Martin Adam, University of Goettingen

Aaron Baird, Colorado State University

Mari-Klara Stein, Tallinn University of Technology

Alexander Benlian, Technical University of Darmstadt

AI is transitioning from a tool for individual productivity assistance to a participant in organizational action through agentic systems that can interpret goals, perceive states, plan actions, and execute tasks with autonomy. This shift reconfigures organizational arrangements, requiring new thinking about delegation, accountability, control, and oversight.

Agentic organizations embed AI agents within routines, systems, and workflows, creating sociotechnical arrangements impacting core operational systems. Information systems scholars are well-positioned to address this transition given existing expertise in organizational change, algorithmic management, platform governance, and human-AI collaboration.

This special issue seeks research on how organizations can design, govern, and manage human-AI ensembles while preserving accountability, resilience, and human judgment. Papers should examine delegated agentic participation in organizational action, including governance mechanisms, workflow redesign, multi-agent systems, epistemic challenges, workforce implications, and safety considerations.

Appel publié par Journal of Management Information Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Delegated autonomy and control in agentic organizations
• Accountability and oversight mechanisms for AI agents
• Agentic process redesign and workflow transformation
• Organizational capability building for agentic systems
• Multi-agent orchestration and coordination
• Agent interoperability and digital ecosystems
• Epistemic governance and trust in AI agents
• Opacity and contestability of AI-generated actions
• Cognitive and behavioral implications of agentic AI
• Workforce implications and professional identity
• Skill formation and reliance on AI agents
• Resilience and safety in agentic systems
• Security and compliance in agentic workflows
• Societal consequences and ethical implications of agentic AI
• Human-AI ensembles and human authority preservation

Timeline

• Invalid DateTime: Final decision and publication
• December 15, 2026: Optional extended abstract submission deadline
• February 1, 2027: Full paper submission deadline
• May 1, 2027: First round of reviews completed
• September 1, 2027: Paper revisions due
• November 1, 2027: Second round of reviews completed
• February 1, 2028: Second paper revisions due

Associate editors

• Armin Alizadeh, Technical University of Darmstadt
• Abhijith Annand, University of Arkansas
• Langtao Chen, University of Tulsa
• Christy M. K. Cheung, Hong Kong Baptist University
• W. Alec Cram, University of Waterloo
• Carolina Alves de Lima Salge, University of Georgia
• Thomas Hess, Ludwig Maximilian University of Munich
• Ekaterina Jussupow, Technical University of Darmstadt
• Harris Kyriakou, ESSEC
• Aron Lindberg, Stevens Institute of Tech
• Anne-Sophie Mayer, Ludwig Maximilian University of Munich
• Abhay Mishra, University of Arkansas
• Long The Nguyen, Washington State University
• William Olivera, Florida State University
• Gabriele Piccoli, Louisiana State University
• Magno Queiroz, Florida Atlantic University
• Marta Stelmaszak, University of Massachusetts Amherst
• Timo Sturm, Technical University of Darmstadt
• Scott Thiebes, Tongji University
• Thomas Ware, University of Pittsburgh
• Martin Wiener, Technical University of Dresden
• David Xu, City University of Hong Kong

Lixiang Yan, Tsinghua University

Yizhou Fan, Peking University

Yueqiao Jin, Monash University

Nancy Law, University of Hong Kong

Yu Zhang, Tsinghua University

Xibin Han, Tsinghua University

This special section examines agentic AI in education, defined as computational systems exhibiting interactivity, bounded autonomy, and adaptability within human-defined objectives. Unlike reactive AI tutoring systems or prompt-based generative AI tools, agentic AI initiates action, sustains participation, and maintains functional roles through persistent memory and task decomposition. The shift toward such systems reconfigures how epistemic labour and coordination are distributed within learning communities, affecting learners' perceptions of agency, shared regulation, and collaborative reasoning.

The section welcomes empirical and conceptually grounded studies exploring how agentic AI reshapes learner perceptions, teacher roles, epistemic labour, and social-cognitive dynamics. Particular emphasis is placed on understanding when artificial agency supports productive learning versus constraining learner autonomy, examining this across diverse educational contexts, learner populations, and cultural settings. Contributions addressing governance, responsibility, equity, and methodological innovation are encouraged.

