Data, AI, & Machine Learning

When deciding whether to deploy a machine learning model, focus on business metrics, not technical ones.

Is your AI project using the right data, and is it set up to succeed? Ask the right questions to head off failure.

Large AI models are big energy consumers and carbon emitters. Sustainable AI practices can reduce their environmental impact.

Understanding large language models’ limitations can help users discern which tasks they are and are not well suited for.

Employees in connector roles can bridge the gaps between departments that often thwart data science project success.

Effective governance enables KPIs to evolve, remain aligned with strategic goals, and gain workers’ and managers’ trust.

Research finds that managers who want to create better job roles can use an effective new assistant: ChatGPT.

Emerging machine learning technology could enhance sound creation and the detection and analysis of acoustic signals.

A data monetization matrix can help leaders assess opportunities and approaches for converting data into revenue.