Here’s what businesses need to know as AI agents move from centralized systems toward a decentralized network of trillions of personal and organizational agents.
Which AI risks could cause the most harm in the next five years? New MIT research shows that businesses should be aware of threats like competitive pressure and dangerous AI capabilities.
McKersie’s 1965 framework for labor bargaining became one of negotiation theory’s most enduring ideas — and helped guide a life of activism, mentorship, and academic leadership.
Enterprises looking to make the most of agentic AI will have to rethink how work gets done and how teams are organized, without forgetting the human workers who set their companies apart.
Here’s what businesses need to know as AI agents move from centralized systems toward a decentralized network of trillions of personal and organizational agents.
Transformative technologies like artificial intelligence succeed when societies make parallel social investments to ensure gains are distributed equitably, MIT Sloan researchers find.
Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the new experts bringing their knowledge and skill sets to the MIT Sloan School of Management.
Three levers — data architecture, data preparation, and data permissions — determine whether data becomes a reusable strategic asset or stays trapped in silos.
Freelancers, contractors, part-timers, gig workers, adjuncts, and other contingent workers deserve more respect, MIT Sloan professor emeritus Paul Osterman writes in his book “Disposable Workers.”
