Data

Experts from Salesforce, S&P Global, and Corning share six key strategies to unlock generative AI’s potential without falling for the hype.

Top-performing companies invest in CEO-level data leadership, data value realization, and data resource life-cycle measurement.

AI workloads have sent data center emissions skyrocketing. An MIT expert details ways to reduce energy use and promote sustainable AI.

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.

Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.

The AI Risk Repository, a database of over 700 risks posed by AI, aims to provide a shared framework for monitoring and maintaining AI risk oversight.

When enterprises address opportunities or threats immediately, they perform better. A new research briefing looks at the traits such companies share.

To truly reap the benefits of artificial intelligence, executives need an understanding of how AI systems operate and what they do well.

MIT Sloan student teams advise Pfizer, Comcast, and others on using data and generative AI to bring products to market and communicate with customers quickly.

Companies should prioritize the capture, management, and availability of data, according to the 2024 Data and AI Leadership Executive Survey.