JIT SI on CNoW

Journal of Information Technology

Call for Papers for a Special Issue on

Human-AI Collaboration, Emerging Digital Work Configurations and the Changing Nature of Work

Alexander Richter, Victoria University of Wellington – New Zealand (corresponding editor, alex.richter@vuw.ac.nz)

João Baptista, Lancaster University – UK & Nova SBE – Portugal

Ella Hafermalz, Vrije Universiteit Amsterdam – The Netherlands

Mareike Möhlmann, Bentley University – USA
Daniel Schlagwein, The University of Sydney – Australia (JIT editor)

Mari-Klara Stein, Tallinn University of Technology – Estonia

Digital technologies, in particular artificial intelligence (AI), are reconfiguring how, where, and when work gets done (Bailey and Barley 2020; Berente et al. 2021), marking a shift from tools designed to support human tasks to agentic systems that collaborate with and even manage human workers. AI technologies are evolving to work autonomously or within hybrid collaboration systems of human and digital agents (Möhlmann et al. 2021; Stelmaszak et al. 2024).

Research on AI and human-AI collaboration has advanced from studying AI that supports human tasks (Jackson and Panteli 2024) to AI agents’ ability to make independent management decisions and regulate and manage human work (Tarafdar et al. 2023; Richter and Schwabe 2025). The future of working with AI is, however, still unknown and emergent (Agerfalk et al. 2022; Benbya et al. 2021), with both utopian and dystopian perspectives shaping our understanding of opportunities and challenges of their adoption and use in organizations, work and other spheres of our lives (Carroll et al. 2024).

Prior research has helped make sense of and anticipate important side effects of AI-driven management (Baiocco et al. 2022; Stark and Broeck 2024), new forms of hidden and unrecognized ‘meta-work’ performed by employees (Klein and Watson-Manheim 2021), and the ‘ripple effects’ of introducing such technologies to the workplace. For example, research has focused on the reconfiguration of spatial-temporal dimensions and ‘ways of seeing’ in the workplace (Willems and Hafermalz 2021), tensions between craft and mechanical work (Hopf et al. 2023), and a wide range of unintended effects in work contexts such as loss of critical thinking (Mayer et al. 2020) and changes in how human work is coordinated as well as the authority and values that underpin it (Benbya et al. 2020).

In addition to such scholarship, several calls and arguments point to limitations of existing knowledge and invite new research to develop relevant theories and methods to study human-AI collaboration and how this is reconfiguring work. For example, theories that take a relational view of AI, recognize that its functionality and affordances emerge dynamically and with use (Hinds and von Krogh 2024) and therefore specific systems and configurations need to be studied in-situ. Further, emergent research on AI safeguards argue for AI’s progressive encapsulation and new forms of socio-technical reversal (Fischer et al. 2023) and socio-technical envelopment of AI to allow organizations to capture the value of AI while minimising exposure to risks (Asatiani et al. 2021). Such research is important in informing scholarship and practice, influencing design considerations to develop responsible and ethical AI systems (Vassilakopoulou et al. 2022), and help with retaining humans-in-the-loop in AI-centric processes (Grønsund and Aanestad 2020), which is needed to manage, for example, emerging tensions between automation and augmentation (Holmström and Carroll 2024; Raisch and Krakowski 2021).

Theme 1: This special issue is particularly interested in research that explores the unique nature of human-AI collaboration, emerging AI technologies and ecosystems (Retkowsky et al. 2024) and how AI changes human work practices and its implications. That is, this special issue seeks new theoretical perspectives or methods and novel unified approaches for the study of AI (Bailey and Barley 2020).

Theme 2: This special issue is open to innovative research that helps understand emerging digital work configurations (Baptista et al. 2020) that are reshaping the functioning and structures of organizations, as well as to research on new and future forms of digital working and organizing (Wang et al. 2020). Thus, we also welcome studies focusing on various (non-AI) digital technologies that are altering human work practices, such as non-learning algorithms, blockchain technologies, robotics, and remote working solutions, even when AI is discussed in the broader context, more in the background, or not at all.

Our interest in AI-human collaboration and the changing nature of work more broadly builds on discussions in the growing community of the AIS Special Interest Group on the Changing Nature of Work (AIS CNoW 2024) and the various related workshops and IS conference tracks on AI, Changing Nature of Work, Digital Work, Future of Work etc. As members of this community, we have seen a growing interest in exploring the evolution of AI and other emergent digital technologies as synergistic partners amplifying (or challenging) human creativity, judgment and contextual understanding. Digital technologies are set to transform work practices, organizational structures and decision-making (Shrestha et al. 2019), while raising critical questions about the value of existing theories and frameworks to study these meta-human phenomena (Lyytinen et al. 2021) as well as their human, societal, ethical and environmental implications in practice.

