MIT Sloan Management Review

MIT Sloan Management Review leads the discourse among academic researchers, business executives and other influential thought leaders about advances in management practice, particularly those shaped by technology, that are transforming how people lead and innovate. MIT SMR disseminates new management research and innovative ideas so that thoughtful executives can capitalize on the opportunities generated by rapid organizational, technological and societal change.

Know Your Own Strength

MIT Sloan Management Review

The Long Tail of Social Media Influence

MIT SMR READS

How Long for AI to Pay Off?

PROMPTING LLMs

The Most Entrepreneurial States in the U.S.

Keeping Innovation Alive at a Legacy Organization

The Hazards of Putting Ethics on Autopilot • Research shows that employees who are steered by digital nudges may lose some ethical competency. That has implications for how we use the new generation of AI assistants.

Why Companies Need to Lobby for Climate Policy • Organizations that want to make real progress on sustainability need to build a business case for climate lobbying.

Tap Employee-Creators to Transform Your Social Media Strategy • Businesses that help employees become social media stars have a cost-effective way to generate enormous brand visibility.

How AI Skews Our Sense of Responsibility • Research shows how using an AI-augmented system may affect humans’ perception of their own agency and responsibility.

To Navigate Conflict, Prioritize Dignity • Four interrelated practices can bolster dignity, leading to more constructive problem-solving and collaboration.

Nudge Users to Catch Generative AI Errors • Using large language models to generate text can save time but often results in unpredictable errors. Prompting users to review outputs can improve their quality.

Why Territorial Managers Stifle Innovation — and What to Do About It

Smart leaders read smart books

Overcoming the Hard Problems to Advance AI Practice

Auditing Algorithmic Risk • How do we know whether algorithmic systems are working as intended? A set of simple frameworks can help even nontechnical organizations check the functioning of their AI tools.

Avoid ML Failures by Asking the Right Questions • Machine learning solutions can miss the mark when data scientists don’t check their assumptions. Adopting a beginner’s mindset in any domain can help.

How Generative AI Can Support Advanced Analytics Practice • Large language models can enhance data and analytics work by helping humans prepare data, improve models, and understand results.

Managing Data Privacy Risk in Advanced Analytics • Cybersecurity techniques that keep personal data safe can limit its use for analytics — but data scientists, data owners, and IT can partner more closely to find middle ground.

Acing Value-Based Sales • To get the best returns on innovative products, collaborate with customers to define and share the commercial opportunity.

Find a Circular Strategy to Fit Your Business Model • Products and services that maximize use and reuse of materials and other resources can be both growth opportunities and sustainability measures.

How to Come Back Stronger From Organizational Trauma • Traumatic events are destabilizing. In their aftermath, leaders can help individuals and teams recover and grow.

Engineer Your Own Luck • Companies that modularize and externalize their best capabilities are in a strong position to seize unexpected opportunities.

Serve More Customers With Inclusive Product Design • Use these questions to empower teams to design products for more diverse populations.

The CEO’s Cyber Resilience Playbook • What do CEOs who led through a serious...