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Companies perform better when their boards and executive teams stay current with fast-moving technologies.

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

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

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

With carbon emissions reduction a top concern, tech leaders are building capabilities that help companies reduce their own emissions and those of suppliers and customers.

To train employees on digital skills, companies need precise insight into current workforce skills. Artificial intelligence can help.

Decontextualize data and prepare data assets that can be reused for many purposes. A new book from MIT CISR researchers explains how.

The key to unlocking new digital value is aligning a reorganization around four levers: customer, capability, commercialization, and component.

Most companies comprehend the impact data has on business strategy. Fewer understand how to convert data efforts into monetary value.

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