This special issue invites submissions that critically examine the current and expected future effects of human-AI collaboration and other emerging digital work configurations (Richter and Richter 2024). It seeks theoretical, empirical, and design-oriented contributions that study the transformative potential of digital-human collaboration. This special issue seeks work that inspires innovative strategies, ethical solutions, and sustainable models for AI-and-digitally-driven work, and informs future digital work scenarios (Wang et al. 2020). The special issue takes a forward-looking perspective, aiming to gather research that follows good research practice in the use of AI (Kulkarni et al. 2024; Schlagwein and Willcocks 2023; Susarla et al. 2023) but is open to  work on developing prospective scenarios and actively creating preferable futures (Schlagwein et al. 2024) – Future Making. The special issue welcomes all types of research papers. This may involve developing new concepts, and ways of theorizing or integrating concepts from different fields and in using innovative methods and approaches to capture the role of technology in the changing nature of work and the future of organizing.

Topics of Interest

Topics of interest include but are not limited to:

Emerging Human-AI Work Configurations

§  Capture and conceptualize emergent configurations and types of interactions and collaborations between humans and AI.

§  Exploring the shift from human-assisted technology to technology-managed human work and anticipate future trends.

§  Showcasing the integration and adoption of AI in complex work environments and suggest how to manage these processes.

Effects of AI and Agentic Systems in the Workplace, Work, and Organizing

§  Study the effects of AI-driven solutions and immersive technologies on collaboration, communication, and productivity in organizations.

§  Explore longitudinal third-order effects of AI agents in work and social fabric of organizations.

§  Explore new forms of trust development in AI agents within the workplace.

Governance, Responsibility, and Ethics of AI Agents

§  Conceptualize risks and opportunities in integrating AI agents in human work.

§  Ethical challenges arising from the increased autonomy of AI systems in decision-making.

§  Explore and propose governance frameworks for ensuring fairness, transparency, bias, and accountability in human/AI collaborative work.

§  The influence of societal values on work practices, policies, and organizational culture, with a focus on sustainability and inclusivity.

Adaptive Practices and Human-AI Dynamics

§  Strategies for fostering effective and sustainable human-AI collaboration in hybrid and virtual workplaces.

§  Redefining roles and responsibilities in AI-integrated teams.

§  Designing machines as teammates.

§  Use cases, such as digital brainstorming agents, demonstrating the impact of human-AI interactions on team dynamics and creativity.

Strategic and Organizational Implications of Human-AI Collaboration

§  The effects of AI integration on organizational structures and workforce development.

§  Innovations in leadership and management practices to accommodate human-AI collaboration.

§  Long-term implications of AI as a collaborative partner on business models and resilience.

New Digital Work Configurations and Changing Nature of Work Beyond AI

§  Work exploring emerging or future digital work practices centred on the interplay between humans and digital agencies.

§  Algorithmic work and management and its implications for workers and organization.

§  New forms of working and organizing enabled, transformed or substantially changed by specific new digital technologies (research focused on a particular technology affecting multiple work practices).

§  Specific work configurations (e.g., digital nomadic, location-independent working and organizing) that is enabled by host of digital technologies (research focused on a particular work practice enabled by multiple digital technologies).

Theoretical and Methodological Advancements

§  Advancing theory of human-AI collaboration or the changing nature of work.

§  Methodologies for studying the emergent scenarios and futures around human-AI collaboration or the changing nature of work.

§  Critical or philosophical accounts of human-AI centred work.

§  Research with substantial policy implications on human-AI work advancements

§  Other types of conceptual, theoretical, methodological or philosophical contributions on the above topics.

Submission Timetable

Submissions due:                                                           15 Aug 2025 (firm deadline!)

Notifications (submissions):                                         15 Nov 2025

Workshops for papers invited forward will be held at ICIS 2025 (Dec 2025) and online (for author teams not attending ICIS).

Revisions due:                                                               1 Mar 2026

Notifications (revision 1):                                             1 May 2026

Second revision due:                                                     1 Aug 2026

Notifications (revision 2):                                             1 Oct 2026

Papers will be finally accepted or rejected after the second round of revision. Third-round revisions only in specific circumstances and will be advised by the Special Issue Editors at this time.

Target publication:                                                       1 Dec 2026 (or later)

Editorial Board

Submission Guidelines

JIT submission guidelines: https://journals.sagepub.com/author-instructions/JIN.

JIT submission site: https://mc.manuscriptcentral.com/jin.

