Jul 2026· International Journal of Education, Leadership, Artificial Intelligence, Computing, Business, Life Sciences, and Society· Vol 10, pp. 1-65· 0 citations
TL;DR
A systematic literature review and bibliometric analysis of the emerging research domain of agentic artificial intelligence in organizations reveals a significant shift from technical investigations of autonomous systems toward questions concerning organizational decision-making, human-agent collaboration, governance mechanisms, and the strategic implications of increasingly autonomous AI systems.
Abstract
The rapid diffusion of generative artificial intelligence has altered the technological and organizational landscape, shifting scholarly and managerial attention from systems primarily designed to generate content toward increasingly autonomous systems capable of planning, reasoning, coordinating actions, and pursuing goals with limited human intervention. This transition has given rise to the concept of agentic artificial intelligence, a broad category encompassing autonomous agents, multi-agent systems, and emerging forms of AI-enabled organizational actors. Despite growing academic and practitioner interest, the literature remains fragmented across computer science, information systems, management, and organizational studies, with limited conceptual integration regarding the implications of agentic AI for organizational design, governance, and leadership.
This study addresses this fragmentation through a systematic literature review and bibliometric analysis of the emerging research domain of agentic artificial intelligence in organizations. Following PRISMA guidelines, the study employs a structured search strategy using the Scopus and Web of Science databases and applies performance analysis and science-mapping techniques through Bibliometrix and VOSviewer. The analysis identifies the principal intellectual foundations of the field, the most influential authors, journals, and countries, and the thematic trajectories that have shaped scholarly discussions from early research on autonomous agents and multi-agent systems to contemporary debates on AI governance and organizational transformation.
The findings reveal a significant shift from technical investigations of autonomous systems toward questions concerning organizational decision-making, human-agent collaboration, governance mechanisms, and the strategic implications of increasingly autonomous AI systems. Six major research themes emerge from the literature: autonomous decision-making systems, multi-agent collaboration, agentic AI governance, human-agent interaction, organizational transformation and leadership, and ethical and societal risks. Building on these findings, the article develops an Agentic AI Organizational Transformation Framework that conceptualizes agentic AI as a dynamic organizational capability whose outcomes depend on governance arrangements, organizational readiness, and institutional trust.
The study contributes to the literature in three ways. First, it provides the first integrative mapping of agentic artificial intelligence research from an organizational perspective. Second, it advances a conceptual framework linking agentic AI capabilities to organizational outcomes and governance mechanisms. Third, it develops a future research agenda aimed at supporting empirical investigations of autonomous AI systems in complex organizational environments. The article concludes that agentic artificial intelligence should not be viewed merely as an incremental extension of generative AI but rather as a potentially transformative organizational phenomenon that may redefine decision-making processes, leadership practices, and the boundaries between human and artificial agency.
Purpose. Marketing organizations are moving from prompt-driven Generative Artificial Intelligence (Generative AI) toward agentic systems that plan, act, and adapt across multi-step tasks with limited human supervision. The scholarly literature on this transition is dispersed across marketing, information systems, and computer science, and it rarely distinguishes technological capability from the organizational conditions under which autonomous agents create legitimate and durable marketing value. This article critically reviews that relationship and develops a capability-based framework for autonomous marketing.
Design/methodology/approach. The article is a critical narrative review rather than a systematic or empirical review. Google Scholar was the principal literature-discovery platform, supplemented by backward and forward citation searching, during July–August 2026. The review audits the 35 references in the source manuscript, retains all as traceable and topically relevant, and adds 8 supplementary scholarly sources identified through citation chaining, producing a cited corpus of 43 scholarly works. A structured narrative process covered identification, relevance screening, design-sensitive appraisal, thematic coding, and narrative synthesis. Dynamic capabilities theory structures the analysis.
