Artificial Intelligence

The age of agentic AI — systems that are semi- or fully autonomous and can act on their own — has arrived. Here’s what you need to know, according to MIT experts.

Stagnant productivity, a tightening workforce, and rising global competition are reprioritizing manufacturing in the U.S. What’s needed: new production models.

As AI capabilities advance, the window for shaping whether the technology augments or replaces workers is narrowing. Decision makers need to step up, MIT researchers say.

Creativity and clean data are at the core of successful artificial intelligence implementations, according to the CFOs of Shopify and Arm Holdings.

AI systems built or run with limited resources could soon perform on par with leading larger models while costing much less, according to new research.

MIT Startup Exchange supports MIT-connected ventures as they explore and assess new technologies. Here are eight companies that were featured in its recent Virtual Demo Day.

Experts in artificial intelligence from MIT Sloan are keeping an eye on the human-LLM accuracy gap, AI guardrails, and other trends.

Open-source and open-weight AI models perform well and cost less — but users opt for closed models 80% of the time, according to new research.

As businesses adopt AI, they need to rethink how they make money. Understanding these four new business models is a place to start.

AI really can pay off. But leaders must take a systematic approach, understand how the technology works, and let their team leaders determine how it’s used.