Leaders must deliver rapid AI innovation while handling many related people management challenges, ethical dilemmas, and security risks. One key is developing strong AI leadership skills while recognizing that human judgment remains essential. Get expert advice to help your team succeed with AI.
Organizational leaders can begin to address racial discrimination in the workplace by taking strategic actions.
Michael Schrage, coauthor of the recent MIT SMR-Deloitte report, “Opportunity Marketplaces,” explores how organizations can offer opportunities to their workforces.
A pharmaceutical giant enlists a consultant to help create an industry-leading global compliance system.
MIT Sloan’s Ben Shields says business can compete better using pro sports’ approach to data analytics.
Opportunity marketplaces sustain employment, reveal untapped worker capabilities, and motivate workers in new ways.
Ask these four questions to determine whether your AI system is really an AI solution.
How U.S. companies are commemorating Juneteenth; what a 2020 recession may mean for data analytics.
There has been a huge demand for data scientists in the past decade. Is that about to change?
Cognitive automation could help managers make better decisions more quickly in the wake of COVID-19.
Big data mining is no longer enough. Data exchanges will shape new economic ecosystems.
How to harness sensor data to generate new value and revenue for traditional products and services.
How businesses can act against racial injustice, and new leadership challenges in a suddenly virtual workplace.
It’s early in the age of experimentation — and the right time to start building expertise.
Understanding how cybersecurity and cyber resilience differ is key to effectively responding to cyberthreats.
Recalibrating metrics to assess work-from-home performance is essential to ensuring that remote work actually works.
Data-wrapping techniques, building diverse AI teams, and communicating with empathy and authority.
To launch successful products that delight customers, companies need a new approach to data analytics.
Computer scientists typically lead AI development, but teams with diverse expertise can build better systems.
This infographic highlights research findings on technology governance issues key to implementing trusted AI.
How to boost innovation capacity and institutional pride, and addressing tech inequity and the ethics of automation.
