Data

The AI hiring revolution doesn’t have to be a story of automated bias, argues MIT Sloan’s Emilio J. Castilla. Tough questions and constant monitoring can lead to fairer systems.

Leaders who actively design for the widespread use of data assets generate three times the revenue from data monetization compared with their peers.

A study found that trained LLMs can identify what customers want as well as expert market reach analysts, who are freed up to apply their expertise to high-leverage tasks.

Digital platforms have already changed how value is created and exchanged. Their next wave — spanning physical assets, AI, and automation — promises new efficiencies but also new risks.

Data centers that shift workload to different times of day save money, but the environmental impact depends on the local grid.

New research highlights four areas leaders must address as they embed AI across their business.

Applying systems dynamics principles to industrial AI can ensure faster and more impactful business outcomes.

Three approaches to acquiring generative AI solutions for your company, and how to choose the right one.

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

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