Beth Stackpole

Rewind a few years, and large language models and generative artificial intelligence were barely on the public radar, let alone a catalyst for changing how we work and perform everyday tasks.

It's a puzzling moment for U.S. manufacturing: Despite upticks in the number of new factories and workers over the past several years, real productivity has declined, out of pace with new investments.

Expect a level-set year and a sharper focus on enterprise value. Artificial intelligence has dominated economic and business attention for the past several years.

Adaptable robotic systems incorporating AI, new vision tech and low-code programming are being used to tackle frequent product changeovers and a variety of production tasks by manufacturers of all sizes.

What you'll learn: The new Question Burst Catalyst tool from MIT Sloan's Hal Gregersen helps leaders use large language models as a thought partner to help surface ideas that truly matter.

Generative artificial intelligence is opening doors to unprecedented productivity and growth opportunities.

Organizations that succeed with digital innovation engage three types of leaders: initiative leaders, shared resource leaders, and portfolio leaders. Each has distinct areas of responsibility and complementary knowledge and expertise.

Few organizations have successfully parlayed artificial intelligence experimentation into large-scale initiatives that move the needle on critical business metrics like revenue growth or productivity gains.

Our current work tools, like Jira and Slack, exist to manage human delays, but AI agents are fast enough to make traditional backlogs obsolete.

As businesses pull out all the stops to integrate artificial intelligence tools into mainstream workflows and business practices, they may be