Appel publié par British Journal of Educational Technology. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Conceptualising Agentic AI as Artificial Agency in Education: Frameworks and models that define agentic AI explicitly in terms of interactivity, bounded autonomy, and adaptability, and that clarify boundaries between agentic AI, generative AI assistants, and reactive AIED systems.
• Learner and Teacher Perceptions of Artificial Agency: Empirical investigations of how learners and educators interpret AI initiative, persistence, and role adoption, and how these perceptions shape trust, attribution of intent, responsibility, and participation in learning activities.
• Epistemic Labour and Initiative Redistribution: Studies examining how agentic AI redistributes epistemic labour within individual or collaborative learning, including effects on problem framing, task coordination, evaluation, and decision-making when AI initiates actions rather than responding to prompts.
• Regulation, Coordination, and Social-Cognitive Dynamics: Analyses of how agentic AI influences self-regulation, co-regulation, and shared regulation, particularly in group settings where AI adopts persistent roles that shape interactional norms, turn-taking, and closure of inquiry.
• Temporal Persistence and Path Dependence in Learning Processes: Research that captures how agentic AI's sustained participation and memory create path-dependent learning trajectories, including benefits for coherence and risks of early framing effects or cascading errors.
• Identity Inference, Social Presence, and Responsibility: Empirical work on how proactive AI behaviour affects identity inference and social presence in cue-lean environments, and how responsibility and accountability are negotiated when learning actions originate from artificial agents.
• Methodological Approaches for Studying Artificial Agency: Methodological contributions that advance the measurement of artificial agency and its effects, including multimodal analyses, process-level modelling, and designs that distinguish agentic participation from tool-based assistance.
• Governance and Educational Implications of Agentic AI: Analyses addressing accountability, transparency, and institutional responsibility when agentic AI functions as a collaborator, coordinator, or evaluator in educational settings.

Timeline

• August 1, 2026: Abstract submission deadline
• October 28, 2026: Full manuscript submission deadline
• March 15, 2027: Final manuscript acceptances
• May 1, 2027: Issue publication online

Tony Fang, Memorial University of Newfoundland

Jennifer A. Harrison, EM Normandie

Fei Song, Toronto Metropolitan University

Mingwei Liu, Rutgers University

Generative AI is being rapidly integrated into workplace systems and HR processes, fundamentally reshaping how work is performed and productivity should be understood. The collaboration between humans and AI systems in task completion creates new challenges for measuring and attributing productivity outcomes, as traditional assumptions about performance metrics and human effort become outdated in AI-augmented contexts.

This special issue seeks research that reconsiders how productivity is conceptualized, measured, and compared when work involves human-AI collaboration. The call invites studies examining the distinction between AI adoption and actual use, the distribution of performance effects across different worker groups, implications for career development and employability, and the organizational and HR factors that influence AI-augmented productivity. Methodological contributions exploring innovative approaches to studying these phenomena are also welcomed.

Appel publié par Personnel Review. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Conceptualizing productivity in AI work and careers
• Distinguishing between AI exposure, use, and augmentation
• Measuring human versus AI contributions to outputs and performance
• Changes in the distribution of performance
• Implications of GenAI for skill development, career trajectories, and employability
• HR practices, job design, and organizational context in shaping AI productivity
• Methodological approaches to studying AI and work

Timeline

• August 31, 2026: Opening date for manuscripts submissions
• January 31, 2027: Closing date for manuscripts submission

Yang Feng, California State University, Fullerton

Quan Xie, Southern Methodist University

Joanna Strycharz, University of Amsterdam

Artificial intelligence is transforming advertising at multiple levels: as a tool for creative and strategic work, and as an autonomous agent capable of planning and executing tasks independently. This transformation raises fundamental questions about how advertising professionals collaborate with AI systems, how roles and authorship are being redefined, how consumers respond to AI-driven advertising, and what research methods and ethical safeguards are needed when AI participates in the research process itself.

The special issue invites contributions addressing three interconnected domains: human-AI collaboration in advertising practice and creative work; how AI-generated and AI-personalized advertising affects consumer perception and behavior; and how researchers should adapt their methodologies, standards, and ethical frameworks when collaborating with AI in data collection, stimulus generation, and analysis. Submissions may employ any methodological approach and should move beyond describing tools toward deeper insights about advertising, persuasion, and communication in the age of AI.

