Data management

LLMs ask questions differently than humans—and that affects how executives use these tools to make decisions.

To drive agentic commerce adoption at scale, brands need to figure out how to earn—and keep—customers’ trust.

Three keys to success in a fractured global business environment.

This four-phase approach bridges the gap between technical possibility and business reality.

Leaders from Fortune 1000 and leading global brands are bullish about their AI investments—but face common problems around adoption and change management.

Four research-based imperatives for executives.

A four-step playbook to align data analysis with strategy.

How to define the role, provide a clear mandate, and ensure they’re positioned to deliver value for the company.

Eight ways to experiment with “synthetic personas” and “digital twins.”

Three questions to shape your strategy.

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.

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 framework to help small teams achieve outsized impact.

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