CALL FOR PAPERS
Asia Pacific Journal of Information Systems (APJIS)
Special Issue:
Generative AI as an Organizational Actor: Delegation, Accountability, and Governance in Enterprise Transformation
GUEST EDITORS
Joonghee Lee, Hankuk University of Foreign Studies, South Korea, leej12@hufs.ac.kr
Jin Sik Kim, University of Massachusetts Boston, the United States of America, jinsik.kim@umb.edu
Thomas KB Koo, Dalhousie University, Canada, tom.kb.koo@dal.ca
Kyung Young Lee, Dalhousie University, Canada, kyunglee@dal.ca
Since the introduction of ChatGPT 3.5 in November 2022, generative AI (GenAI) technologies have experienced rapid and widespread adoption across professional and everyday contexts. The period of 2023–2024 was characterized by extensive individual-level experimentation and organizational pilot initiatives, coinciding with rapid improvements in the underlying model capabilities, reliability, and multimodal functionality of GenAI systems. More recently, an increasing number of organizations have begun transitioning from experimentation to formal integration, adopting GenAI chatbots and GenAI-enabled systems as core enterprise applications embedded in workflows, services, and decision-making processes.
This pivotal shift signals not only technological advancement but also a transformation in managerial logic regarding how organizations conceptualize and interact with enterprise systems, allocate responsibility, and structure work. As GenAI systems move from peripheral tools to embedded components of organizational processes, existing information systems and management theories face growing difficulty in explaining how authority, judgement, and accountability are exercised when the non-human systems actively participate in work processes.
As GenAI becomes deeply intertwined with organizational activities, its role is increasingly understood not merely as a tool to support tasks but as an organizational actor capable of participating in, shaping, and in some cases leading work processes. Emerging information systems and management research highlight how organizations now delegate substantive responsibilities to GenAI, treating it as a collaborator that influences productivity, coordination, and strategic decision-making. This evolution introduces significant opportunities, such as enhanced efficiency, cost reduction, and productivity gains, while also raising concerns related to accountability, governance, oversight, human resource development, and broader socio-organizational consequences.
This Special Issue welcomes rigorous research that examines GenAI as an organizational actor and investigates how delegation to GenAI for various work processes reshapes organizational logic across multiple levels of analysis, including individuals, groups, firms, industries, and broader institutional environments. We seek to advance rigorous theoretical and empirical contributions that examine the opportunities enabled by the integration of GenAI, as well as the tensions it creates for responsibility, control, and organizational governance.
Relevant topics include, but are not limited to:
* Allocation of responsibility and accountability when organizational tasks or decisions are delegated to Generative AI systems
* Reconfiguration of organizational control, governance, and oversight structures resulting from the integration of Generative AI into routine operations
* Emergence of novel coordination mechanisms in human–AI collaboration at team, interdepartmental, and organizational levels
* Governance, accountability, and market-level implications of AI-generated outputs, predictions, and competitive actions
* Trust, transparency, and legitimacy of AI-mediated interactions with employees, customers, and external stakeholders
* Dark-side outcomes of organizational Generative AI adoption, including over-reliance, de-skilling, embedded biases, and shifting power asymmetries
* Cross-level, cross-industry, and cross-national analyses of Generative AI adoption within market-oriented organizational processes
* Generative AI as an active contributor and its effects on employee voice, dissent, psychological safety, and creative risk-taking
* Co-producing work products with Generative AI and employees¡¯ sense of authorship, ownership, professional identity, and craftsmanship
* Employee perceptions of Generative AI¡¯s agency, competence, and moral standing, and the implications for the delegation of authority and discretion
* Effects of Generative AI involvement in evaluation, hiring, resource allocation, and task assignment on perceived fairness, equity, and organizational trust
* Boundary conditions shaping the delegation of tasks to Generative AI, including task criticality, uncertainty, ethical sensitivity, and organizational risk tolerance
* Organizational learning dynamics, knowledge erosion, and capability shifts resulting from sustained reliance on Generative AI systems
* Institutional, regulatory, and industry-level responses to the adoption of Generative AI as an organizational actor
* Organizational dependence, vendor lock-in, and strategic vulnerability arising from deep integration of proprietary Generative AI platforms
* Redistribution of power and control among managers, employees, and external technology providers due to Generative AI adoption
* The emergence of hybrid human–AI roles and Generative AI altering job boundaries, career trajectories, and professional socialization
ASIA PACIFIC JOURNAL OF INFORMATION SYSTEMS:
The Asia Pacific Journal of Information Systems (APJIS), a Scopus and ABDC-indexed journal (B-ranked), is the flagship journal of the IS field in the Asia Pacific region. The journal seeks to advance knowledge about the effective and efficient utilization of information technology by individuals, groups, organizations, society, and nations for the improvement of economic and social welfare. [https://apjis.or.kr/]
SUBMISSION GUIDELINES:
* The author(s) should indicate that the submission is for the special issue (SI: GenAI as Org. Actor) on the first page of the manuscript
TIME PLAN
* Submission due: 2026, July 31
* 1st round review decision: 2026, September 30
* Revised submission due: 2026, November 30
* 2nd round final review decision 2026, December 31
* Minor Revision and Publication: 2027, February 28