Who Innovates When AI Acts? Agentic Systems as Engines of Strategic Renewal

Abstract

The rapid emergence of agentic artificial intelligence (AI) systems—AI systems capable of autonomous goal-setting, decision-making, and coordinated action—raises a fundamental strategic question: who innovates when AI acts? This article develops a conceptual framework that positions agentic systems not merely as tools for operational efficiency, but as engines of strategic renewal. We argue that as AI systems increasingly participate in sensing opportunities, recombining knowledge, and executing experimentation, innovation shifts from being solely human-driven to being co-produced within human–AI collectives. Building on theories of dynamic capabilities, organizational learning, and strategic entrepreneurship, we introduce the concept of “distributed agency in innovation,” where initiative, experimentation, and adaptation are partially delegated to AI agents operating within bounded governance structures. We identify three mechanisms through which agentic systems enable strategic renewal: continuous opportunity discovery, autonomous variation and selection, and rapid capability reconfiguration. At the same time, we highlight emerging tensions related to accountability, control, and the redefinition of managerial roles. By reframing AI agents as strategic actors embedded in organizational processes, this article contributes to debates on digital transformation and innovation governance and outlines a research agenda for understanding how firms design, orchestrate, and regulate innovation in the age of agentic AI.

Keywords: Agentic AI; Artificial Intelligence; Strategic Renewal; Innovation; Dynamic Capabilities; Organizational Learning; Human–AI Collaboration; Digital Transformation; Autonomous Systems; Strategic Management.