Data, AI, & Machine Learning

Counterpoints looks at whether analytics can quantify team chemistry.

A successful pitch for AI must overcome economic, technical, political, and cultural hurdles.

Defensive analytics are shaping how NBA basketball strategy is evolving.

Five essential management practices illustrated through the lens of sports analytics.

A webinar describing what companies need to effectively use AI and automation for operations.

Analytics can help NBA teams make better draft pick decisions.

Combining cutting-edge AI and MIT expertise, the Culture 500 provides a nuanced picture of corporate culture in the world’s top organizations.

Tim O’Brien explains his role as Microsoft’s first full-time manager for AI policy and ethics.

New competitors will require consumer packaged goods companies to engage directly with consumers.

Counterpoints looks at predicting the college football playoffs with UW-Madison’s Laura Albert.

MIT SMR‘s Summer 2019 issue takes a closer look at the cultural changes adopting AI may require.

A mental vacation is good for your powers of creativity.

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.