Special issue authors must indicate in the submission comments and the cover letter that this is a submission to the special issue on ‘The Changing Nature of Work’.

References

AIS SIG CNoW 2024. 15th International Workshop on the Changing Nature of Work (CNoW), https://communities.aisnet.org/sigcnow/2024cnow.

Agerfalk, P., Conboy, K., Crowston, K., Lundström, J., and Jarvenpaa, S. 2022. Artificial Intelligence in Information Systems: State of the Art and Research Roadmap, Communications of the Association for Information Systems (50:6), pp. 420-438.

Asatiani, A., Malo, P., Per Rådberg, N., Penttinen, E., Rinta-Kahila, T., and Salovaara, A. 2021. Sociotechnical Envelopment of Artificial Intelligence: An Approach to Organizational Deployment of Inscrutable Artificial Intelligence Systems, Journal of the Association for Information Systems (22:2), pp. 325-352.

Bailey, D. E., and Barley, S. R. 2020. Beyond Design and Use: How Scholars Should Study Intelligent Technologies, Information and Organization (30:2), article 100286.

Baiocco, S., Fernandez-Macias, E., Rani, U., and Pesole, A. 2022. The algorithmic management of work and its implications in different contexts, JRC Working Papers Series on Labour, Education and Technology, No. 2022/02, European Commission, Joint Research Centre (JRC), Seville.

Baptista, J., Stein, M.-K., Klein, S., Watson-Manheim, M. B., and Lee, J. 2020. Digital Work and Organisational Transformation: Emergent Digital/Human Work Configurations in Modern Organisations, The Journal of Strategic Information Systems (29:2), article 101618.

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Carroll, N., Holmström, J., Stahl, B. C., and Fabian, N. E. 2024. Navigating the Utopia and Dystopia Perspectives of Artificial Intelligence, Communications of the Association for Information Systems (55) pp. 854-874.

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Jackson, S., and Panteli, N. 2024. AI-Based Digital Assistants in the Workplace: An Idiomatic Analysis, Communications of the Association for Information Systems (44:9), pp. 123-148.

Klein, S., and Watson-Manheim, M. B. 2021. The (Re-)Configuration of Digital Work in the Wake of Profound Technological Innovation: Constellations and Hidden Work, Information & Organization (31:4), article 100377.

Kulkarni, M., Mantere, S., Vaara, E., van den Broek, E., Pachidi, S., Glaser, V. L., Gehman, J., Petriglieri, G., Lindebaum, D., Cameron, L. D., Rahman, H. A., Islam, G., and Greenwood, M. 2024. The Future of Research in an Artificial Intelligence-Driven World, Journal of Management Inquiry (33:3), pp. 207-229.

Lyytinen, K., Nickerson, J. V., and King, J. L. 2021. Metahuman Systems = Humans + Machines That Learn, Journal of Information Technology (36:4), pp. 427-445.

Mayer, A.-S., Strich, F., and Fiedler, M. 2020. Unintended Consequences of Introducing AI Systems for Decision Making, MIS Quarterly Executive (19:4), pp. 239-257.

Möhlmann, M., Zalmanson, L., Henfridsson, O., and Gregory, R. W. 2021. Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control, MIS Quarterly (45:4), pp. 1999-2022.

Raisch, S., and Krakowski, S. 2021. Artificial Intelligence and Management: The Automation-Augmentation Paradox, Academy Management Review (46:1), pp. 192-210.

Retkowsky, J., Hafermalz, E., and Huysman, M. 2024. Managing a ChatGPT-Empowered Workforce: Understanding Its Affordances and Side Effects, Business Horizons (67:5), pp. 511-523.

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Schlagwein, D., Currie, W., Leimeister, J. M., and Willcocks, L. 2025. Digital Futures: Definition (What), Importance (Why) and Methods (How), Journal of Information Technology.

Schlagwein, D., and Willcocks, L. 2023. ‘ChatGPT et al.’: The Ethics of Using (Generative) Artificial Intelligence in Research and Science, Journal of Information Technology (38:3), pp. 232-238.

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Stelmaszak, M., Möhlmann, M., and Sørensen, C. 2024. When Algorithms Delegate to Humans: Exploring Human-Algorithm Interaction at Uber, MIS Quarterly https://doi.org/10.25300/MISQ/2024/17911

Susarla, A., Gopal, R., Thatcher, J. B., and Sarker, S. 2023. The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly Activities in Information Systems, Information Systems Research (34:2), pp. 399-408.

Tarafdar, M., Page, X., and Marabelli, M. 2023. Algorithms as Co-Workers: Human Algorithm Role Interactions in Algorithmic Work, Information Systems Journal (33:2), pp. 232-267.

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