AI, Economy & Markets

AI lifts weaker workers' output, but not their unaided judgment Training mid-tier workers in checking AI output pays off Top workers thrive, while the bottom tier cannot be saved In a study of 5,172 customer support ag

AI adoption follows different paths across worker age groups Older workers face accumulated digital barriers and lower exposure Younger workers increasingly adopt AI under labor-market pressure Age and adoption of AI initial

Study tests three explanations for r*'s post-2020 rise Fiscal news, AI news, Fed meetings all fail to explain it AI news lowers r*; the increase remains unexplained The United States' natural real interest rate, kno

AI adoption follows economics, not technical exposure alone Lower costs can expand demand rather than eliminate jobs Comparative advantage determines where automation becomes commercially rational Technically e

Korea adopts AI faster than productivity grows AI gains remain concentrated in higher-paid work Implementation determines whether efficiency becomes output AI now saves the global economy about $2.7 trillion a year in

AI may boost growth but not fix U.S. debt Capital, not labor, captures most AI-driven income gains Political spending risks outpacing any real AI dividend The U.S.

Data centers create construction jobs, few permanent ones Labor shortages, not automation, are the real bottleneck Incentives should reward construction, fund trade training A hyperscale campus in Lebanon, Indiana w

AI can extend healthy life while eroding the job security that pays for it A small group gains from AI, while others lose both work and access to care Sharing AI's health gains requires sharing its productivity gains too

AI use is already widespread Better output does not prove learning Assessment must verify unaided skill Ninety-four percent of software leaders say AI has produced a meaningful productivity gain.

AI does not create a separate and measurable tax base Europe should tax economic rents and shifted profits, not AI use A layered tax framework can protect revenue without discouraging adoption

Data-centre hosts should recover identifiable local costs Server location cannot reveal where all AI rents arise Facility charges and wider profit allocation require separate rules

AI can raise productivity without causing broad job losses Fiscal outcomes depend on who captures the gains Tax bases weaken when income moves from wages to mobile or deferred returns

AI can make basic financial guidance cheaper and more personal Its advice often follows life-cycle theory but falls back on rough rules Public standards are needed before guidance becomes automated action

AI productivity gains remain limited and uneven Entry-level hiring may weaken before mass layoffs appear Policy must protect workers as tasks are redistributed The most informative figure in the AI employment debate is not 5

AI exposure follows work and capacity, not party identity The divide is between places that gain from AI and places that absorb its shocks Policy should focus on tasks, infrastructure and local power, not red-blue maps The c

AI will reshape trade first through prices, not only through jobs Countries that adopt AI can gain, while non-adopters risk weaker exports The real policy test is whether workers can move into better work fast enough

AI trading can turn private choices into one crowded move DQN tools may create stronger herding than LLMs The policy goal is market diversity, not just smarter trading

AI boosts output, but may weaken jobs Less work means weaker demand Training must come before displacement

AI can weaken the local tax base. Bond yields reveal that fiscal risk Policy must track local value, not AI adoption Research context

AI will reshape work unevenly, not all at once The real risk is losing entry-level career ladders Policy should track labor signals and act before shocks deepen Among the AI Labor Transition, what is meaningful is not a