MIT斯隆管理学院

In his new book, MIT Sloan entrepreneur Paul Cheek argues that managerial hierarchies are holding companies back — an inefficiency that artificial intelligence can help streamline.Knowledge workers in 2026 are grappling with what MIT Sloan School of Management senior lecturer Paul Cheek calls a “split-screen reality.” On one side are the “AI-abled elite” who can move quickly, free from the administrative burdens of legacy organizations. On t

What you’ll learn: As AI shrinks the cost and time required to research markets, build products, and test hypotheses, founders should focus on reaching and retaining paying customers. AI can make go-to-market strategies far more precise by identifying new customers, burgeoning trends, and emerging warning signs.In an AI-enabled startup, humans should act as future-forward architects, supplying the judgment, relationships, creativity, an

What you’ll learn: Giving people the opportunity to trade energy stocks increased their support for government and business actions to counter climate change.Study participants who used a stock-trading module for six weeks improved their financial literacy and their knowledge of companies’ environmental impact.Investing on a small scale — as little as $50 — was enough to prompt participants to shift their news consumption away from Fox News

What you need to know:  Organizations that succeed in the 21st century are agile and innovate quickly. According to MIT Sloan’s Andrew McAfee, the future of tech-driven companies is young U.S. firms on the West Coast. About a decade ago, MIT Sloan School of Management principal research scientistAndrew McAfeebumped into venture capitalist Steve Jurvetson at a conference and asked, “What’s new?” Jurvetson, known for early-stage

What you’ll learn: Enterprises must address complex ethical issues surrounding AI or risk exposure to myriad financial, legal, and reputational risks.A framework called Boundaries of Tolerance includes a set of performance measures to help organizations assess their position on the AI ethics maturity spectrum.Organizations should strive to go beyond minimum compliance requirements and continuously adapt AI systems to evolving risks and uncer

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.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. McKersie’s landmark 196

What you need to know: Enterprises looking to make the most of agentic AI must rethink how work gets done and how teams are organized, without forgetting the human workers who set their companies apart.  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 lecturerPaul Cheeksaid.“Emer

What you’ll learn:AI agents are moving from centralized systems toward a decentralized network of trillions of personal and organizational agents.The real business opportunity isn’t building agents for specific tasks — it’s building the marketplaces, protocols, and services that agents will need.A new MIT research initiative called Project NANDA is working to keep the agentic web open before corporate consolidation makes that impossible.MIT’s Ram

What you’ll learn:The success of transformative new technologies depends on parallel investments in capital, human development, metrics, systems thinking, and social and economic institutions.  As AI advances, governments and societies have a responsibility to shape how these system-level complements emerge so that AI’s gains are distributed equitably.Amid the transformative promise of artificial intelligence, one significant question is “Wi

These new MIT Sloan School of Management faculty members are experts in workplace instability, microfinance, human-AI interaction, digital economics, and more.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 StudiesComes from: Harvard, where

What you’ll learn: When workers become overreliant on AI, there’s a risk of significant skills collapse.Workers may fall victim to “AI gravity” — the constant pressure to outsource more thinking to AI in order to become more efficient.Individuals and organizations can take specific actions to protect cognitive capital and preserve institutional knowledge, says MIT Sloan School of Management professor Eric So. As businesses pull out all

Pope Leo XIV’s first encyclical, “Magnifica Humanitas: On Safeguarding the Human Person in the Time of Artificial Intelligence,” could not come at a more opportune time. His call to respect workers’ right to a voice in shaping the future of work builds on Pope Leo XIII’s historic 1891 encyclical “Rerum Novarum” and subsequent Catholic social teachings.“Rerum Novarum,” which championed workers’ rights and unions, was the moral foundation for progr

Credit: peshkov / iStockPeter Hirst, the senior associate dean for MIT Sloan Executive Education, has unique insight into how leaders are thinking about artificial intelligence. Themes include: Technology shouldn’t overshadow humans. Having a basic understanding of AI is important, but leaders should focus on how it affects organizations, systems, and people. AI changes the relationship between IT and the C-suite. Top leaders are drivin

Credit: Summit Art Creations / ShutterstockWhat you’ll learn: Most organizations struggle to move from AI experimentation to seeing a return on their investments. Work from the MIT Center for Information Systems Research shows five common AI mistakes, such as mistaking productivity gains for strategic business value, and how you can overcome them.Few organizations have successfully parlayed artificial intelligence experimentation into large-scale

What you’ll learn: A new paper from researchers at the MIT Sloan School of Management argues that AI’s biggest impact comes from how it reshapes entire workflows — specifically, how tasks are sequenced, grouped, and handed off between humans and machines. Most organizations have approached artificial intelligence as a tool for boosting productivity at individual tasks, such as drafting emails, summarizing documents, or generating code.

What you’ll learn: AI should be treated as an operating system, not a toolkit, to generate measurable business impact. Job role is no longer the right unit of work analysis after AI adoption; organizations need to redesign work task by task. Closing the “last mile” gap between AI’s potential and real-world impact requires new metrics, user involvement, and a test-and-scale mindset.As organizations deploy artificial intelligence mor

What you’ll learn: Developers with access to GitHub Copilot increased the proportion of their time spent on core coding by 12.4% while cutting the proportion of their time spent on project management tasks by 24.9%.Junior developers saw the biggest impact from AI assistance, which makes a case against replacing entry-level workers with AI.As AI shortens the learning curve, employers must ensure that workers are using it to learn rather than

Closed AI models are proprietary systems that keep their code confidential. Open models make public one or more model details. A new paper found: Users largely opt for closed models, which account for about 80% of model usage.Open models achieve about 90% of the performance of closed models at the time of release but quickly make up the difference.Closed models cost users, on average, six times as much as open ones.Optimal reallocation of de

What you’ll learn about establishing pro-worker artificial intelligence:Build domain-specific, reliable AI systems.Design AI that supports skill development.Use interaction techniques to reduce blind reliance on AI.Adopt adaptive decision-support systems.Recognize that pro-worker AI requires deliberate design and policy intervention.Imagine an electrician equipped with an artificial intelligence tool that can spot edge-case failures, surface insi

Nine of the 10 articles on our list of the past year’s top articles focus on how AI is changing work and how we work, from the macro — predictions about how AI will affect the U.S. economy in the next decade — to more specific guidance about when to use machine learning, when to use generative AI, and when the two pair well together.