AI systems are increasingly used in HR functions such as recruitment, employee analytics, training, performance management and workforce planning. While organizations often expect these systems to improve efficiency and fairness, they raise concerns about transparency, employee wellbeing, job quality and whether such systems genuinely enhance organizational performance. This special issue shifts focus from simply whether organizations adopt AI to how AI-enabled HR systems should be designed, governed and experienced to benefit employees and organizational effectiveness.

The special issue examines the relationship between AI-enabled HR practices and sustainable organizational performance, considering both potential benefits and risks. It invites research exploring when and how AI strengthens or undermines work quality, fairness, employee voice, inclusion and capability development. The collection addresses emerging regulatory interest from bodies like the OECD and EU AI Act, which recognize that AI in employment decisions requires responsible governance.

Appel publié par Journal of Organizational Effectiveness: People and Performance. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-enabled recruitment, selection and fair access to work: How AI screening, automated assessments, candidate ranking, video interviews and people analytics affect fairness, validity, transparency, accessibility and selection outcomes.
• AI-supported training, development and capability building: How AI-enabled learning systems, skills analytics, career platforms and talent systems affect reskilling, development access, career visibility and employee capability.
• AI-enabled performance management, monitoring and evaluation: How algorithmic monitoring, datafication and AI-supported appraisal affect fairness, trust, employee agency, wellbeing, reasonable adjustment and performance outcomes.
• Work design, job quality and employee voice in AI-enabled workplaces: How AI changes autonomy, workload, coordination, meaningful work, participation, consultation and human oversight in people-management decisions.
• Inclusion, disability, governance and sustainable organisational effectiveness: How organisations design AI-enabled HRM systems that reduce bias, support EDI, protect disabled workers and applicants, strengthen trust and contribute to sustainable organisational performance.

Timeline

• June 25, 2026: Opening date for manuscripts submissions
• January 25, 2027: Closing date for manuscripts submission

Fernando Miramontes Forattini, Dublin City University

Regina Connolly, Dublin City University

This special issue examines how care ethics and relational approaches can advance responsible design and governance of AI-enabled systems. While contemporary AI ethics discourse has focused on fairness, transparency, and compliance frameworks, this call seeks to address the structural, relational, and institutional dimensions of how digital systems affect vulnerability, participation, and human agency.

The special issue invites empirical research, conceptual contributions, design science research, and interdisciplinary perspectives that move beyond procedural approaches to explore responsibility distribution across socio-technical arrangements. Submissions should examine relationships between technology, power, participation, exclusion, and accountability in digital environments, grounded in diverse epistemological and methodological traditions.

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

Potential topics

• Care ethics and Information Systems design
• Responsible AI and relational accountability
• Ethics of participation, inclusion, and exclusion in digital systems
• Structural ethics and socio-technical governance
• Human-centred and care-centred AI design
• Vulnerability, dependency, and digital infrastructures
• AI governance and institutional legitimacy
• Ethics of repair, maintenance, and redress in digital systems
• Participatory and inclusive approaches to AI governance
• Responsible innovation and structurally aware design
• Public sector AI and questions of care, trust, and legitimacy
• Algorithmic systems and the distribution of risk and burden
• Gender, inequality, and digital governance
• Ethics of automated decision-making
• Relational approaches to trust, transparency, and accountability
• Organizational responsibility in AI-enabled environments
• Care ethics and sustainability in digital transformation

Timeline

• September 30, 2026: Manuscript submission deadline
• November 30, 2026: First review decisions
• February 1, 2027: Revised manuscript submission
• March 15, 2027: Final decisions

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

Jenny Le, VinUniversity

Helen Chun, Cornell University

Sara Quach, Griffith University

Park Thaichon, University of Southern Queensland

This Special Issue aims to advance ethics of algorithmic persuasion in marketing. It seeks to fill the critical gaps related to the underexplored mechanisms by which AI technologies construct, amplify, or mitigate consumer vulnerability; the limited empirical evidence on how privacy risks intersect with persuasion strategies; and the insufficient integration of ethical principles into the design of AI-powered marketing systems.

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

Potential topics

• Mechanisms by which AI technologies construct, amplify, or mitigate consumer vulnerability
• Privacy risks and their intersection with persuasion strategies
• Ethical principles in the design of AI-powered marketing systems
• Ethics of algorithmic persuasion in marketing

Timeline

• July 1, 2027: Submission window opens
• August 30, 2027: Submission deadline

Muhammad Imran Rasheed, University of Surrey

Barbara Rita Barricelli, Università degli Studi di Brescia

Waseem Ul Hameed, Universiti Utara Malaysia

This special issue examines how artificial intelligence systems are transforming workplace interactions, employee behavior, and organizational dynamics. While prior research has focused on AI adoption and performance outcomes, this collection addresses the human-centered dimensions of AI at work, including how employees develop trust in intelligent systems, experience AI-mediated processes, adapt their behaviors, and navigate issues such as technostress, autonomy, and cognitive load.

The special issue prioritizes behavioral, cognitive, and psychological perspectives on human-AI interaction in organizational settings. It seeks contributions that explore employee experiences with intelligent technologies, design of user-centered AI systems, transparency mechanisms, and the creation of psychologically sustainable digital work environments. The collection welcomes empirical, theoretical, and design-oriented research across quantitative, qualitative, and mixed-method approaches.

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

Potential topics

• Employee interaction with AI-enabled systems
• Human reliance, overreliance, and resistance toward AI
• Behavioral adaptation to intelligent technologies
• Human-AI collaboration and hybrid decision-making
• Trust formation in intelligent systems
• Algorithmic transparency and explainable AI
• Employee perceptions of AI fairness and accountability
• Behavioral responses to opaque decision systems
• Technostress, digital exhaustion, and AI fatigue
• Cognitive overload and information processing under AI systems
• AI dependency and employee wellbeing
• Digital distraction and attention fragmentation
• AI-supported autonomy and employee empowerment
• Algorithmic management and behavioral control
• Digital surveillance and monitoring technologies
• Behavioral consequences of automated performance systems
• Ethical design of workplace AI systems
• Human-centered intelligent systems
• Responsible AI implementation in organizations
• Designing psychologically sustainable digital work environments
• AI-enabled learning systems and digital upskilling
• Employee agility and adaptability in AI-enabled workplaces
• Behavioral implications of reskilling and task transformation
• Human learning behavior in technology-mediated contexts
• AI-supported teamwork and collaboration
• Virtual collaboration and intelligent communication systems
• Social interaction patterns in AI-mediated environments
• Team trust and coordination under intelligent systems
• AI in healthcare, hospitality, education, finance, and public services
• Gig work, platform labor, and digital employment systems
• Cross-cultural and cross-national comparisons
• Remote and hybrid work environments
• User experience (UX) of workplace AI systems
• Human-centered design of intelligent workplace technologies
• Conversational AI and intelligent assistants at work
• Adaptive and personalized workplace interfaces
• AI usability and user acceptance in organizational settings
• Interaction design for human-AI collaboration
• Human oversight and human-in-the-loop systems
• Trust calibration in intelligent systems
• Employee engagement with AI-enabled technologies
• Interface design for responsible and ethical AI use
• User perceptions of agency, control, and autonomy in AI-mediated work environments

Timeline

• July 31, 2027: Manuscript deadline