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    The great acceleration: CIO perspectives on generative AI

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    The great acceleration: CIO perspectives on generative AI
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    Although AI was acknowledged as strategically vital earlier than generative AI turned outstanding, our 2022 survey discovered CIOs’ ambitions restricted: whereas 94% of organizations had been utilizing AI ultimately, solely 14% had been aiming to attain “enterprise-wide” AI by 2025. By distinction, the ability of generative AI instruments to democratize AI—to unfold it by means of each perform of the enterprise, to assist each worker, and to interact each buyer —heralds an inflection level the place AI can develop from a expertise employed for specific use circumstances to at least one that really defines the trendy enterprise.

    As such, chief data officers and technical leaders should act decisively: embracing generative AI to grab its alternatives and keep away from ceding aggressive floor, whereas additionally making strategic selections about knowledge infrastructure, mannequin possession, workforce construction, and AI governance that can have long-term penalties for organizational success.
    This report explores the newest pondering of chief data officers at a few of the world’s largest and best-known firms, in addition to consultants from the general public, non-public, and tutorial sectors. It presents their ideas about AI in opposition to the backdrop of our international survey of 600 senior knowledge and expertise executives.

    Key findings embody the next:

    • A trove of unstructured and buried knowledge is now legible, unlocking enterprise worth. Previous AI initiatives needed to focus on use circumstances the place structured knowledge was prepared and plentiful; the complexity of amassing, annotating, and synthesizing heterogeneous datasets made wider AI initiatives unviable. By distinction, generative AI’s new capacity to floor and make the most of once-hidden knowledge will energy extraordinary new advances throughout the group.

    • The generative AI period requires an information infrastructure that’s versatile, scalable, and environment friendly. To energy these new initiatives, chief data officers and technical leads are embracing next-generation knowledge infrastructures. More superior approaches, resembling knowledge lakehouses, can democratize entry to knowledge and analytics, improve safety, and mix low-cost storage with high-performance querying.

    • Some organizations search to leverage open-source expertise to construct their very own LLMs, capitalizing on and defending their very own knowledge and IP. CIOs are already cognizant of the restrictions and dangers of third-party companies, together with the discharge of delicate intelligence and reliance on platforms they don’t management or have visibility into. They additionally see alternatives round growing custom-made LLMs and realizing worth from smaller fashions. The most profitable organizations will strike the suitable strategic steadiness primarily based on a cautious calculation of danger, comparative benefit, and governance.

    • Automation nervousness shouldn’t be ignored, however dystopian forecasts are overblown. Generative AI instruments can already full complicated and various workloads, however CIOs and teachers interviewed for this report don’t count on large-scale automation threats. Instead, they consider the broader workforce can be liberated from time-consuming work to focus on greater worth areas of perception, technique, and enterprise worth.

    • Unified and constant governance are the rails on which AI can pace ahead. Generative AI brings business and societal dangers, together with defending commercially delicate IP, copyright infringement, unreliable or unexplainable outcomes, and poisonous content material. To innovate shortly with out breaking issues or getting forward of regulatory adjustments, diligent CIOs should handle the distinctive governance challenges of generative AI, investing in expertise, processes, and institutional buildings.

    Download the complete report.

    This content material was produced by Insights, the customized content material arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial workers.

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