Appel publié par International Journal of Advertising. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Human-AI collaboration in advertising creative processes, including authorship, creative judgment, and practitioner roles across different contexts of advertising
• AI-assisted campaign strategy, optimization, and automated decision-making
• Agentic AI as a proactive partner in advertising practice and its implications for human oversight and accountability
• Governance structures for human-AI collaboration in advertising agencies and brand organizations
• The full range of human-AI collaborative modes, from tool use to co-creation to agentic delegation, and their implications for advertising practice and governance
• Human-AI collaboration in prosocial and public interest advertising
• Consumer perception, emotion, evaluation, and response to AI-generated advertising
• AI-driven personalization and its effects on persuasion, privacy, and consumer trust, consent, data protection, and consumer vulnerability
• Anthropomorphism, virtual influencers, AI digital twins, and AI agents as advertising vehicles
• AI advertising across diverse contexts, such as PSAs, health communication, political advertising, public policy, and nonprofit campaigns
• Ethical implications of AI advertising for vulnerable audiences, including children, older adults, patients, and politically targeted publics
• Consumer awareness, literacy, and resistance in response to AI-driven advertising systems
• Construct validity and stimulus equivalence in advertising experiments using AI-generated materials
• Reliability and replicability standards for AI-assisted advertising research
• Validity of AI-mediated data collection in advertising research
• Research ethics of AI-simulated participants and agentic data collection in advertising studies
• Privacy, consent, and data protection in AI-assisted research, synthetic data, and agentic data collection
• Bias and representational equity introduced through AI-assisted research designs and/or AI-generated advertising content
• Theoretical implications of human-AI collaboration for established advertising frameworks
• Agentic AI in advertising research and the governance structures needed to maintain scholarly rigor

Timeline

• August 1, 2027: Submission window opens
• August 31, 2027: Manuscript deadline

This special issue explores the multifaceted dimensions of human-AI collaboration, examining both the opportunities it presents and the challenges it raises across various domains and disciplines. The collection seeks interdisciplinary perspectives on how humans and artificial intelligence systems can work together effectively and responsibly.

Appel publié par Technology in Society. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• December 31, 2026: Submission deadline

Olga Battaïa, Kedge Business School

Yasser Dessouky, San Jose State University

Reza Zanjirani Farahani, Paris School of Business

Masood Fathi, University of Skövde

Madjid Tavana, La Salle University

This special issue investigates how collaborative intelligence—combining human expertise, artificial intelligence, and distributed problem-solving—can advance operations research to address modern decision-making challenges. Traditional OR methods struggle with the dynamic and interconnected nature of contemporary problems, from logistics to emergency response. The collection seeks contributions that demonstrate how human-AI collaboration can enhance decision-making, boost system resilience, and optimize complex operational environments.

The call invites theoretical, computational, and applied research on human-AI collaboration in OR models, optimization and game-theoretic approaches for multi-agent systems, adaptive and decentralized frameworks, and data-driven learning-based optimization. Submissions should demonstrate both theoretical rigor and practical relevance, with innovative methodologies and real-world applications that advance collaborative intelligence in operations research.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Designing OR models that facilitate seamless interaction and information exchange between human decision-makers and AI agents
• The framework for integrating human judgment, preferences, and ethical considerations into AI-driven decision-making
• Techniques for visualizing and interpreting AI outputs to enhance human understanding and trust
• Novel optimization algorithms and game-theoretic frameworks for coordinating and optimizing decisions in multi-agent environments
• Models addressing diverse objectives, capabilities, and interactions among multiple agents
• Approaches to managing conflicts, uncertainties, and strategic behaviors in multi-agent decision-making
• OR frameworks capable of dynamically adapting to real-time changes and uncertainties
• Decentralized optimization algorithms and control strategies for distributed systems
• Online learning and adaptive control techniques to improve system responsiveness and resilience
• Leveraging machine learning and data analytics to extract insights and patterns for OR applications
• Learning-based optimization algorithms that improve performance through data feedback
• Predictive analytics and simulation techniques for enhanced decision-making and risk management

Timeline

• December 31, 2026: Submission deadline

Laura Amo, University at Buffalo, State University of New York

Richard Baskerville, Georgia State University

Rui Chen, Iowa State University

Matthew Hashim, University of Arizona

Yaojie (William) Li, University of New Orleans

Yuan Li, University of Tennessee at Knoxville

As artificial intelligence increasingly dominates both offensive and defensive cybersecurity, this special issue emphasizes the critical importance of maintaining human involvement in security systems and decisions. The issue addresses concerns about AI-driven threats such as sophisticated phishing attacks, deepfakes, and behavioral data exploitation, while acknowledging that defensive reliance on AI-based threat detection creates cognitive challenges for practitioners.

