Perceptions of Agentic AI in Organizations: Implications for Responsible AI and ROI
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Abstract (arXiv)
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.
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References · 9
- 2025Multi-Agent Risks from Advanced AIcited by 150
- 2023Harms from Increasingly Agentic Algorithmic Systemscited by 134
- 2025International AI Safety Reportcited by 64
- 2022Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineeringcited by 20
- 2025Agentic Systems: A Guide to Transforming Industries with Vertical AI Agentscited by 20
- 2024Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systemscited by 3
- 2023The Return on Investment in AI Ethics: A Holistic Frameworkcited by 1
- 2024An ethical study of generative AI from the Actor-Network Theory perspectivecited by 1
- 2024Criticizing Ethics According to Artificial Intelligencecited by 1
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- 2026Towards Agentic AI Governance: A Preliminary Assessment
- 2025With Great Capabilities Come Great Responsibilities: Introducing the Agentic Risk & Capability Framework for Governing Agentic AI Systems
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- 2026Governing the Agentic Enterprise: A Governance Maturity Model for Managing AI Agent Sprawl in Business Operations