detention facilities. CoreCivic’s net profit in the first quarter of 2026 was up by half from the year before. For Geo Group, it doubled. Deportation has also become a lucrative industry. March set a monthly record for ICE of nearly 1,800 deportation flights. Airlines such as GlobalX are profiting handsomely. The carrier, which had been making losses until recently, saw its sales rise by 15% year on year in the first quarter, thanks largely to deportation flights. Most in the industry expect the boom to continue. Looking soft on illegal immigration has proved time and again to be a vote-loser. Politicians will be reluctant to tighten the purse-strings. ■ To track the trends shaping commerce, industry and technology, sign up to “The Bottom Line”, our weekly subscriber-only newsletter on global business. This article was downloaded by zlibrary from https://www.economist.com//business/2026/05/14/companies-are-making-big-bucks-from- immigration-crackdowns
Introducing “Velocity pivot” The corporate world’s Lorem ipsum May 14th 2026 We are pleased to announce a modern alternative to the “Lorem ipsum” text. This much-loved piece of filler text, derived from Cicero’s “De finibus bonorum et malorum”, has been used for layout purposes for centuries, and remains available for anyone to use. But we believe that other, newer forms of meaningless babble are even better at taking up space, which is why we are thrilled to unveil “Velocity pivot”. For most forms of corporate communication, it is not necessary to change the text at all before you publish. Velocity pivot hunger to win relentless execution insatiable appetite artificial intelligence tokenmaxxing tokenised toecurling double-digit growth transformational volatility fireside chat drinking from a fire hose burning
platform general pyromania augmentation not automation it’s not AI that will take your job but the person using AI headcount reduction tough decisions rightsizing. Innovation powerhouse three horizons four Ps five whys six is too many town hall watercooler conversations think like an owner speed up fast forward step back step up zoom in zoom out I’m feeling quite dizzy helicopter view deep dive top-down bottom-up downside upside rotating turnaround no really I am going to be sick. Change management strategic strategising waterfall agile sprint cascade tentpole brainstorming whiteboard miro board bored senseless modernising digitisation revolution not evolution not revolution vibe-coding value-added MVP SVP FIFA CRO MCP PRD BBQ BAU KPI DEI though we don’t talk about the last one much any more. Data is the new oil models are the new oil oil is the new oil surplus abundance multiplier effect 10x 100x 1,000x oh what the hell 10,000x impact deep impact really deep impact supercharged superexcited superpower superintelligence supermarket superstars tipping point inflection point choke points three-point turn lean elevate sharpen reach out circle back converge spin up spin down spin out. Edge cases use cases suitcases frequent flyer lounges platinum member air miles in flight dynamic environment shifting landscape new industrial revolution bias for action actionable traction tractionable is that a word? It is now reimagine reinvent reinforce revamp renew redefine resilient grit growth mindset futuristic heuristic holistic optimistic systemic getting the ic. Transforming the value proposition propositioning transformational value delighting customers strengthening communities leveraging insights other verb-noun combinations end-to-end workflows deployment training inference stack full-stack slack attack geopolitics geoeconomics geotechnology geography is back top-right-hand quadrant total alignment partial alignment non-alignment disagree and commit together. Unfolding ever-changing fresh perspectives instant personalised large-scale multi-year multi-service long-term investment pipelines embedded
ecosystem leaders leading through leadership leaden prose new normal new paradigms paradox parabola hockey-stick J-curve K-shaped A-game C-suite B-yoncé. Improved outcomes purpose values mission behaviours customer-centricity customer-obsessed sounds a bit creepy to be honest bold audacious daring restless ambition world-class industry-leading game-changing topline metrics blueprint corporate DNA digital workforce orchestration agentic compute fuelling propelling driving accelerating never braking operational platform analytics global footprint local know-how uniquely positioned scaling powering delivering achieving winning executing mastering aggressive complete passivity just kidding. Decision points gates milestones gallstones durable sustainable confident momentum sentiment differentiated competitive advantage organic growth inorganic growth basically growth core business core strength cor blimey cycles cycling triathlon lycra stretch goals objectives key results at scale pace of change testament to the value of the brand maximise breakthroughs unlock potential expand frontiers utilise headroom advance something or other. Velocity pivot hunger to win relentless execution insatiable appetite artificial intelligence tokenmaxxing tokenised toecurling double-digit growth transformational volatility fireside chat drinking from a fire hose burning platform general pyromania augmentation not automation it’s not AI that will take ■ Step inside the world of work with our Bartleby newsletter. Each week our white-collar oracle muses on the agonies of office life. This article was downloaded by zlibrary from https://www.economist.com//business/2026/05/14/introducing-velocity-pivot
Big tech is sacrificing its cashflows to prop up the AI boom The result is increasingly unsettling May 14th 2026 Achart is haunting Silicon Valley. The profits of big cloud-computing firms (Amazon, Google, Meta, Microsoft and Oracle) are rising inexorably. Yet the amount of cashflow they generate after capital spending is falling. Sketched together, these soaring profits and diving free cashflows, which until recently rose in unison, resemble the gasps of the world’s investors. In short order America’s biggest companies have gone from printing money to burning it. Amazon, Meta and Microsoft are all expected by analysts to announce negative cashflows in at least one quarter this year. Alphabet, the parent company of Google, will just about keep its head above water. Oracle, the weakest of the bunch, is already drowning.
