Raffaele Ciriello, The University of Sydney Business School

Martin Adam, University of Goettingen

Zhongyun Zhou, Tongji University

AI companions are conversational systems designed to simulate human-like relationships and deployed as emotional support tools, tutors, and therapeutic assistants. Unlike conventional productivity software, their value derives from sustained interaction and personalised continuity, raising questions about trust, dependency, wellbeing, and how relational dynamics emerge through interactions between users, systems, and contexts.

This special issue invites Information Systems scholarship to examine AI companions through a relational lens extending beyond efficiency metrics. While these systems offer potential benefits such as broadened access to support, they simultaneously raise concerns about surveillance, manipulation, and commodified intimacy, reshaping individual capabilities and organisational practices.

The special issue welcomes theoretically ambitious and empirically grounded research across diverse methodologies that carefully theorise the sociotechnical characteristics of relational AI systems. Submissions should address design, governance, and use implications, with particular interest in interdisciplinary and critical perspectives.

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

Potential topics

• Dark sides of AI companions, problematic use patterns, and their potential roles in fostering delusions, harmful ideation, and maladaptive dependencies
• Relational perspectives on digital technologies: extending beyond instrumental and performance-based evaluation
• Social presence, parasocial interaction, and relationship formation with AI systems
• Anthropomorphism as a sociotechnical phenomenon: design, effects, and risks
• Design principles for AI systems that promote dignity, autonomy, trust, and human flourishing
• Hyper-personalisation and interaction-level adaptation in AI-mediated relationships
• How AI companions affect loneliness, wellbeing, identity formation, and social connection
• Human transformation through AI interaction: cognition, creativity, identity, and capability development
• Dependency, attachment, persuasion, and behavioural influence in sustained human–AI interaction
• Tensions and paradoxes in human–AI relationships
• AI companions in organisations, including changing work practices, expertise, authority, and control
• AI companions in healthcare, education, customer service, and public services: opportunities and risks
• Platform incentives, business models, and governance logics shaping relational AI
• Alternative governance and ownership models, including cooperative, open-source, and public-interest approaches
• Governance of emotionally sensitive data, privacy, portability, and consent
• Power asymmetries between users, providers, employers, and states in relational AI
• Youth, ageing populations, and other vulnerable stakeholders of relational AI
• Cross-cultural differences in companionship, intimacy, and acceptable machine roles
• Dual-use concerns, including manipulation, radicalisation, fraud, coercion, and political influence
• Regulatory and policy approaches to companion AI and socially consequential AI infrastructures
• Historical, philosophical, feminist, or critical perspectives on human–AI relations

Timeline

• December 31, 2026: Extended abstract submission deadline (optional)
• March 31, 2027: Full paper submission deadline

Associate editors

• Anuragini Shirish, IMT Business School
• Arisa Shollo, Copenhagen Business School
• Stan Karanasios, University of Queensland
• Sven Laumer, Friedrich-Alexander University
• Angsana Techatassanasoontorn, Auckland University of Technology
• Christoph Breidbach, University of Queensland
• Hameed Chughtai, Lancaster University
• Evelyn Ng, University of Sydney
• Johan Sæbø, University of Oslo
• Brad McKenna, Norwich Business School
• Riitta Hekkala, Aalto University
• Kai Riemer, University of Sydney
• Dimitra Petrakaki, University of Sussex
• Avijit Sengupta, University of Queensland

Marco Marabelli, Bentley University

Robert Davison, City University of Hong Kong

Federico Iannacci, University of Sussex

Shahla Ghobadi, University of Leeds

Zhongyun Zhou, Tongji University

Vanessa Cooper, RMIT University

This special issue examines how information systems scholarship can address environmental concerns related to generative AI. While GAI offers significant benefits for efficiency and automation, its rapid development has created substantial environmental challenges, including high electricity consumption, water use for cooling, and electronic waste from obsolete computing hardware. These impacts disproportionately affect vulnerable populations and regions in the Global South.

The issue seeks studies adopting an eco-socio-technical perspective to explore both the negative environmental effects of GAI and its potential benefits for weather forecasting, agriculture, and urban management. Contributors are encouraged to investigate how organizations, governments, individuals, and communities can implement and use GAI responsibly, examining tradeoffs between technological benefits and environmental costs. Research employing primary data, various methodologies, and practitioner perspectives are welcomed.

