MIT Sloan

PPaint/Ikon Images Balancing the daily grind of operations with the spark of innovation is one of the most persistent challenges managers face.1 Regulatory compliance, performance metrics, and the never-ending demands of customers can easily crowd out creative thinking. Work overload or mismanaged operations elevate employee stress, which directly constrains ideation capacity. This cognitive bottleneck triggers

Carolyn Geason-Beissel/MIT SMR | Getty Images As multinational companies implement artificial intelligence workflows and look to adopt AI across their global operations, they are increasingly running up against country-specific regulations and policies that aim to govern AI and align its use with national priorities and local cultural norms. These regulations and policies — which fall

Michael Glenwood Gibbs/theispot.com Digital platforms and generative AI have lowered the barriers to accessing global talent, capital, and knowledge for companies everywhere while making it possible to reach customers across languages and cultures. Research my colleagues and I have conducted suggests that such tools make it easier for entrepreneurs to serve global markets and for

Carolyn Geason-Beissel/MIT SMR | Getty Images To understand their customers and markets, a growing number of customer-oriented companies are using generative AI tools, alongside the language and reasoning capabilities of popular large language models (LLMs), to access and analyze their own internal content. These hybrid knowledge approaches, which typically employ a technique called retrieval-augmented generation

Chris Gash/theispot.com The Research The authors synthesized findings from four studies spanning short-story writing, circular-economy solutions, humor caption contests, and collaborative storytelling. Across all four studies, AI assistance improved individual output quality, but it reduced collective diversity, resulting in more similar, convergent ideas across groups. AI had the greatest positive effect on individuals with lower

Matt Harrison Clough / Ikon Images The Research The authors performed a four-year, fixed-window observational analysis of administrative work inside a large U.S. public higher-education institution. Generative AI tools were introduced to executive leaders, operational leaders, and student-facing professionals throughout the organization in 2026. Staffing levels and work hours remained stable across the period studied.

Carolyn Geason-Beissel/MIT SMR | Getty Images In 1951, philosopher Martin Heidegger told a small audience, “The most thought-provoking thing in our thought-provoking time is that we are still not thinking.” Few understood him then. Seventy-five years later, the observation has become unavoidable because AI has forced every leader to confront a question about the nature

Carolyn Geason-Beissel/MIT SMR | Getty Images Leaders at literally every Fortune 500 company will tell you that they are governing their AI — every single one of them. Now ask those same leaders who’s responsible for shutting down an AI model that’s causing harm. Most people can’t answer that question. That silence is the most

Patrick George/Ikon Images What would you do with artificial intelligence if you were confident that it would transform your industry? What actions would you take if you felt that you were at an inflection point in that transformation? Would you try to be an early proponent of AI-first in your industry, or a fast follower?

Matt Kenyon/Ikon Images “Professionalism” encompasses the broad set of shared beliefs and expectations about how people within an industry or workplace should interact with one another: Think communication style, punctuality, or meeting etiquette. But opinions differ: Cameras on? Cameras off? Do meetings start precisely on the hour? Is arriving a few minutes late acceptable or