An AI crash could bring down the economy. Some in the tech world think that's the price of progress. The tech billionaire Hemant Taneja admits that AI is a bubble. In fact, he welcomes it: "Bubbles are good," Taneja, the CEO of General Catalyst, a venture-capital firm, told me in an email. If AI comes crashing down, it will lead to "some spectacular failures," he said--companies will go under and people will lose their jobs--but that's a price worth paying for "enduring companies that change the world forever."

In physical systems where errors carry tangible consequences, AI creates value through reliability and first-time-right performance. The impact of artificial intelligence extends far beyond the digital world and into our everyday lives, across the cars we drive, the appliances in our homes, and medical devices that keep people alive. More and more, product engineers are turning to AI to enhance, validate, and streamline the design of the items that furnish our worlds. The use of AI in product engineering follows a disciplined and pragmatic trajectory. A significant majority of engineering organizations are increasing their AI investment, according to our survey, but they are doing so in a measured way. This approach reflects the priorities typical of product engineers.

It generally takes 18 to 36 months to build a hyperscale AI site - such as, presumably, one of the world's most powerful supercomputers. It generally takes 18 to 36 months to build a hyperscale AI site - such as, presumably, one of the world's most powerful supercomputers. From press release to scrap metal site: the Essex'supercomputer' that's still a scaffolding yard Nscale's AI project still in use as depot ahead of pledged completion date - with planning permission filed after Guardian's inquiries Revealed: UK's multibillion AI drive is built on'phantom investments' T he press releases announcing a gleaming supercomputer on the outskirts of north London depict a glass and concrete building, rising from a tree-lined street. Accompanied by images of glowing blue robot faces, it looks like the centre of a technological revolution. By the end of this year, that artist's impression is supposed to be a reality.

The central objective of empirical asset pricing is to identify firm-level signals that explain the cross-section of expected stock returns--whether through exposure to risk factors or persistent mispricing. The dominant paradigm, grounded in the assumption of self-predictability, asserts that a firm's own characteristics forecast its own returns (see, e.g., Cochrane (2011); Harvey et al. (2016)). Complementing this view is a growing literature on cross-predictability--the idea that the characteristics or returns of one asset can help forecast the returns of others (see, e.g., Lo and MacKinlay (1990); Hou (2007); Cohen and Frazzini (2008); Cohen and Lou (2012); Huang et al. (2021, 2022)). A key mechanism underpinning this phenomenon is the presence of lead-lag effects, whereby price movements or information from one firm precede and predict those of related firms. Such effects can stem from staggered information diffusion, peer influence within industries, supply chain linkages, or correlated trading by institutional investors that induces price pressure across related assets. Despite recent methodological advances in modeling cross-stock predictability, several foundational questions remain unresolved. Chief among them is how a mean-variance investor can analytically integrate multiple predictive signals when returns are interconnected across assets. Equally crucial is developing a framework that jointly captures both the relevance of individual signals and the structure of return spillovers--enhancing portfolio performance while preserving interpretability .

Visualising AI spending: How does it compare with history's mega projects? World leaders and tech executives are convening in New Delhi for the India-AI Impact Summit 2026, focusing on the role of artificial intelligence in governance, job disruption and global collaboration. However, behind these discussions lies the financial reality. Over the past decade, AI has drawn one of the largest waves of private investment in modern history, totalling trillions of dollars. According to Gartner, a United States-based business and technology insights company, worldwide spending on AI is forecast to total $2.5 trillion in 2026, a 44 percent increase over 2025.

Traders on the floor of the New York Stock Exchange as markets fell on Friday morning trading after a steep drop on Thursday, as investors continue to worry about the impact of AI on business and the wider economy. Traders on the floor of the New York Stock Exchange as markets fell on Friday morning trading after a steep drop on Thursday, as investors continue to worry about the impact of AI on business and the wider economy. The message from investors to the software, wealth management, legal services and logistics industries this month has been clear: AI is coming for your business. The release of new, ever more powerful AI tools has coincided with a stock market slide, which has swept up sectors as diverse as drug distribution, commercial property and price comparison sites. Advances in the technology are giving increasing credulity to predictions that it could render millions of white-collar jobs obsolete - or, at least, eat into the profits of established companies.

This story appears in the March 2026 print edition. While some stories from this issue are not yet available to read online, you can explore more from the magazine . Get our editors' guide to what matters in the world, delivered to your inbox every weekday. America Isn't Ready for What AI Will Do to Jobs Does anyone have a plan for what happens next? In 1869, a group of Massachusetts reformers persuaded the state to try a simple idea: counting. The Second Industrial Revolution was belching its way through New England, teaching mill and factory owners a lesson most M.B.A. students now learn in their first semester: that efficiency gains tend to come from somewhere, and that somewhere is usually somebody else. They were operating at speeds that the human body--an elegant piece of engineering designed over millions of years for entirely different purposes--simply wasn't built to match. The owners knew this, just as they knew that there's a limit to how much misery people are willing to tolerate before they start setting fire to things. Still, the machines pressed on. Check out more from this issue and find your next story to read. So Massachusetts created the nation's first Bureau of Statistics of Labor, hoping that data might accomplish what conscience could not. By measuring work hours, conditions, wages, and what economists now call "negative externalities" but were then called "children's arms torn off," policy makers figured they might be able to produce reasonably fair outcomes for everyone. A few years later, with federal troops shooting at striking railroad workers and wealthy citizens funding private armories--leading indicators that things in your society aren't going great--Congress decided that this idea might be worth trying at scale and created the Bureau of Labor Statistics. Measurement doesn't abolish injustice; it rarely even settles arguments. But the act of counting--of trying to see clearly, of committing the government to a shared set of facts--signals an intention to be fair, or at least to be caught trying. It's one way a republic earns the right to be believed in. The BLS remains a small miracle of civilization.

Asked about the terms of the deal, including the board seats, the timing and the size of the investment, Mr. Wachsman said, "We made the deal in question because we strongly believe that it was what was best for our company as we continue to grow." Representatives for Sheikh Tahnoon did not immediately respond to a request for comment. The Trump family's business dealings with the Emiratis have blurred the line between government and private enterprise, alarming ethics experts and congressional Democrats. Sheikh Tahnoon, a member of the Emirati royal family, has been a major foreign policy intermediary with the United States for over a decade on matters varying from combating terrorism to sharing advanced computer technology. He runs a sprawling investment empire that includes G42, a technology firm that has become a powerhouse in the booming world of artificial intelligence.

Americans pulling into a Starbucks drive thru might think they are being served by a friendly staff member. But at some locations, the voice listening to the order is actually an AI robot. Behind the counter inside the store, baristas can lean on a virtual personal assistant to recall recipes or manage schedules. In the back of the shop, a scanning tool has taken on the painstaking process of counting the inventory, relieving staff of one of retail's most tedious chores, in a bid to fix the out-of-stock gaps that have frustrated the firm. The new technology is part of the hundreds of millions of dollars the 55-year-old coffee giant has been investing as it tries to win back customers after several years of struggling sales.