Paper Number

ECIS2026-1054

Paper Type

CRP

Abstract

We analyzed how eight organizations seek to govern Generative Artificial Intelligence (GenAI). We identified five key governance roles (i.e., technology owner, business owner, knowledge owner, risk and compliance, and end user). Moreover, we showcase that each role controls different resources that become critical at different lifecycle stages. Specifically, we demonstrate that the focal power dependence relation moves away from “the business depends on engineers to build AI” toward “engineers depend on knowledge owners, risk and compliance, and end users to steer AI.” We further showcase three organizational coordination mechanisms (i.e., AI Business Unit, AI Squads, and AI Spine) and their respective effectiveness in managing evolving power-dependence relationships in an AI governance context.

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Jun 14th, 12:00 AM

Generative Artificial Intelligence Governance: A Structural Practice Perspective

We analyzed how eight organizations seek to govern Generative Artificial Intelligence (GenAI). We identified five key governance roles (i.e., technology owner, business owner, knowledge owner, risk and compliance, and end user). Moreover, we showcase that each role controls different resources that become critical at different lifecycle stages. Specifically, we demonstrate that the focal power dependence relation moves away from “the business depends on engineers to build AI” toward “engineers depend on knowledge owners, risk and compliance, and end users to steer AI.” We further showcase three organizational coordination mechanisms (i.e., AI Business Unit, AI Squads, and AI Spine) and their respective effectiveness in managing evolving power-dependence relationships in an AI governance context.

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