Agentic AI as a Driver of Innovation and Change Management in Organizations: A Conceptual Review and Framework for Technology-Enabled Transformation
Purpose: This paper investigates the potential of Agentic Artificial Intelligence (AI) to be a driver of innovation and change management in organizations undergoing technology-enabled transformation. It addresses the impact of Agentic AI features, such as autonomy, reasoning, planning, tool use, memory, and multi-agent coordination, on innovation processes, organizational readiness, human–AI interaction, as well as responsible governance. Methodology: The methodology used in this paper was a desk-based conceptual review design, which was supported by framework development. The literature was identified through a concept-driven structured search process using ScienceDirect and Emerald Insight. The concepts reviewed were the five interrelated concepts: Agentic AI/AI agents, AI and innovation management, change management/AI readiness, digital transformation/technology-enabled transformation, and responsible AI governance. A conceptual and thematic synthesis method of analysis was used to analyze the selected literature. Findings: The review revealed that Agentic AI is able to assist with ideation, knowledge recombination, experimentation, process redesign, business model innovation, and workflow coordination. However, transformation does not occur automatically. The factors of organizational readiness, data quality, leadership support, employee trust, and role clarity, along with human-AI interaction and responsible governance, are essential for transformation based on Agentic AI. The paper also noted that Agentic AI presents a governance paradox because while it can have value due to autonomy, the greater the autonomy, the more likely there will be a need for human oversight, audit trails, escalation protocols, transparency, and restrictions on autonomous activity. Unique Contribution to Theory, Practice and Policy: The paper is unique in bringing together, in a single conceptual framework, socio-technical, dynamic capability, AI-readiness, change-management, and responsible AI governance views on the topic of Agentic AI-enabled transformation. It makes a contribution to practice by demonstrating that Agentic AI can be used as an organizational transformation capability, not as a technology with a narrow scope of practice. It helps shape policy by highlighting the importance of establishing real-world, reliable governance standards, accountability measures, controlled testing spaces, and sector-specific guidance for the responsible adoption of Agentic AI.