aiqbench analysis
This research proposes a theoretical framework for the Chief AI Officer role, distinguishing AI from prior technologies through unique properties like distributed accountability and non-stationarity. It outlines specific organizational configurations—ranging from dedicated roles to federated structures—and defines the conditions under which each approach effectively governs enterprise-level AI integration. The findings offer a structured lens for executives evaluating whether to create new C-suite positions or adapt existing mandates to handle AI's distinct governance challenges.
Strategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer
arXiv:2407.10247v3 Announce Type: replace-cross Abstract: 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.
Abstract: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.
Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); General Economics (econ.GN)
arXiv:2407.10247 [cs.CY]
(or arXiv:2407.10247v3 [cs.CY] for this version)
Full text under the publisher's open licence · 226 words
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