管理生成式人工智能在下一代商业中的新兴作用

Jacob Dencik, Brian Goehring, Anthony Marshall
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引用次数: 0

摘要

自2022年11月OpenAI发布ChatGPT以来,由于其能够创建引人注目的相关内容和新的大型语言模型(LLM)技术,商业领袖,尤其是首席执行官,正面临加速新生成人工智能投资的压力。IBM IBV对高管进行了调查,以评估他们的进展和关注点,以及他们的采用策略。生成式人工智能的选择仍处于非常早期的阶段。大多数组织才刚刚开始弄清楚如何以及在哪里利用它。事实上,在IBM商业价值研究院(IBM Institute for Business Value)进行的一项新调查中,只有6%的高管表示,他们目前正在企业中使用生成式人工智能。与许多人对人工智能的期望相反,对于希望利用生成式人工智能来增加商业价值的高管来说,任务自动化并不是他们的首要任务。通过功能、研究和创新来看待收益是组织看到生成式人工智能机会的主要领域。sibm IBV最近对高管的调查发现,有效部署和使用生成式人工智能的主要障碍与安全、隐私、道德、法规和经济有关,而不是获得底层技术本身。原创性/价值组织将不得不评估其企业中哪些地方的潜在收益和成本效率超过了使用生成式人工智能可能出现的错误或意外后果的风险,以及更广泛的道德考虑。生态系统扩大了生成人工智能的机会,以利用来自合作伙伴和利益相关者的数据、见解和技术能力,同时实现对组织价值主张最核心的能力的控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Managing the emerging role of generative AI in next-generation business
Purpose Since the release of ChatGPT by OpenAI in November 2022 – with its ability to create compelling, relevant content, new large language model (LLM) technology – business leaders, especially CEOs, are being pressured to accelerate new generative AI investments. IBM IBV surveyed executives to assess their progress and concerns and their adoption strategies. Design/methodology/approach Adoption of generative AI is still in its very early stages. Most organizations are only beginning to figure out how and where to make use of it. In fact, as few as 6 percent of executives in new surveying conducted by the IBM Institute for Business Value say they are operating generative AI in their enterprise today. Findings In contrast to many peoples’ expectations about AI, automating tasks is not the top priority for executives looking to tap generative AI to grow business value. Looking at benefits by function, research and innovation is the primary area where organizations see opportunities for generative AI. Practical implications IBM IBV's recent survey of executives found that the key barriers to the effective deployment and use of generative AI are linked to security, privacy, ethics, regulations and economics – not access to the underlying technology itself. Originality/value Organizations will have to evaluate where in their enterprise the potential gains and cost efficiencies outweigh the risks of possible errors or unintended consequences from the use of generative AI along with broader ethical considerations. Ecosystems expand generative AI opportunities to harness data, insights and technology capabilities from across partners and stakeholders while enabling control over the capabilities that are most central to an organization’s value proposition.
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