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MIT Initiative on the Digital Economy
4 new studies about agentic AI from the MIT Initiative on the Digital Economy
New research ranges from how AI agents negotiate to how “personality pairing” can optimize human-AI collaboration.
Special Report
MIT Sloan insights for success in AI-driven organizations
Experts share innovative ideas for using artificial intelligence to solve critical business problems and deliver on strategy.
Teaching & Learning Resources
Generative AI for Teaching & Learning
Explore our resources to unlock AI's potential for enhancing teaching and learning at MIT Sloan.

Centers, Initiatives, and Programs

Positioned at the intersection of technology and management, the MIT Sloan School of Management is a meeting place for leading thinkers and researchers. The centers, initiatives, and programs at MIT Sloan and the larger MIT ecosystem drive research and education on artificial intelligence, its implications, and its uses.
MIT Center for Collective Intelligence
Center for Information Systems Research
Computer Science and AI Lab
Master of Business Analytics
Business Analytics Certificate
AI Executive Education

AI at MIT Sloan

Explore insights about artificial intelligence from MIT Sloan experts and learn how MIT Sloan students, alumni, and faculty are employing AI to build a better future.
Choose the human path for AI
To realize the greatest gains from artificial intelligence, we must make the future of work more human, not less.
Beyond the algorithm: AI’s societal impact
MIT Sloan research explores the promise and limits of using AI in medicine, hiring, and creative pursuits.

AI at Work Newsletter

Research and insights powering the intersection of AI and business, delivered to your inbox monthly.
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AI is reinventing hiring — with the same old biases. Here’s how to avoid that t…
The AI hiring revolution doesn’t have to be a story of automated bias, argues MIT Sloan’s Emilio J. Castilla. Tough questions and constant monitoring can lead to fairer systems.
How to spot real value in AI — and avoid the snake oil
A new book aims to help business leaders separate real AI value from overhyped claims.
How organizations build a culture of AI ethics
From risk management policies to the five stages of AI ethics, here’s how some organizations approach ethical AI.
Bringing transparency to the data used to train artificial intelligence
Using the wrong datasets to train artificial intelligence models can result in legal risks, bias, or lower-quality models. The Data Provenance Initiative’s tool can help.
Media: Bloomberg
MIT Harnesses AI to Accelerate Startup Ambitions
Paul Cheek, executive director of the Martin Trust Center for MIT Entrepreneurship said: "Our mission at the Trust Center is to advance the field of innovation-driven entrepreneurship everywhere. We can't do it with intuition or by throwing stuff against the wall. We have to practice entrepreneurship in a rigorous, systematic way that increases the odds of success."
Managers and workers need to collectively develop new expectations and work practices to ensure that any work done in collaboration with generative AI meets the values, goals, and standards of their key stakeholders.
Kate Kellogg

David J. McGrath jr (1959) Professor of Management and Innovation
I've gained deep insights into cutting-edge technologies and had the chance to connect and network with industry leaders ... [T]aking courses or working on projects related to deep learning has been a rewarding experience.
Anne Castille Buisson

MBAn ’24
This technology’s deepest impact on the world of work will come as it’s used to reimagine entire organizations. This deep reimagination will be a decentralized and distributed phenomenon, carried out by innovators and entrepreneurs.
Andrew McAfee

Co-Director, MIT IDE & Principal Research Scientist, MIT Sloan
You need to be talking about AI along with specific initiatives and the outcomes you want to achieve using it. And those outcomes need to be compelling for your organization.
Barbara Wixom

Principal research scientist at the MIT Center for Information Systems Research
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Working Definitions: Artificial Intelligence

MIT Sloan's Working Definitions explore the words and phrases behind emerging management ideas.
jagged AI frontier
pro-worker AI
BYOAI
secure-by-design AI
algorithmic aversion
power capping
Year In Review

Bridging Real Estate and Data Science

By Tracey Palmer

A team of students in MIT Sloan Action Learning’s Real Estate Lab (RE-Lab) developed a predictive model for a leading global commercial real estate and investment management firm.

May 20, 2026
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Year In Review

A Spotlight on AI at Demo Day

By Haley Bierman

The Martin Trust Center for MIT Entrepreneurship highlighted 22 innovative startups at its September 2025 Demo Day, with many leveraging AI in their products and entrepreneurial processes.

May 20, 2026
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