Artificial Intelligence

Generative artificial intelligence is rapidly emerging as a key foundational platform for new applications. But hurdles remain, according to researchers.

Launching a venture? Here’s advice from MIT entrepreneurs in residence on navigating artificial intelligence, the economy, and uncertainty.

From risk management policies to the five stages of AI ethics, here’s how some organizations approach ethical AI.

Colgate-Palmolive, Sanofi, and other firms are making generative AI work for them in ways both big and (intentionally) small.

Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks.

Experts say those making decisions about AI should engage proactively with policymakers and consider worker voice and well-being.

Using the wrong datasets to train AI models can result in legal risks, bias, or lower-quality models. The Data Provenance Initiative’s tool can help.

Generative AI and financial data are opening up the digital economy to more consumers and small businesses, but crypto concerns remain.

Are you experimenting with artificial intelligence, or are you “AI future-ready”? A new model maps four stages of enterprise AI maturity.

Artificial intelligence can be useful in the workplace, but humans have to first define what success looks like, according to MIT Sloan’s Danielle Li.