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A new study from the MIT Sloan School of Management sheds light on a puzzling paradox: Despite AI’s growing accuracy and efficiency, people often prefer human decisions—even when AI performs better.
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Three steps to finding use cases for large language models: Break down workflows into tasks, consider all costs associated with automation, and launch pilots.
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The work tasks that AI is least likely to replace are those that depend on uniquely human capacities, such as empathy, judgment, ethics, and hope.
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Adversity can cultivate instincts that serve entrepreneurs well, says venture capitalist Noubar Afeyan. Here are his three tips to start innovating.
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Organizations have options when it comes to using or adapting off-the-shelf large language models to handle tasks or business use cases.
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While generative AI is widely accessible and useful, businesses need to know when to use other AI tools, like traditional machine learning.
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Finalists for the MIT Sloan 2025 CIO Leadership Award recommend agentic AI, pervasive innovation, and an executive focus on strategy.
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The U.S. is experiencing a crisis around job quality. Emerging climate jobs can give workers a living wage, health care, and safe working conditions.
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From assessing bridge infrastructure to predicting worker fatigue risk via voice analysis, these startups are widening the scope of what artificial intelligence can do.
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And why. Plus, an inclusive innovation scorecard.
