Aug 2026· International Research Journal of Management IT and Social Sciences· 0 citations
TL;DR
The first comprehensive synthesis linking AI technical capabilities with anticipatory governance theory is provided, offering a theoretically grounded, actionable pathway for practitioners navigating the digital transformation of project delivery, shifting the focus from controlling machines to cultivating symbiotic ecosystems.
Abstract
Purpose: The integration of artificial intelligence (AI) into project management is accelerating, yet governance frameworks have failed to keep pace with the transition from tool-based automation to genuine human-AI symbiosis. This article synthesizes literature across four fragmented domains to propose a unified governance model for anticipatory project management. Design/methodology/approach: A systematic, integrative review was conducted covering: AI in project management, Human-AI collaboration, Anticipatory governance, and Complexity theory. The synthesis draws on peer-reviewed literature from 2023-2026, integrating seminal work on human-AI co-agency and adaptive systems. Findings: The review reveals a fundamental tension: technological capability outpaces organisational absorption. To address this, the article introduces the Adaptive Organism Governance (AOG) Framework. This model reconceptualises the project organisation as a complex adaptive system comprising four interdependent dimensions: Cognitive Augmentation, Collaborative Intelligence, Anticipatory Sensing, and Complexity Absorption. The framework is operationalized through six governance principles: subsidiarity, transparency, adaptability, resilience, human-centricity, and continuous learning. Originality/value: This article provides the first comprehensive synthesis linking AI technical capabilities with anticipatory governance theory. The AOG Framework offers a theoretically grounded, actionable pathway for practitioners navigating the digital transformation of project delivery, shifting the focus from controlling machines to cultivating symbiotic ecosystems.
The study argues that collaborative intelligence should be viewed as an organizational capability rather than merely a technological outcome, requiring deliberate management of human judgment, ethical responsibility, and organizational design.
M. R· International Journal of Phi...· 0 citations
An exploratory literature review of the socio-technical issues involved in the adoption of GenAI tools in project documentation and governance and suggests a socio-technical conceptual framework that integrates these aspects into a unified view to inform people's understanding of responsible Human-AI collaboration in project settings.
Bela Lestari Dwireja, F. Abdalla, Yuhang Liu et al.· International journal of res...· 0 citations
This paper explores how AI risk governance can be effectively integrated into the epistemological and structural foundations of such organizations through the lens of fourth-order cybernetics, and offers a conceptual pathway for resilient and ethically aligned AI implementation in complex organizational environments.
Ludmila Jiříčková, Petr Doucek· International Scientific Con...· 0 citations
The findings indicate that AI enhances sustainable HRM by strengthening employee abilities, motivation, and opportunities, while simultaneously enabling organisational dynamic capabilities such as sensing, seizing, and transforming.
Masyhuri Masyhuri, Iqbal Lhutfi, Siswanto Siswanto et al.· Journal of Economics, Entrep...· 0 citations
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.
Fatma Albalooshi· International journal of tec...· 0 citations
The proposed framework offers a real-world action plan for sustainable AI transformation and a theoretical understanding of the phenomenon of AI transformation by offering a structured, risk-mitigated pathway toward high-maturity, AI-enabled enterprise operations.
M. Abuhaimed· Journal of Intelligent Decis...· 0 citations
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