The integration of Artificial Intelligence (AI) into corporate strategy has become critical for organizations seeking to maintain competitive advantage in the digital age. Although organizations increasingly rely on AI as a strategic and organizational resource, existing C-suite roles remain only partially equipped to govern, integrate, and leverage it coherently at the enterprise level. Organizations vary in their responses. Some create a dedicated Chief AI Officer (CAIO), others extend existing mandates into hybrid roles, and still others coordinate AI through federated structures. This paper develops a role-design theory to explain this variation. I identify three properties that distinguish AI from earlier cross-cutting enterprise technologies - distributed accountability for judgment, upstream governance, and non-stationarity - and three configurations through which organizations respond: concentrated extension, distributed extension, and role creation. The CAIO Framework links these properties to the executive design problems they generate and to the functions and capabilities required of the dedicated role. Four propositions specify when a dedicated CAIO emerges, what form an organization's response takes, when the dedicated role is effective, and how configurations evolve over time. This paper contributes to research on executive leadership, organizational design, and digital governance by offering a theory-driven account of the strategic integration of AI at the executive level.

翻译：人工智能在公司战略中的整合已成为组织在数字时代保持竞争优势的关键。尽管组织日益依赖人工智能作为战略和组织资源，但现有的C-Suite角色在治理、整合以及在企业层面协调运用人工智能方面仍存在局限性。各组织的应对方式不尽相同：有些设立专职首席AI官（CAIO），有些将现有职责扩展为混合角色，还有些通过联邦式结构协调人工智能工作。本文构建了角色设计理论以解释这种差异。我识别出人工智能与早期跨领域企业技术相区别的三个特性——判断责任的分布式分配、上游治理与非平稳性——以及组织应对的三种配置：集中式扩展、分布式扩展和角色创建。CAIO框架将这些特性与其产生的行政设计问题、以及专职角色所需的功能和能力联系起来。四项命题分别阐述了专职CAIO出现的条件、组织应对形式、专职角色的有效性以及配置随时间的演变方式。本文通过提供关于人工智能在高层战略整合的理论驱动论述，为高管领导力、组织设计和数字治理研究做出了贡献。