Perceptions of Agentic AI in Organizations: Implications for Responsible AI and ROI
It addresses organizational challenges in implementing responsible AI for agentic systems, which is incremental as it builds on existing responsible AI literature.
This paper investigates how organizations perceive and adapt responsible AI frameworks for increasingly autonomous agentic AI systems, finding that complexity, novelty, and implementation challenges hinder effective adaptation and compromise both responsible AI outcomes and ROI.
As artificial intelligence (AI) systems rapidly gain autonomy, the need for robust responsible AI frameworks becomes paramount. This paper investigates how organizations perceive and adapt such frameworks amidst the emerging landscape of increasingly sophisticated agentic AI. Employing an interpretive qualitative approach, the study explores the lived experiences of AI professionals. Findings highlight that the inherent complexity of agentic AI systems and their responsible implementation, rooted in the intricate interconnectedness of responsible AI dimensions and the thematic framework (an analytical structure developed from the data), combined with the novelty of agentic AI, contribute to significant challenges in organizational adaptation, characterized by knowledge gaps, a limited emphasis on stakeholder engagement, and a strong focus on control. These factors, by hindering effective adaptation and implementation, ultimately compromise the potential for responsible AI and the realization of ROI.