Data, AI, & Machine Learning

To adopt intelligent technologies, companies need to develop both the right tools and human capital.

Cognitive speed bumps in AI design can prompt users to engage in reflective thought.

AI can help you choose, measure, and prioritize the KPIs informing your strategy.

Five capabilities and four practices help companies generate business value from AI applications.

Consumers’ concerns about data privacy are offset by a desire for personalized service.

New research by MIT SMR Connections and NETSCOUT reveals IT leaders’ data analytics priorities.

AI is making it possible for companies to reach a new level of customer-centric marketing.

Analytics from ESPN have shown just how important the offensive line is in the NFL.

Chatbots aren’t replacing human customer service agents — they’re making them more efficient.

Smart machines can help pick crops and reduce traffic — but what’s their impact on privacy?

People analytics is at the heart of eSports success.

Unlike the housing bubble, the effects of a bursting AI bubble wouldn’t cause great harm.

A star’s absence, even if it’s just a night off, can mean big financial losses for NBA teams.

Artificial intelligence may look poised to tackle tricky business decisions — but it only works for certain sorts of problems.

Companies must choose whether humans or machines should get the last word on employee performance.

In the race for jobs, the capacity for leisure can give humans a surprising edge.

Elite soccer academies are using analytics to help identify future star talent in the schoolyard.

Organizations need algorithmic smarts to excel in the future of work.

Gillian Armstrong, Eric Kessler, John Ashley, and Abbie Lundberg discuss how to identify opportunities to automate, enhance, or innovate with AI.

By adding new incentives to long-term contracts, teams may be able to offset the likelihood of poor effort.