What drives the corporate payoffs of using generative artificial intelligence?

被引:0
|
作者
Bughin, Jacques [1 ]
机构
[1] Free Univ Brussels, Solvay Brussels Sch Econ & Management, Brussels, Belgium
关键词
AI; Generative AI; Productivity impact; Capabilities; Entropy; INFORMATION-TECHNOLOGY; COMPETITIVE ADVANTAGE; DYNAMIC CAPABILITIES; FIRM PERFORMANCE; PRODUCTIVITY; AI; TRANSFORMATION; DIFFUSION; RESOURCES;
D O I
10.1016/j.strueco.2024.09.011
中图分类号
F [经济];
学科分类号
02 ;
摘要
Artificial Intelligence, a set of technologies that aim to replicate human cognitive functions, has seen remarkable improvements over the last decade. In particular, generative AI (GenAI), a subset of AI able to generate content tasks based on Large Language Models (LLM), has recently gained momentum. Based on an extensive analysis of generative AI use cases in large enterprises, we find that Gen AI shows strong labor productivity improvements across metrics such as throughput time, unit cost, and task effectiveness. However, the distribution of gains is asymmetric in favor of a few companies. While the current distribution of gains does not provide evidence of a power law effect, the current asymmetry reflects differences in AI resources/capabilities across companies mainly data access, AI talent, or AI governance.
引用
收藏
页码:658 / 668
页数:11
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