Leaders must rethink the way they manage people and projects to ensure that everyone reaps the efficiency and innovation benefits of generative AI.

A new MIT Sloan Experts Series talk explains how algorithms and humans can work together to compensate for blind spots and create clearer outcomes.

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

The work tasks that AI is least likely to replace are those that depend on uniquely human capacities, such as empathy, judgment, ethics, and hope.

To foster a data-centric culture, adopt the right technology, improve data literacy, and don’t be afraid to disrupt the status quo.

Generative AI’s broad accessibility and applicability make it a vital tool for businesses — but those traits can also cause trouble when upskilling employees.

When software developers were given access to an AI coding tool, productivity increased — particularly among newer hires and more junior employees.

Machine learning can drive climate action initiatives, but its widespread use could have negative implications, according to Climate Change AI’s Priya Donti.

From designing intelligent decision processes to tapping the full power of deep learning, here are data practices to adopt now from MIT Sloan analytics faculty.

A “red light, yellow light, green light” framework can help companies streamline AI governance and decision-making.