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

Potential topics

• Local and global policies associated with data centers, outsourcing, and offshoring practices, including legal, managerial, and economic perspectives
• Business models relying on or incentivizing GAI across specific industries such as healthcare, automotive, robotics, and aerospace, focusing on efficiency versus responsible use tradeoffs
• Individual-level practices of responsible GAI use in organizational and private citizen contexts, and how users understand environmental consequences
• GAI applications in smart cities, including traffic and parking optimization while addressing surveillance concerns
• GAI use in public administrations to streamline processes such as document production and benefit eligibility checks
• Existential short-term and long-term eco-socio-technical effects and the role of IS discipline in mitigating environmental and societal risks from large-scale GAI diffusion
• Collective action and activism strategies for promoting green development and responsible GAI use by major technology developers and deployers

Timeline

• December 31, 2026: Submission deadline for extended abstracts
• June 30, 2027: Submission deadline for full papers

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

Stefan Seidel, University of Cologne

Nicholas Berente, University of Notre Dame

Hong Guo, Arizona State University

Wonseok Oh, Korea Advanced Institute of Science and Technology

Digital technologies and artificial intelligence are disrupting established institutional practices and creating significant ethical, regulatory, and policy challenges. Organizations and governments must navigate tensions between addressing risks associated with data privacy, algorithmic bias, and labor displacement while fostering innovation and competitiveness.

The regulatory landscape is rapidly evolving through frameworks like the EU AI Act and GDPR to embed ethical protections. However, digital technologies operate at a pace that traditional regulatory approaches struggle to match, leading to novel mechanisms where technology itself serves as a tool for implementing and monitoring compliance.

This special issue invites sociotechnical and information systems research examining how ethical concerns, regulatory requirements, and policy initiatives interact within organizational and institutional contexts. Studies should employ diverse methodologies to investigate governance practices, regulatory effectiveness, compliance mechanisms, and how emerging technologies address institutional challenges.

Appel publié par MIS Quarterly. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Technology and AI ethics
• Data ethics
• Technology regulation
• AI regulation
• Data regulation
• Institutional governance
• Risk management
• Digital governance
• Sociotechnical perspectives
• Regulatory design
• Compliance and enforcement
• RegTech and SupTech
• Algorithmic regulation
• Organizational adaptation to regulation
• Data privacy and GDPR
• Responsible AI
• AI governance
• Sustainability and ESG
• Market regulation
• Self-regulation
• Legal technology
• Responsible data governance
• Bias and fairness in AI
• Algorithm accountability
• Labor and deskilling
• Human dignity in AI systems
• Regulatory sandboxes
• Innovation and regulation balance

Timeline

• November 1, 2026: Submissions Open
• November 13, 2026: Submissions Closed

Associate editors

• Alessandro Acquisti, Massachusetts Institute of Technology
• Alexander Benlian, Technical University of Darmstadt
• Min Chen, George Mason University
• Aaron Cheng, The London School of Economics and Political Science
• Ioanna Constantiou, Copenhagen Business School
• John Dong, Nanyang Technological University
• Anna Essén, Stockholm School of Economics
• Haiyang Feng, Tianjin University
• Stefan Feuerriegel, Ludwig Maximilian University of Munich
• Uri Gal, The University of Sydney
• James Gaskin, Brigham Young University
• Goh Khim Yong, National University of Singapore
• Anand Gopal, Nanyang Technological University
• Brad Greenwood, George Mason University
• Dominik Gutt, RWTH Aachen University
• Ola Henfridsson, University of Miami
• Nina Huang, University of Miami
• Jannis Kallinikos, The London School of Economics and Political Science
• Gerald C Kane, University of Georgia
• Wolf Ketter, University of Cologne
• Cameron Kormylo, University of Notre Dame
• Natalia Levina, New York University
• Zhepeng Li, The University of Hong Kong
• Kalle Lyytinen, Case Western Reserve University
• Min-Seok Pang, University of Wisconsin-Madison
• Hani Safadi, University of Georgia
• Nachiketa Sahoo, Boston University
• Juliana Sutanto, Monash University
• Mari-Klara Stein, TalTech
• Lai Wei, Shanghai Jiao Tong University
• Yi Yang, The Hong Kong University of Science and Technology
• Lior Zalmanson, Tel Aviv University
• Nan Zhang, University of Notre Dame
• Xia Zhao, University of Georgia
• Youngjin Yoo, London School of Economics and Political Science