Artificial Intelligence

Companies that adopt industrial artificial intelligence see productivity losses before longer-term gains, according to new research.

Enterprises racing to adopt AI must be wary of giving into hype, downplaying ethical concerns, and focusing on use cases that won’t generate real value.

Eight research-backed titles covering retirement transitions, artificial intelligence and skills development, and how to build an innovation advantage.

A new book aims to help business leaders separate real AI value from overhyped claims.

New research ranges from how AI agents negotiate to how “personality pairing” can optimize human-AI collaboration.

The work tasks that AI is least likely to replace are those that depend on uniquely human capacities, such as empathy, judgment, ethics, and hope.

Three steps to finding use cases for large language models: Break down workflows into tasks, consider all costs associated with automation, and launch pilots.

Organizations have options when it comes to using or adapting off-the-shelf large language models to handle tasks or business use cases.

While generative AI is widely accessible and useful, businesses need to know when to use other AI tools, like traditional machine learning.

Companies perform better when their boards and executive teams stay current with fast-moving technologies.