Deep analysis and background on the big AI topics.
15 stories
An internal study from Anthropic details profound workplace changes: junior technical hiring has dropped to single digits while AI agents outwork human staff hours by six to one.
Surveys by Datadog and Mastercard reveal that while European firms push AI into operations, organizational governance and legacy infrastructure struggle to keep pace.
New reports by Bitkom and FNF reveal dual AI dependencies: while executives use US tools, developers increasingly turn to Chinese models that are up to 33 times cheaper.
New macroeconomic and IT spending reports reveal that AI delivers productivity gains almost exclusively to Big Tech, while broader industries face flat output and delayed financial returns.
Research by the Institute for Employment Research shows that while experienced employees benefit from AI adoption, employment among young workers in exposed jobs has declined.
Despite the rapid spread of AI tools in workplaces, new empirical studies by Deloitte and MIT show that few large enterprises have deeply integrated the technology into core operations.
New studies from Ricoh and Founder Reports show workplace AI tools often cause friction and extra work, as software rollouts outpace change management and training.
Despite rising investments, 44 percent of CEOs struggle to prove financial returns on AI. New data shows that rigid internal processes and missing use cases hold back value realization.
New surveys from KPMG and Redwood Software show that as enterprises pour millions into AI agents, many face sudden cost spikes, control lapses, and measurement blind spots.
New empirical data reveals European developers shifting heavily toward Chinese models, even as real-world productivity increases remain modest and governance lags behind.
Surveys from Creatio, Grafana Labs, and GoodFirms document enterprise transitions toward AI agents, alongside clear constraints on autonomy and mandatory human oversight for critical tasks.
A Gartner survey reveals that only 13 percent of CIOs see significant value from AI investments. High project failure rates and platform sprawl are sobering corporate expectations.
New economic analyses from ifo and McKinsey quantify enterprise AI value in the trillions, while highlighting regulatory risks and an ongoing struggle to convert time gains into EBIT.
A new study by Anthropic reveals a sharp divide: while AI insiders expect massive automation by 2030, the general public anticipates a far slower transformation of everyday work.
Recent Bain & Company studies reveal a growing disconnect between accelerated code generation, surging operational costs, and missed enterprise return-on-investment targets.
