生成式人工智能将如何推动企业创新

Anthony Marshall, Christian Bieck, Jacob Dencik, Brian C. Goehring, Richard Warrick
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摘要

目的最近的大多数 C-suite 调查表明,尽管生成式人工智能被大肆宣传,但其目前的应用是零散的,不太可能产生预期的重大经济回报。相反,企业领导者希望通过将生成式人工智能应用于创新来实现生成式人工智能的主要价值:运营创新、产品和服务创新,以及最难以捉摸的商业模式创新。设计/方法/途径本文介绍的结论和分析借鉴了 IBM 商业价值研究院与牛津经济研究院合作在 2023 年期间对 C 级高管进行的多项调查数据。每项调查的重点都是生成式人工智能在特定业务领域的潜力。每项调查的N计数范围在100-3000之间。企业领导者预计,在传统人工智能投资回报的基础上,到2025年,生成式人工智能投资的RoI有望达到10%。2.2. 高管们预计,在为扩大创新而实施人工智能时,生成式人工智能将产生最大影响。3.为运营创新、产品创新和商业模式创新提供了具体实例。实际意义生成式人工智能的商业应用极为分散。社会影响为了减轻生成式人工智能的负面影响,关注创新潜力和价值最大化至关重要。原创性/价值本研究基于全新的调查和数据。本论文丰富了生成式人工智能领域的新知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How generative AI will drive enterprise innovation
Purpose Most recent C-suite surveying suggests current applications of generative AI, although hyped, are fragmented and unlikely to yield major financial returns anticipated. Instead, business leaders expect major value from generative AI will be achieved through application of generative AI to innovation: operational innovation, product and service innovation, and most elusive of all, business model innovation. Design/methodology/approach Findings and analysis presented draws on data from several surveys of C-level executives conducted by IBM Institute for Business Value in collaboration with Oxford Economics during 2023. Each survey focused on the potential of generative AI in a particular business area. The n-count of each survey ranged from 100-3000. Findings 1. Business leaders expect generative AI to build on returns achieved from investments in traditional AI, with 10 percent RoI expected on generative AI investments by 2025. 2. Executives anticipate that generative AI will have most impact when implemented to expand innovation. 3. Specific examples provided for operational innovation, product innovation, and business model innovation Research limitations/implications We are still very early in the generative AI development cycle. We have made best efforts to project, but only time will tell for sure. Practical implications Business application of generative AI are extremely fragmented. Despite the desire to throw investments at the wall to see what sticks, it is important that leaders take a structured approach to generative AI, focusing on RoI from innovation investments. Social implications To alleviate negative impacts of generative AI, focusing on innovation potential and value maximization is crucial. Originality/value This research is based on completely new surveying and data. This papers adds to the sum total of new knowledge in the generative AI domain.
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