Data, AI, & Machine Learning

Banning GenAI tools won’t work. Leaders should set guidelines that let employees experiment: This mitigates risks while opening the door to organizational gains, research shows.

Generative AI is already affecting how creative professionals work. Prepare now for more disruption.

Organizations can develop effective digital twins despite limited training data by combining AI and human knowledge.

Developing a cohesive approach to AI deployment requires the right people — and mindset. Here's how to bring together the human resources to manage the opportunities and risks.

Image- and text-generation tools are helping innovation groups improve ideation and creativity and gain market insights.

Two frameworks can help organizations identify potential harms posed by algorithms, AI tools, or large language models.

Checking assumptions and mapping out work processes can help ensure that ML solutions fit the job to be done.

The natural language capabilities of LLMs can augment the predictive powers of advanced analytics.

Gaining value from data assets that include customers’ personal information requires advanced data protection tactics.

When humans are in the loop with an AI system, they may not feel a sense of responsibility to intervene if things go wrong.