Are you experimenting with artificial intelligence, or are you “AI future-ready”? A new model maps four stages of enterprise AI maturity.

Generative AI and financial data are opening up the digital economy to more consumers and small businesses, but crypto concerns remain.

Using the wrong datasets to train AI models can result in legal risks, bias, or lower-quality models. The Data Provenance Initiative’s tool can help.

This Entrepreneurial Strategy Compass from MIT Sloan helps startups avoid conflicting advice and choose the right path to commercialization.

A combination of AI and humans works best in tasks where humans outperform AI and in those that involve creating content.

Research topics include analyzing firm behavior, data-driven sequential decision-making, inequality and worker power, and renewable energy integration.

The art of leadership requires putting theories into practice. Painters, musicians, and acrobats can be some of the best teachers.

Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks.

Indirect emissions that occur along a company’s value chain account for 75% of the organization’s overall emissions, on average. They remain difficult to track.

Experts say those making decisions about AI should engage proactively with policymakers and consider worker voice and well-being.