OpenAI got “distracted by side quests” and is now refocusing on enterprise tools that generate revenue. We take inventory of all of the company’s side projects, including the ones it’s recently abandoned.
Too many organizations understand the AI skills gap backwards, focusing too much on the output layer. Most AI projects that fail go astray because of bad data, and that’s where you need to focus.
The AI bubble narrative suggests that the underlying technology has no value, but it is already changing the way we work. Even if some companies are overvalued, AI is here to stay.
Meta Superintelligence Labs has finally released its first AI model, Muse Spark. It packs quite the punch for its compact nature, but its consumer-first focus might fail to close the gap with competitors fueled by enterprise revenue.
As companies begin factoring AI implementation into performance reviews, employees are being asked to prove its impact. Here’s how to quantify your results, explain your approach and show how your use of AI drives real business value.
An AI system can be technically dazzling, but users will still abandon it if it’s hard to use or feels untrustworthy. User research is how you bridge the gap between technical power and adoption.
Smart glasses promise convenient, wearable AI. But when recording is on a constant, continuous loop and the point-and-shoot social cue disappears, legal guardrails start to crack.
Modern enterprise IAM is shifting to govern AI agents as first-class identities, distinct from service accounts. Our expert explains how to make the switch.
