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    Separating AI myths from business reality isn’t always easy. Explore 12 examples of how organizations are creating very real business value with artificial intelligence.
    How to create business value with AI
    Separating AI myths from business reality isn’t always easy. Explore 12 examples of how organizations are creating very real business value with artificial intelligence.

    It’s easy to get caught up in the artificial intelligence (AI) hype. But when industries or business leaders do, it creates AI myths that some executives base decisions on—big decisions. Instead of making wise, data-based moves based on what AI can actually do for business, they make decisions based on potential they might not be set up to reach—yet.

    Getting it right—now—matters because business and society are rapidly adopting AI. Early in the pandemic, 84% of all organizations expected to maintain or increase the level of organizational focus on AI, with nearly a third boosting their AI investments as a direct result of the pandemic.

    For some innovative AI adopters, AI helps create entirely new business models. Few enterprises, however, are using it for such broad transformation yet.

    A peek behind the AI curtain

    To help separate myth from reality, the IBM Institute for Business Value (IBV), in collaboration with the MIT-IBM Watson AI Lab, interviewed individuals involved in deep-learning projects from more than 35 real-life artificial intelligence (AI) implementations around the globe. We talked to business and technology experts from more than a dozen industries about their AI goals, challenges, and learnings.

    What did we learn about AI business value?

    AI uptake continues to increase, but most organizations are not yet using it fully for broad transformation. Instead, many are just addressing discrete business challenges. By the end of 2022, we estimate that just one out of four large companies will have moved beyond pilots to operational AI.

    Some companies are still basing AI decisions on a few myths, rather than AI reality. “AI shortcuts don’t work.” Oh, but they do. “If it isn’t deep learning, it isn’t AI.” Not so. Part of AI’s power lies in its many variations. Fit for purpose matters.

    In this piece, we pull back the curtain on five artificial intelligence myths, revealing through data and real-world examples the truth about how companies are using AI, so business leaders and teams can learn from their peers.

    Five common AI myths

    Five common AI myths

    Transformation depends on reality, not perception

    The transformative value of AI—through its financial, economic, and societal impacts—can only become reality if leaders of more traditional enterprises fully grasp the opportunities for innovation strategically, thoughtfully, and concretely. A critical starting point is to separate perception from the emerging reality of AI.

    To distinguish AI realities versus the myths, download our report. You’ll learn how a consumer goods company used AI to supplement the experience of junior food scientists to help them perform at the level of a senior scientist with 20 years of expertise. You’ll discover how AI is being used to battle malaria, and how an insurance company dropped settlement costs by 40% using artificial intelligence. And that’s just the beginning.


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    Meet the authors

    Nicholas Borge

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    , Researcher, FutureTech, MIT Computer Science and AI Lab


    Subhro Das, PhD

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    , Research Staff Member, MIT-IBM Watson AI Lab


    Martin Fleming, PhD

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    , Chief Revenue Scientist, Varicent


    Brian Goehring

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    , Associate Partner and Global AI Research Lead, IBM Institute for Business Value


    Neil Thompson, PhD

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    , Director, FutureTech, MIT Computer Science and AI Lab

    Download report translations


      Originally published 12 August 2022

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