AI is changing which human capabilities matter most at work, yet employees are reporting that some of those same capabilities are being eroded, according to a new IBM study.
Gartner forecasts worldwide AI spending will reach $2.67 trillion in 2026, up 49.5% from 2025, with AI infrastructure accounting for nearly $1.5 trillion, or about 56% of the total. For every dollar Gartner expects to be spent on generative AI models, more than $52 will be spent on infrastructure.
As AI systems become capable of generating genuinely novel scientific results, determining who discovered something, who deserves credit, and what role the company behind the model played will become considerably harder.
In an active social engineering campaign, attackers are impersonating IT help desks and using fake passkey setup requests to compromise employee identities and gain access to enterprise cloud data.
Microsoft has published a draft code of conduct that details how its homegrown AI models should behave, with human control taking priority over model capability, autonomy, and even task completion.
For years, leaders in the artificial intelligence industry have warned that increasingly capable AI systems could eventually become dangerous, all the while continuing to race to build them. Now, their sentiments have changed.
OpenAI has published what it says is an AI-generated solution to the Navier-Stokes existence and smoothness problem, one of mathematics' seven Millennium Prize Problems, while Anthropic has reported separate advances in research mathematics and formal proof generation.
OpenAI has unveiled GPT-6 Astra, its most capable broadly deployed model and the first system the company says has reached the "Critical" cybersecurity capability threshold under its Preparedness Framework.
Cybersecurity companies Rubrik and CrowdStrike have announced an expanded identity-security integration intended to move compromised identity environments from threat detection through clean recovery with less manual intervention.
Gartner's 2026 Magic Quadrant for Enterprise Storage Platforms reflects a broad infrastructure shift driven by hypervisor changes, cloud-style consumption economics, surging hardware costs, and AI.