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MIT Sloan’s Paul Osterman argues that the rise in gig workers, freelancers, contractors, adjuncts, and other contingent workers carries long-term implications for the future of work.

A new research briefing explains how semantic layers make enterprise data more accessible and understandable by humans and machines.

AI performance is improving across many workplace tasks broadly, not in sudden shocks, new MIT research finds. That cadence gives companies and workers time to prepare for task-level displacements.

Few AI pilots scale successfully. Asking key questions about goals, governance, and culture can help them thrive.

AIDEs have lower overhead, are extremely efficient at product development, require a smaller footprint, and provide increased ownership for founders, according to MIT Sloan’s Paul Cheek.

As AI systems become more capable, companies will need to think beyond individual tools and begin managing AI as a digital colleague — part of how teams, workflows, and business processes operate.

Large language models encourage smart financial behavior, but they fall short on the more subtle aspects of saving and investing, according to MIT Sloan’s Taha Choukhmane and co-authors.

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.