Most organisations already have more data than they can use and more AI tools than they can operate. The dashboards are built, and the pipelines run every night. And still,

Something uncomfortable is showing up in the latest workplace data. Employees have picked up advanced AI habits faster than the organizations they work for can absorb them. The tools are

Most AI projects look healthy the day they go live. The trouble starts later, when the shortcuts that got them shipped fast begin to cost more than they saved. Data

There’s a specific kind of anxiety spreading through organizations right now. Not the fear of AI taking over — something subtler. The feeling that everyone else is figuring out how

AI assistants are being introduced into enterprises through specific functions—sales, customer service, and internal operations—rather than as a single, general-purpose solution. Their impact is typically evaluated on concrete activities such

It usually starts the same way. You know the document exists. You’ve seen it before. Maybe it was shared in an email, or saved somewhere in a shared drive, or

Every year, HBR’s AI in the Wild study analyzes thousands of real generative AI use cases, drawing on posts and conversations from Reddit, LinkedIn, TikTok, and YouTube. This year’s sample

For a long time, video has been treated as a passive asset—something to store, catalog, and occasionally retrieve. But what if video could actually be understood? This is where video

Here we go again, it’s that time of year. Stanford HAI has published the 2026 edition of its AI Index Report, and as every year, we’ve worked through it to

In the global race toward AI transformation, most organizations are asking the same questions:Do we have the right tools? The right infrastructure? The right use cases? But there’s a more