Theorizing the Data-AI Nexus

Call for Papers

Theorizing the Data-AI Nexus

Journal: European Journal of Information Systems
Publisher: Taylor & Francis Group
Special Issue
Manuscript Submission Deadline: 15 January 2027

European Journal of Information Systems (EJIS) invites submissions for a Special Issue advancing theoretical and empirical understanding of the data-AI nexus—the increasingly intertwined relationship between data, artificial intelligence, organizational practices, and social processes.

About the Special Issue

Contemporary AI systems increasingly learn from, operate through, transform, and generate data. This creates a recursive relationship in which data shape what AI systems can know and do, while AI systems simultaneously influence how data are produced, classified, interpreted, and governed.

The Special Issue seeks to move beyond purely technical accounts of AI by examining its socio-technical, organizational, institutional, and epistemic dimensions. It particularly encourages theoretically ambitious and empirically rich research that considers data and AI as mutually constitutive rather than independent phenomena.

Topics of Interest

Submissions may address, but are not limited to:

• Data and AI co-constitution

• Data selection, curation, and labelling

• Historical accumulation of organizational data

• Epistemological assumptions in AI development

• AI as a producer and transformer of data

• AI-generated and synthetic data

• Recursive AI training using AI-generated data

• Data quality and provenance

• AI agents as organizational actors

• Autonomous and semi-autonomous AI agents

• Data detached from social and professional practice

• Decontextualized data and organizational decision-making

• Institutional knowledge and AI

• Organizational memory and AI systems

• Collective sensemaking

• Human-AI interaction and collaboration

• Data work in organizations

• Data cleaning, transformation, and evaluation

• Model development and fine-tuning practices

• Synthetic-data pipelines

• Generative AI integration into organizational workflows

• AI governance and accountability

• Responsible AI

• Classification and infrastructuring

• Data-AI recursion and performativity

• Intelligence as a relational and emergent phenomenon

• Data quality and ground truth

• AI training and model performance

• AI and societal outcomes

• AI and grand challenges

• Data and AI in scientific, environmental, and planetary contexts

Key Research Themes

Data and AI Co-Constitution
Research examining how datasets, computational architectures, curation practices, classification systems, and historical data jointly shape what AI systems can know and accomplish.

AI as a Data-Maker
Studies conceptualizing AI as an active producer, organizer, filter, and transformer of data, including research on synthetic data and autonomous AI agents.

Data Decoupled from Practice
Research exploring what happens when data become separated from situated knowledge, lived experience, institutional practices, professional judgment, or established meaning-making processes.

The Social Life of the Data-AI Nexus
Studies examining how data travel through organizations, accumulate classifications, become embedded in organizational memory, and interact with institutional histories and collective sensemaking.

Preferred Article Types and Methods

The Special Issue welcomes:

• Empirical Studies

• Conceptual Contributions

• Philosophical Analyses

• Methodological Contributions

• Opinion and Commentary Pieces

A broad range of paradigms and methodologies is encouraged, including interpretivist, processual, critical, computational, design-science, and positivist approaches. Studies may operate at individual, group, organizational, inter-organizational, or societal levels.

Relevant methods may include trace-data analysis, computational methods, ethnography, archival research, experimental designs, and other approaches suitable for examining the socio-technical relationship between AI and data.

Important Dates

• Initial Paper Submission Deadline: 15 January 2027

• First-Round Author Notification: 15 April 2027

• Workshop for First-Round Authors: May 2027, during the Theorizing Data & AI Conference

• Invited Revisions Deadline: 31 July 2027

• Second-Round Author Notification: 31 October 2027

• Final Revision Deadline: 15 January 2028

Submission Information

Submissions should make the Information Systems (IS) artefact central to the theoretical contribution. The editors particularly encourage work that develops original conceptual insights rather than only incremental extensions of established models. Interdisciplinary studies are welcome where they maintain a clear connection to Information Systems scholarship.

For questions about the suitability of a manuscript, authors may contact Lauren Waardenburg at waardenburg@essec.edu, Cristina Alaimo at alaimo@essec.edu, or another Special Issue Editor.

Submit to European Journal of Information Systems

European Journal of Information Systems – Instructions for Authors

European Journal of Information Systems – Journal Page

Special Issue Editors

Cristina Alaimo
ESSEC Business School

Lauren Waardenburg
ESSEC Business School

Jonny Holmström
Umeå University

Lior Zalmanson
Tel Aviv University

Reza M. Baygi
VU Amsterdam

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