Data, AI, & Machine Learning

Organizations that struggle to gain payback from data science efforts can recognize and overcome five common obstacles.

To gain business agility, leaders must deconstruct jobs into tasks and deploy workers based on their skills.

Data accessibility must be managed from the start of AI projects in order to be implemented in production.

Collecting and analyzing the right employee data can help leaders build more equitable workplaces.

Recommendation engines promise to revolutionize how customers buy and employees work.      

Discover how to overcome challenges and identify opportunities by assembling the right talent, upskilling your leadership skills, and reshaping organizational strategy. The AI & ML collection helps leaders think strategically about artificial intelligence and make the kinds of decisions that will best leverage the associated new technologies.

In this new executive guide, you'll learn how to build a successful data approach, embrace a culture of experimentation, and identify which data systems in your company need improvement. The Data Strategy collection helps leaders think strategically about data and analytics and make the kinds of decisions that will best leverage the associated new technologies.

Companies can use data and collaborative scenario plans to enhance supply chain responsiveness. 

Companies that change processes to facilitate organizational learning with AI realize the biggest business value.

Boards will need increased technology fluency to provide adequate oversight of AI risk management.