Findings. Agentic AI does not automatically improve marketing outcomes. Its value is contingent on an organizational capability-conversion process in which AI affordances are translated, through data infrastructure, analytical and creative skill, redesigned workflows, and governance, into accountable marketing routines. Evidence specific to Agentic AI in marketing remains overwhelmingly conceptual, vendor-authored, or transferred from adjacent domains such as personal selling and customer service; controlled, longitudinal, or audited evidence of autonomous-agent performance in marketing is scarce, and widely circulated efficiency and return-on-investment figures originate predominantly from industry and consultancy reports rather than peer-reviewed research.
Originality/value. The review replaces a linear technology-adoption narrative with a capability-conversion explanation, separates reviewed evidence from proposed relationships, and contributes a four-stage evolutionary model, a governance-sensitive AI–capability–marketing relationship framework, and testable propositions distinguishing technological affordances from organizational capability, marketing practice redesign, and verified outcomes.
Ankita Garg· International Journal of Sci...· 0 citations
This paper aims to examine the managerial impact of agentic artificial intelligence in public administration, with a particular focus on how autonomous AI systems reshape decision-making, organizational structures, managerial authority and accountability mechanisms. The study adopts a conceptual-analytical research design, based on the synthesis of relevant literature, policy documents, regulatory perspectives and theo-retical contributions in the fields of digital governance, artificial intelligence and public management. The analysis shows that the transition from traditional digital administration to agentic organizations may im-prove operational efficiency, support data-driven decision-making and enable more adaptive public ser-vices. At the same time, it generates significant challenges related to trust, ethical oversight, legal respon-sibility, workforce adaptation and the redefinition of managerial roles. The originality of the paper lies in its focus on agentic AI as a distinct stage of digital transformation, moving beyond conventional automation toward autonomous systems capable of planning, execution and self-correction. The study contributes to the literature by proposing the need for a new managerial profile, the systems architect manager, responsible for orchestrating hybrid ecosystems composed of human experts and digital agents. From a practical per-spective, the findings highlight the importance of institutional readiness, human-on-the-loop supervision, transparent governance mechanisms and continuous training for the responsible integration of agentic AI in public institutions.
Roxana Sârbu, Florin Dobre, Ion Pargaru et al.· New Trends in Sustainable Bu...· 0 citations
The emergence of autonomous artificial intelligence agents represents a new phase in the evolution of generative artificial intelligence, extending AI capabilities beyond content generation toward autonomous reasoning, workflow orchestration, institutional coordination, and organizational decision support. Among these developments, Claude Agents exemplify a new generation of agentic AI systems capable of executing complex multi-step tasks, managing institutional information, and interacting continuously with human users across diverse educational environments. Although generative artificial intelligence has attracted substantial scholarly attention, research remains largely centered on pedagogical applications, while the governance and leadership implications of autonomous AI agents continue to be conceptually fragmented and insufficiently theorized.This paper develops an integrative conceptual framework that examines how Claude Agents may transform educational leadership, institutional governance, and strategic decision-making in schools and higher education institutions. Drawing upon interdisciplinary scholarship in educational leadership, organizational governance, socio-technical systems theory, organizational information processing theory, human-AI collaboration, and digital transformation, the study adopts a conceptual qualitative methodology based on an integrative literature review and theory-building approach. The analysis argues that Claude Agents should not be understood merely as intelligent assistants but as agentic organizational actors that increasingly participate in institutional information processing, policy implementation, strategic planning, administrative coordination, and evidence-informed decision-making. Their integration creates opportunities for more adaptive, transparent, and data-informed governance while simultaneously introducing new challenges related to accountability, explainability, algorithmic bias, professional autonomy, institutional legitimacy, and ethical oversight.Building on these insights, the paper proposes the Human-AI Governance Framework for Educational Leadership (HAGF), which conceptualizes leadership as a collaborative governance process in which human judgment and autonomous AI agents jointly contribute to organizational decision-making within clearly defined institutional, ethical, and regulatory boundaries. The study contributes to emerging debates on agentic artificial intelligence by extending existing theories of educational leadership beyond technology adoption toward a governance-oriented perspective that integrates organizational resilience, distributed intelligence, and responsible AI governance. Finally, the paper identifies a future research agenda focused on AI-enabled leadership, institutional trust, governance architectures, and the evolving relationship between educational leaders and autonomous intelligent agents.
