AI & Machine Learning
GenAI Tools and Decision-Making: Beware a New Control Trap
Consider these three takeaways for leaders on how to avoid pitfalls while using generative AI tools in decision-making.
Generative AI
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Data & Data Culture
Sharing AI Mistakes: Partnership on AI’s Rebecca Finlay
On this Me, Myself, and AI podcast episode, the nonprofit’s CEO argues for more transparency when companies err with AI.
Skills & Learning
Learning to Manage Uncertainty, With AI
The second Artificial Intelligence and Business Strategy report of 2024 looks at how organizations that combine organizational learning and AI learning are better prepared to manage uncertainty.
AI & Machine Learning
A Practical Guide to Gaining Value From LLMs
Applying a comprehensive cost-benefit analysis to generative AI use cases will highlight where the technology pays off.
Performance Management
Intelligent Choices Reshape Decision-Making and Productivity
Research shows that better decision-making can be achieved through the strategic use of artificial intelligence systems.
AI & Machine Learning
The Risks of Too Much AI: Fortune’s Jeremy Kahn
On the Me, Myself, and AI podcast, journalist Jeremy Kahn discusses the risks of an overreliance on AI technologies.
AI & Machine Learning
Bring Your Own AI: How to Balance Risks and Innovation
Learn how to transform employees’ use of publicly available GenAI tools at work from organizational liability to asset.
Content Sponsored by ThoughtSpot
Generative AI for Data and Analytics: How Early Adopters Are Reaping the Rewards
Survey report: What 1,000 business and data leaders think about using generative AI for analytics.
AI & Machine Learning
Reality Check: Generative AI’s Impact on Work
Research finds that the adoption of generative AI tools across industries has been slower than many people anticipated.
New Product Development
When Generative AI Meets Product Development
Image- and text-generation tools are helping innovation groups improve ideation and creativity and gain market insights.
Developing Strategy
Our Guide to the Summer 2024 Issue
This issue of MIT SMR focuses on analytics, the challenges of advancing artificial intelligence, and business strategy.
Technology Implementation
Auditing Algorithmic Risk
Two frameworks can help organizations identify potential harms posed by algorithms, AI tools, or large language models.
AI & Machine Learning
Three Things to Know About Prompting LLMs
Apply these techniques when crafting prompts for large language models to elicit more relevant responses.
AI & Machine Learning
Nudge Users to Catch Generative AI Errors
Prompting users to spot errors when using generative AI to complete reports improves the accuracy of the final product.
New Product Development
If 10% of the World Were Developers: GitHub’s Mario Rodriguez
On the Me, Myself, and AI podcast, GitHub’s Mario Rodriguez discusses AI’s potential to change the future of coding.
AI & Machine Learning
Reinventing the Organization for GenAI and LLMs
Learn three principles for reorganizing work around AI.
AI & Machine Learning
In AI We Trust — Too Much?
To reduce the risk of accidentally using bad artificial intelligence, we need regulation — and skepticism.
Innovation Strategy
Our Guide to the Spring 2024 Issue
The spring 2024 issue of MIT SMR looks at opportunities in digital innovation, automation, generative AI, and more.
AI & Machine Learning
Who Profits the Most From Generative AI?
Analyzing factors behind generative AI’s value can help leaders determine who will benefit most from its growth.
AI & Machine Learning
What AI Means for Human Capital
Many organizations are experimenting with generative AI, and many questions remain about its impact on the workforce.
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