AI implementation strategies from MIT Sloan Management Review
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Value creation is the true measure of successful AI implementation. It starts at proof of concept and considers AI’s impact on an industry, not just a company.
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Value creation is the true measure of successful AI implementation. It starts at proof of concept and considers AI’s impact on an industry, not just a company.
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The AI Risk Repository, a database of over 700 risks posed by AI, aims to provide a shared framework for monitoring and maintaining AI risk oversight.
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Fintech — technology for financial services — encompasses lending, payments, investing, insurance, property management, risk assessment, and more.
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A McKinsey expert shares insights on what it takes to turn generative AI’s promise into tangible business value.
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Counterterrorism expert Humera Khan harnesses diverse perspectives to anticipate and prevent violent extremism via her think tank, Muflehun.
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Experts say those making decisions about AI should engage proactively with policymakers and consider worker voice and well-being.
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Generative AI can boost highly skilled worker productivity, if organizations establish a culture of accountability and encourage role reconfiguration.
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Plus, a new series on developing a healthy corporate culture.
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The delta v 2018 Demo Day highlighted some of the most creative and promising startup ideas coming out of MIT.
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Dimitris Bertsimas and Nikolaos Trichakis modeled a points-based framework called continuous distribution (CD) based on AI and machine learning to aid in allocating lung transplants.