Return on AI (RoAI): A framework for assessing AI investments in the marketing organization

Abstract

Artificial intelligence (AI) is reshaping marketing as firms increasingly delegate activities and decisions previously performed by marketers to AI systems. As AI assumes a greater role in market-facing decisions, understanding the value firms realize from these investments becomes increasingly important. Building on marketing accountability and resource-based theory, we develop a Return on AI (RoAI) framework that conceptualizes AI investment through the people, processes, and capabilities that enable its deployment and governance. RoAI evaluates incremental benefit while accounting for value retention, evidence durability, and the full costs of deployment over time. The framework identifies a distinctive consequence of delegated judgment, wherein AI can improve current performance while reducing the experiential practice through which marketers develop and maintain the judgment required to evaluate and redirect the AI solution. This mechanism helps explain heterogeneity in AI returns across firms and over time. We develop seven testable predictions and an agenda for research on creating, appropriating, and sustaining value from AI.