MIT Sloan Ideas Made to Matter

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. 8 minute read Robert B. McKersie, a professor emeritus at the MIT Sloan School of Management whose pioneering research on collective bargaining and negotiations is widely credited with shaping the field of industrial relations, died July 11 at the age of 96.

When it comes to creating an AI-driven organization, enterprise leaders may feel like they’re steering a cruise ship while startups are navigating around them in kayaks, MIT Sloan School of Management senior lecturer said. “Emerging firms can start and scale faster than we’ve ever seen before,” he said.

MIT’s Ramesh Raskar offers a compelling vision of the future. Suppose a 70-year-old pre-diabetic woman from rural India wants to attend a festival in a nearby city. She tells this to her AI agent — every person in this future has a personal AI agent — and it gets to work. It finds and purchases her train ticket; it negotiates the best rate on a hotel within walking distance of a health clinic; and it establishes a menu sensitive to her medical condition.

Amid the transformative promise of artificial intelligence, one significant question is “Will AI enhance welfare for all or generate wealth for just a few?” Studying the rollout of other general-purpose technologies, such as the automobile and the internet, is helpful in the quest for an answer. This wave of AI is nascent. We can still decide how to deploy it in society so that it brings welfare to many.

Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the seven new experts bringing their knowledge and skill sets to the MIT Sloan School of Management. Clem Aeppli, Assistant Professor of Work and Organization Studies Comes from: Harvard, where he received a PhD in sociology in 2026. Research: Aeppli uses quantitative approaches to understand how broad transformations in the organization of work shape inequality and instability.

As the United States marks its 250th anniversary, it’s worth looking beyond familiar milestones to the business ideas that fundamentally reshaped how we work, build, and innovate. We asked MIT Sloan School of Management faculty members to identify the concepts, moments, and systems that have had the greatest impact on business and society — from the rise of entrepreneurial ecosystems and new models of leadership to the frameworks that still govern work and wages today.

The rapid rise of artificial intelligence has put data back at the center of corporate strategy. Many organizations, however, are discovering that deploying advanced analytics or AI tools doesn’t automatically translate into better decisions or business results. What separates leaders from laggards is not how much data they collect or how sophisticated their models are — it’s how easily data can be reused, combined, and put to work across the enterprise.

Flexibility is a defining feature of the modern workforce. But, according to the MIT Sloan School of Management’s that flexibility can come at a cost. In his forthcoming book, “Disposable Workers: The Transformation of Employment,”Osterman, an emeritus professor of human resources and management, argues that a profound shift is reshaping employment culture at the expense of a large swath of the U.S. workforce.

A data center technician’s job involves more than just inspecting equipment or responding to alarms. Today, they have to interpret streams of operational data, spot early signs of risk, and make decisions across systems. And with the support of artificial intelligence — surfacing relevant information, flagging potential hazards, and guiding next steps in real time — they can take on more complex tasks with greater confidence.

This article was adapted from the May 2026 edition of the MIT Sloan School of Management’s monthly AI at Work newsletter. Sign up for AI at Work here. For a while, the conversation about generative AI — and then AI agents — was largely speculative. What might it do to our day-to-day work, our workplaces, our careers, and the economy? Artificial intelligence was like a new coworker, and we were anticipating its arrival. Now our AI coworkers have arrived in most workplaces and sectors.