It does not take Poirot to work out what’s going on. This year the five firms will spend $800bn filling warehouses with computers to run artificial- intelligence models. These investments barely register on their profit statements, since assets depreciate only once built—and then only slowly. Cashflow statements, though, are less susceptible to obfuscation. At around 40% of their revenues this year, the cloud giants’ capital expenditures will surpass those of the oil industry during the shale boom in the 2010s and the telecoms industry during the dotcom bubble in the 1990s. Arguments dismissive of the scale of big tech’s transformation have collapsed under the weight of the growing bill. Comparisons to the dotcom bubble are wrongheaded because the big spenders today generate ample cashflows, went one argument. Not any more. Their cashflow pressures cannot be that great because firms are still buying back bucketloads of their own stock, many said. During the most recent quarter, buy-backs collapsed. A third is that big tech trades at “only” 23 times the firms’ forecast earnings. Yes, but when the denominator of this equation captures almost nothing of their spending, is it at all useful? Nowadays investors judge the success of these firms on the basis of concentrated revenue contracts stretching far into the future, rather than dispersed sales received today. Mostly these contracts involve selling computing capacity to model-makers like OpenAI and Anthropic, which are themselves incinerating vast piles of cash. Total future revenue agreements have risen to $2trn, from $730bn last year, at Amazon, Google, Microsoft and Oracle (Meta is a buyer, rather than a seller, of computing capacity). Simple balance-sheets with intangible assets and generous cash buffers have been replaced by ones which are complicated, asset-heavy and indebted. Since the start of last year the big five have raised $260bn from bond markets, a quarter of all such borrowing by listed American non-financial firms. What started as a local affair has become a global bacchanal. Nearly a third of the haul from selling bonds this year is in currencies other than the dollar. Alphabet, Google’s parent, will soon issue its first bonds denominated in yen. Much larger obligations lurk off-balance-sheet. The biggest are $820bn of future payments to lease data centres yet to be built, up from $270bn a year
ago. Commitments to spend money on other things, like packing their data centres with chips, have risen as fast. Amazon, Google, Meta and Oracle now disclose $680bn of such obligations. Other bills are tied to special- purpose vehicles: separate entities with their own balance-sheets. Last year one assembled to build Meta’s new data-centre in Louisiana issued the biggest single corporate bond in history. Oracle’s finance chief recently talked about “uncoupling” the firm’s cashflows from its capex, presumably with similarly advanced financial engineering. This vast nexus of AI contracts combines an absolute faith in technologists with a naive trust in lawyers. Occasionally the market is discerning about what these contracts really mean; Oracle’s shares have been hammered since investors realised how dependent its future revenue is on OpenAI. More often the market is obtuse. Bankers increasingly whisper about decaying documentation in AI financing agreements. “When we ask our lawyers to find ways that a hyperscaler might wriggle away from or re-negotiate a lease contract, often they come back with a very long list,” says the boss of one big lender that has steered clear of some more esoteric financing structures in the AI boom. So far the capex splurge has been a great act of charity to the rest of America’s tech industry. The five firms have assumed the role of central planners, attempting to make the complex chain of returns on investment work across the AI economy: data centres are useless if businesses don’t find models worth paying for, which only happens if model-makers can raise enough capital to make them. In the process, the hyperscalers have sacrificed their own returns. Only shares in Alphabet have beaten the NASDAQ index during the past year. Big tech has also liberally lent its creditworthiness across capital markets. Many firms that contract with the giants can take those contracts to the bank (literally) and raise more debt. Moreover, the hyperscalers’ capex has become someone else’s free cashflow. Broadcom, Micron, Nvidia and Sandisk, four chip companies, are all minting real fortunes outfitting big tech’s data centres. Together they account for a quarter of the expected profit growth in the S&P 500 index this year.
Clearly this is unsustainable without enterprises becoming much more willing to pay for AI. But for now there are no brakes on the train. The hyperscalers’ capex bills this year will be twice as great as analysts predicted they would be a year ago. If AI models keep getting hungrier for computing power and the cost of equipment keeps rising, this forecast will soon be left behind, as those that came before it were. After two years of consistent shock-and-awe, nothing would be less shocking. ■ Subscribers to The Economist can sign up to our Opinion newsletter, which brings together the best of our leaders, columns, guest essays and reader correspondence. This article was downloaded by zlibrary from https://www.economist.com//business/2026/05/13/big-tech-is-sacrificing-its- cashflows-to-prop-up-the-ai-boom