Human-in-the-loop (HITL) is presented as a design principle that ensures human participation in system training, decision-making, and error mitigation, recognizing that fully automated security systems may be restrictive or dangerous. The special issue calls for behavioral information security research that balances AI's growing role with sustained focus on human behavior, cognition, and motivation in secure systems, training, and technologies.

Appel publié par Information Systems Frontiers. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Neurosecurity (NeuroIS) investigations of information security behavior
• Behavioral analyses of design science treatments enhancing or balancing security and privacy tradeoffs
• The behavioral intersection of cybersecurity/privacy research and AI/ML advancements
• AI-enabled security awareness, training, nudging, and behavioral intervention systems
• Human-AI collaboration in security decision-making, compliance, monitoring, and response
• Behavioral security implications of generative AI, including phishing, social engineering, misinformation, insider threats, and user overreliance on AI tools
• Design science approaches to developing, evaluating, and theorizing intelligent security artifacts with behavioral implications
• Adaptive, personalized, and context-aware security interventions enabled by AI and analytics
• Theoretical extensions or reconceptualizations of established behavioral security theories in AI-mediated environments
• Security behaviors in pervasive and post-pandemic work environments, including remote work, hybrid work, IoT, cloud platforms, and platform ecosystems

Timeline

• January 15, 2027: Submission deadline
• May 15, 2027: Notification of first round reviews
• July 15, 2027: Revised manuscript due
• September 1, 2027: Notification of second round reviews
• October 15, 2027: Final version due
• January 30, 2028: Tentative publication date

Paul Leonardi, :?

Alex Murray, :?

Frank Nagle, :?

Nelson Phillips, :?

Juliana Schroeder, :?

Paula Ungureanu, :?

Elisa Villani, :?

The fundamental concept of agency—who can act, what action requires, and who bears responsibility—has long shaped organizational theory. With intelligent technologies now actively participating in organizational processes, this foundational understanding is being challenged as action, intention, and consequences can no longer be attributed solely to individual human actors.

This special issue invites theoretically sophisticated research that reimagines agency when humans and machines co-produce organizational action. The editors seek work that both reconceptualizes agency itself and examines how this shift transforms core organizational phenomena including behavior, leadership, careers, strategy, institutions, and governance.

Appel publié par Organization Science. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Reconceptualization of agency in contexts involving artificial intelligence and human actors
• Distribution and location of agency when action is co-produced by people and machines
• Implications for organizational behavior and motivation theories
• Leadership and decision-making in AI-augmented environments
• Control mechanisms and accountability in human-AI systems
• Value creation involving intelligent technologies
• Career development and work structures affected by AI participation
• Institutional change driven by agentic AI
• Technological change and organizational adaptation
• Management and organizational control with autonomous systems
• Strategic implications of distributed agency
• Entrepreneurship in the age of AI
• Sociology of work and labor transformation
• Information systems and autonomous action
• Governance frameworks for AI-driven organizational action

Timeline

• February 1, 2027: Submissions due

Rosanna Fornasiero, CNR IEIIT

Luis M. Camarinha-Matos, NOVA University Lisbon

Xavier Boucher, Mines Saint-Étienne

Angel Ortiz, Universitat Politècnica de València

Hybrid Collaborative Networks combining human and artificial intelligence actors are becoming fundamental to value creation in digitally distributed ecosystems. These networks integrate diverse actors such as organizations, individuals, intelligent systems, and platforms operating across physical, digital, and organizational boundaries. Understanding their dynamics is essential for ensuring effective design, management, resilience, and sustained performance in changing environments.

This special issue addresses the scientific challenges of managing the life cycle of hybrid human-AI collaborative networks, including how such structures emerge, evolve, adapt, and dissolve. It calls for innovative design methods, adaptive governance models, and frameworks that integrate technological solutions with socio-human and managerial approaches to ensure effective human-AI integration, trust, and scalability.

