Artificial Intelligence

MIT SMR’s fall 2024 issue highlights the need for personal and organizational resilience amid global uncertainty.

Digital nudges can encourage reactive thinking and limit employees’ ethical thinking.

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On the Me, Myself, and AI podcast, Wonder Dynamics’s cofounder discusses an AI tool that enables faster, more cost-effective animation.

Experts debate how effectively organizations are adjusting risk management practices to govern AI.

Business leaders can identify and avoid flawed AI models by employing statistical methods and statistics experts.

On the Me, Myself, and AI podcast, Stitch Fix’s Jeff Cooper explains how generative AI enables employees to gain more efficiencies while still connecting with customers.

New research shows where marketers are seeing gains from AI and how to speed up payoffs.

In the age of artificial intelligence, executives must make maintaining their AI literacy a habit.

On the Me, Myself, and AI podcast, Jackie Rocca explains how Slack uses artificial intelligence to relieve user pain points.

The nonprofit is delivering technology and services to help its staff build AI applications efficiently and safely.

To reduce the risk of accidentally using bad artificial intelligence, we need regulation — and skepticism.

Learn to drive digital transformation by turning business-domain experts into citizen developers.

On the Me, Myself, and AI podcast, Daniele Petecchi discusses how Pirelli uses AI to develop tires more efficiently.

MIT SMR wants to hear from you, our readers, to better understand your biggest challenges and help you meet them.

Analyzing factors behind generative AI’s value can help leaders determine who will benefit most from its growth.

To succeed with machine learning, manage projects as business initiatives, not technology projects.

LLMs have immense capabilities but present practical challenges that require human knowledge workers’ involvement.

This free webinar offers expert insights on effective data-management strategies for AI adoption.

When deciding whether to deploy a machine learning model, focus on business metrics, not technical ones.