UK share values'most stretched' since 2008, Bank warns The Bank of England has warned of a sharp correction in the value of major tech companies with growing fears of an artificial intelligence (AI) bubble. It said share prices in the UK are close to the most stretched they have been since the 2008 global financial crisis, while equity valuations in the US are reminiscent of those before the dotcom bubble burst. The central bank's financial stability report warned valuations are particularly stretched for companies focused on AI. It said the growth of the sector in the next five years would be fuelled by trillions of dollars of debt, raising financial stability risks if the value of the companies falls. The Bank of England cited industry figures forecasting spending on AI infrastructure could top $5tn (£3.8tn).

Republicans face potential political fallout if the AI investment bubble bursts during Trump's presidency, similar to how past market crashes hurt incumbent parties at the polls.

On this episode of, guest Brian Merchant walks us through a historical framework he used to analyze whether AI fits the classic signs of an economic bubble--and what that means for all of us. Chatter about an AI bubble has been everywhere lately, and top tech companies like Google, Meta, and Microsoft have doubled down on their AI investments for 2026. But how have analysts in the past accurately identified forming tech bubbles? Hosts Michael Calore and Lauren Goode sit down with Brian Merchant, WIRED contributor and author of the newsletter to break down the four criteria some researchers have used in the past to understand and brace for the worst. Please help us improve by filling out our listener survey . Write to us at uncannyvalley@wired.com . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . Hey Lauren, how are you doing? It's earnings season, so a lot of us on the business desk here at WIRED have been tuning into tech companies earnings reports and their earnings calls. And I guess that basically means it's CapEx season. Now that I'm a business desk reporter, I say CapEx. I throw it around at parties. But we are seeing a trend in how tech companies are sleeping on piles of money, but they aren't just sleeping on it. They're sharing big plans to spend on it, and especially to spend on AI infrastructure. And this is all partly what is fueling all of this talk about a bubble, which we touched on a little bit a couple of weeks ago with our colleague Molly Taft.

Financial bubbles often arrive without much warning, but create long-lasting economic effects. For example, during the dot-com bubble, innovative technologies created market disruptions through excitement for a promised bright future. Such technologies originated from research where scientists had developed them for years prior to their entry into the markets. That raises a question on the possibility of analyzing scientific publishing data (e.g. citation networks) leading up to a bubble for signals that may forecast the rise and fall of similar future bubbles. To that end, we utilized temporal SNAs to detect possible relationships between the publication citation networks of scientists and financial market data during two modern eras of rapidly shifting technology: 1) dot-com era from 1994 to 2001 and 2) AI era from 2017 to 2024. Results showed that the patterns from the dot-com era (which did end in a bubble) did not definitively predict the rise and fall of an AI bubble. While yearly citation networks reflected possible changes in publishing behavior of scientists between the two eras, there was a subset of AI era scientists whose publication influence patterns mirrored those during the dot-com era. Upon further analysis using multiple analysis techniques (LSTM, KNN, AR X/GARCH), the data seems to suggest two possibilities for the AI era: unprecedented form of financial bubble unseen or that no bubble exists. In conclusion, our findings imply that the patterns present in the dot-com era do not effectively translate in such a manner to apply them to the AI market.

Industry 4.0, also known as the Fourth Industrial Revolution, refers to the emerging era of connectivity between machines and humans, specifically in automation and manufacturing. It comprises the internet of things (IoT), cloud computing, cognitive computing and artificial intelligence, which help create real-time access to meaningful and actionable data. The history of industrial progress leading to Industry 4.0 includes the following periods: Industry 4.0 offers entrepreneurs and business managers countless applications across various market sectors, and as such is poised to have a significant impact on the way we all live and work. As increasingly tech-savvy consumers, we have seen many technology trends appear and generate hype. Some of these technologies bring with them genuine disruption and progress, while others may disappear completely or decline.

AI experts are worried the field is on the brink of a scenario similar to the dotcom bubble bursting. It's called an AI winter. And, if it happens, it could leave a lot of researchers, investors, and entrepreneurs out in the cold. Such a scenario could happen for a number reasons, and its effects could vary wildly depending on how poorly the investments in the space end up performing. But before we dive into all of that, it's important to understand that there's no official Bubble Czar out there determining when it's time to head for the lifeboats. The problem with bubbles is you can never tell when they're going to burst – or even if you're in one.

A flurry of technology mergers and acquisitions (M&A) are set to happen before 2020, a new report predicts. However private equity firms – which have recently been elbowing trade buyers out of the way to splash the cash on tech targets, such as in the $5.3bn (£3.8bn) buyout of Nets – could soon see their bubble burst. According to a report from tech-focused deal advisers Hampleton Partners, the availability of cheap debt has allowed private equity to outbid trade buyers. But as interest rates look set to rise, this bubble could burst – possibly causing a price correction. "Despite the slowdown in the second half of last year, the overall outlook in the foreseeable future is very positive as continued technological disruption forces established vendors and new market entrants to innovate and stay competitive via tech M&A," said Hampleton founder Miro Parizek.

There have been several discussions lately around machine intelligence that are started to converge in how they may change competition and regulation in all markets but is likely to become a bigger issue in 2017. This is a bubble waiting to burst. The recent letter for Apple to the National Highway Traffic Safety Administration regarding policy changes to help promote automated self-driving vehicles stressed not just a level playing field to promote new technology and data sharing but also the impact of automated vehicles on the public good, including their consequences for employment and public spaces. Other issues around consumer product automation in the home with Amazon Echo Alexa and Google Home have raised the bar in interactive systems and questions over the type of privacy and data use issues these may bring. Other issues have been raised over the use by Facebook of algorithms for "editing" the social media sites for certain political issues or in the case of their entry to the Chinese market and creating a censoring app to comply with regulations.