpenAI now works with Palantir in other ways.
Around the time the Anduril deal was announced, a few dozen OpenAI employees joined a public Slack channel to discuss their concerns about the company’s military partnerships, sources say and a spokesperson confirmed. Some believed the company’s models were too unreliable to handle a user’s credit card information, let alone assist Americans on the battlefield.
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