Analytics and data science

Three questions to shape your strategy.

To realize the technology’s promise, prioritize outcomes—not tasks.

A playbook for checking your instincts.

Two years ago, licensing deals with AI developers amounted to about $75 million. This year the figure will be about $20 billion—and next year it could be twice that.

Move from individual experiments to robust corporate applications.

Getting on the same page about which metrics really matter helps cut waste and focus investment.

An experiment with MBA students provides a roadmap for building and leading AI-native organizations.

These specialized models can outperform their large counterparts in speed, cost, and control.

Recent firings of top officials at the Bureau of Labor Statistics and the Federal Reserve—as well as shifting tariffs—call for a reevaluation of the data your company consults as it plans for the future.

What Amazon learned when it automated the creation of product pages.

A new study shows they lead to more-creative tech solutions.

A framework to help small teams achieve outsized impact.

Employees’ reluctance to use new tools may actually reflect rational self-preservation.

By studying 100 companies, researchers have identified four ways to strategically implement the technology.

Recent legal rulings will have major implications on both creative industries and AI companies.

Three lessons from the Chinese brand behind Labubu.

Unfulfilled orders lead to long-lasting consequences, from frustrated shoppers to lower future revenue.

This report card offers a systematic approach to identifying and addressing the problem.

It frees middle managers from constant project coordination.