Bogdan Costache· International Journal of Edu...· 0 citations
This study presents a systematic literature review of agentic commerce, with particular emphasis on autonomous shopping systems, machine-to-machine transaction protocols, and the governance conditions necessary for their large-scale adoption. Rapid advances in large language models, generative artificial intelligence, and autonomous agent architectures are transforming digital commerce by enabling intelligent agents to search for and assess products, compare suppliers, negotiate transaction terms, execute purchases, coordinate logistics, and manage post-purchase activities with limited human involvement. Despite increasing academic and industry interest, the relevant literature remains fragmented across e-commerce, information systems, artificial intelligence, cybersecurity, digital governance, and consumer behavior research. Following the PRISMA 2020 methodology, this review examines studies published between 2020 and 2026 and retrieved from Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and the ACM Digital Library, supplemented by searches of Google Scholar and arXiv. Following identification, deduplication, screening, eligibility assessment, and quality appraisal, 42 studies were included in the qualitative synthesis. The evidence was analyzed using the AI-Commerce Integration Assessment Framework, which enabled systematic interpretation of the literature across the dimensions of readiness, feasibility, performance, and maturity. The findings indicate a clear transition from AI-assisted product discovery and recommendation systems toward increasingly autonomous purchasing environments in which AI agents operate as active economic actors. However, broader adoption remains limited by concerns related to trust, privacy, transparency, accountability, cybersecurity, user control, and legal responsibility. The review also identifies emerging infrastructures for digital identity, authentication, interoperability, automated negotiation, smart contracts, payment settlement, and dispute resolution. Nevertheless, these mechanisms remain weakly standardized and insufficiently interoperable across platforms and jurisdictions. Overall, agentic commerce is conceptualized as a transition from human-centered digital transactions toward AI-mediated economic ecosystems. Its sustainable development will depend on the coordinated evolution of technical standards, governance structures, explainable AI, consumer protection mechanisms, accountability frameworks, and secure transaction infrastructures. This review provides an integrated synthesis of the field and identifies priorities for future empirical research on real-world implementation, interoperability, regulation, market effects, and human–AI collaboration.
The rapid emergence of agentic artificial intelligence (AI) has outpaced scholarly discussions of its implications for library reference services, creating a significant conceptual gap within the broader discourse on the Fifth Industrial Revolution (5IR). Existing studies have focused largely on chatbots, robotic technologies, and conventional AI applications, with limited attention to autonomous AI agents capable of reasoning, planning, and executing complex information tasks. This conceptual review addresses that gap by examining the transformative potential of agentic AI for reference services within the human-centred philosophy of the 5IR. Drawing on recent literature on agentic AI, Industry 5.0, and library and information science, the paper synthesises current knowledge to identify the defining characteristics, emerging applications, opportunities, challenges, and strategic implications of agentic AI for librarians. The review indicates that agentic AI can significantly enhance reference services through autonomous literature searching, personalised research support, intelligent knowledge discovery, multilingual assistance, and complex query resolution. Nevertheless, concerns relating to algorithmic bias, hallucination, transparency, data privacy, intellectual property, and professional accountability require careful governance. The paper argues that successful implementation depends on AI literacy, ethical oversight, human–AI collaboration, institutional governance frameworks, equitable access, and continuous evaluation. It provides a strategic framework for advancing innovative, ethical, and sustainable AI-enabled reference services.
Isu Michael Egbe, Y. Ajani, Sadiya Abubakar· Business Information Review· 0 citations
A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.
Sparsh Bajoria, Shreyanshu Ranjan, Adhitya M et al.· Cognitive Computation· 0 citations
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