Appel publié par Production Planning & Control. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Digital platforms for HCNs
• Collaborative dynamics among human and AI teams
• Agile design and management of hybrid networks
• Design of AI teammates
• Knowledge life cycle in distributed cognitive systems
• Collaboration and coopetition in untrustworthy environments
• Life cycle of collaborative cognitive cyber-physical systems
• Combination of human expertise with AI systems
• Scalability and adaptability of HCNs
• Collective decision making, value creation and creativity
• Digital twins for HCNs
• Governance framework for HCNs
• Understanding and explainability of HCN decisions
• Advanced collaborative robotics
• Complex hybridization of collaboration – organizations, people, smart machines, intelligent systems
• Resilience & antifragility in HCNs
• Ethics, security, & trust in HCNs
• AI integration for logistics and transportation networks
• AI for collaborative risk and crisis management
• Society 5.0 and collaborative networks
• CN applications and case studies in multiple fields

Timeline

• March 31, 2027: Manuscript deadline

Wanhao Zhang, Norwegian University of Science and Technology (NTNU)

Younghoon Chang, University of Nottingham Ningbo China

Sameer Kumar, University of Malaya

Smart systems are now deeply embedded in various social contexts, functioning as sociotechnical arrangements that sense, classify, predict and intervene in everyday practices. This special issue seeks to understand how these digitally enabled systems reshape relations between humans, machines, organisations and institutions, and how they become consequential through design, institutional embedding and everyday use.

The issue addresses both how smart systems are governed and how they themselves participate in governing sociotechnical transformation. Key concerns include questions of behaviour, interaction, coordination, authority, accountability and power, particularly examining hybrid intelligence and human-AI collaboration. The special issue invites submissions examining smart systems not merely as technical innovations but as systems shaping governance, interaction and behaviour in organisational, institutional and everyday contexts.

Appel publié par Behaviour & Information Technology. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Smart systems in homes, workplaces, healthcare, education, mobility, public services and platform-mediated environments
• Human-centred AI, hybrid intelligence and human-AI collaboration in organisational and everyday settings
• Conceptual, methodological and design-oriented approaches to studying governance in smart systems
• Algorithmic decision-making, coordination, compliance and accountability
• User adaptation, negotiation, resistance, appropriation and trust in relation to smart technologies
• AI ethics, information privacy, surveillance, transparency and asymmetrical power in digital systems
• Smart and digital health, care technologies and digitally mediated wellbeing
• Digital work, algorithmic management, robotic management and the reconfiguration of organisational routines
• Datafication, monitoring, prediction and automated feedback as modes of governance
• Inclusion, exclusion, vulnerability and inequality in smart sociotechnical environments
• Smart cities, digital government and platform-based public services
• Comparative, cross-cultural or interdisciplinary studies of smart systems and sociotechnical transformation

Timeline

• October 20, 2026: Manuscript deadline

The special issue draws upon three strands of literature. The first explores the evolving interaction between human intelligence and artificial intelligence. A balanced augmentation approach combining human and artificial intelligence is recommended rather than an automative approach. This calls for co-intelligence, using AI as a co-worker. Recent research has explored the creative collaboration between humans and AI to co-create brand voice, identifying effective human-AI co-creation as happening at three levels: the individual brand professional, the organisational level of brand management and the societal level, the external environment in which the brand operates. Frameworks have been developed for human marketers and consumers collaborating with AI within the retail sector.

Appel publié par European Journal of Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How can augmented brand intelligence be effectively implemented in strategic and operational brand management and brand control?
• Does augmented brand intelligence lead to an increase or decrease in brand purpose, brand consistency, and creativity?
• What are the possibilities and limitations of augmented brand intelligence in brand science?
• What is the role of AI and humans in consumer-brand interactions?
• What is the role of human emotions in the development of consumer-brand relationships in the age of AI?
• What is the role of human creativity in brand innovation in the age of AI, especially with social innovations aimed at positively impacting society and the planet?
• What humanistic values should brands embrace in order to build a profitable but also responsible business capable of addressing some of the pressing problems that humanity is facing, such as climate change or social inequalities?
• What are the potential ethical dilemmas that the use of AI in branding might raise and how managers should address them?
• How is the role and skill set of brand managers changing in the AI age?
• What are best practice examples of AI currently being used by marketers to drive brands and customer relationships?

Timeline

• August 7, 2026: Opening date for manuscripts submissions
• August 9, 2026: Closing date for manuscripts submission