Research

Three levers — data architecture, data preparation, and data permissions — determine whether data becomes a reusable strategic asset or stays trapped in silos.

Researchers at the MIT Initiative on the Digital Economy share the latest insights about getting the most from working with AI, such as personality pairing and reorganizing job tasks.

A new paper explores how seeing economic value from artificial intelligence hinges on closing the gap between what AI can do and how humans can verify its outputs.

Organizations are struggling to succeed with AI. Research from the MIT Center for Information Systems Research shows common mistakes and how to overcome them.

Learnright laws would give copyright holders the exclusive right to license their content for artificial intelligence model training.

When professionals try to validate outputs, generative AI often responds not with corrections or candor but with escalating persuasion tactics.

New research shows that AI delivers the most value when organizations redesign workflows, not just when they automate individual tasks.

A study of consultants found that employees use generative AI three different ways. Each has different implications for on-the-job learning.

Here’s how aircraft noise at major airports in Boston, Chicago, and Seattle affected housing prices.

Sound economic planning and policymaking requires trustworthy data. Private data can serve as a complement but not fully replace official U.S. statistics.