杠杆(统计)
知识管理
过程(计算)
集合(抽象数据类型)
价值(数学)
人工智能
心理学
计算机科学
机器学习
程序设计语言
操作系统
作者
Jan Jöhnk,Malte Weißert,Katrin Wyrtki
标识
DOI:10.1007/s12599-020-00676-7
摘要
Abstract Artificial intelligence (AI) offers organizations much potential. Considering the manifold application areas, AI’s inherent complexity, and new organizational necessities, companies encounter pitfalls when adopting AI. An informed decision regarding an organization’s readiness increases the probability of successful AI adoption and is important to successfully leverage AI’s business value. Thus, companies need to assess whether their assets, capabilities, and commitment are ready for the individual AI adoption purpose. Research on AI readiness and AI adoption is still in its infancy. Consequently, researchers and practitioners lack guidance on the adoption of AI. The paper presents five categories of AI readiness factors and their illustrative actionable indicators. The AI readiness factors are deduced from an in-depth interview study with 25 AI experts and triangulated with both scientific and practitioner literature. Thus, the paper provides a sound set of organizational AI readiness factors, derives corresponding indicators for AI readiness assessments, and discusses the general implications for AI adoption. This is a first step toward conceptualizing relevant organizational AI readiness factors and guiding purposeful decisions in the entire AI adoption process for both research and practice.
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