Calls for Papers

ISR Special Issue: Generative AI and New Methods of Inquiry in Information Systems Research

Special Issue Editors

Ahmed Abbasi (University of Notre Dame)
Martin Bichler (Technical University of Munich)
Ram Gopal (University of Warwick)
Elena Karahanna (University of Georgia)
Suprateek Sarker (University of Virginia)

Due Date: September 7, 2026

Motivation and Scope

Generative Artificial Intelligence (GenAI) is rapidly reshaping not only organizations, markets, and technologies, but also the practice of scientific research itself (e.g., Gopal et al. 2025). Large language models, multimodal foundation models, and increasingly agentic AI systems now participate in activities such as literature discovery, theorizing, data analysis, simulation, coding, and writing.

This Special Issue (SI) seeks papers that push the boundaries of what can be achieved through innovative, rigorous, and responsible use of Generative AI in the information systems research process. Rather than focusing on GenAI solely as an object of empirical study, the SI emphasizes GenAI as a research collaborator, instrument, and infrastructure.

The ambition of the SI is twofold:

• To publish a small number of exemplary papers that demonstrate novel research capabilities enabled by GenAI.
• To advance shared principles, frameworks, and practices that will shape how information systems research is conducted and reported in an era of human–AI collaboration.

What Makes a Submission Appropriate for This Special Issue?

The SI is not intended to be a general outlet for any study that uses GenAI. GenAI must be constitutive of the research contribution—not merely supportive. The central theoretical, methodological, or design advance should depend on the capabilities of generative or agentic systems.

Submissions must satisfy both of the following criteria:

• Exemplary and Central Use of Generative AI: GenAI must make a substantive and consequential contribution in the research process—enabling outcomes that would be difficult, infeasible, or qualitatively different without it.
• Strong Scholarly Contribution to Information Systems: Each paper must meet the high standards of Information Systems Research, including clear theoretical, methodological, or design contributions to Information Systems.

Authors must explicitly document and reflect on how GenAI was used in the research process, including its benefits, limitations, risks, and the role of human judgment. Examples of papers that are not appropriate for the special issue:

• Pure performance benchmarks of GenAI models without IS insight.
• Papers where GenAI is only a data preprocessing convenience.
• Opinion pieces without empirical, analytical, or design grounding.
• Studies treating GenAI solely as the object of the study (e.g., its impact, adoption/use, or design that are not related to research-process problems/tasks).

GenAI Contributions of Interest

We welcome submissions across the full range of IS research traditions, including:

A. Illustrating New Research Methods and Capabilities

• Hybrid human–AI workflows for coding, classification, or sensemaking.
• GenAI-supported measurement development, construct validation, or scale refinement.
• GenAI-supported survey design, sampling, and survey administration.
• GenAI-supported experimental design, treatment generation, and implementation.
• GenAI-supported computational theory construction.
• Simulation, agent-based modeling, or scenario generation.
• GenAI-enabled qualitative analysis, theory building, or inductive discovery.
• GenAI-assisted econometric modeling, estimation, or robustness analysis.
• AI-supported proof search, counterexample generation, or equilibrium exploration.
• Discovery or validation of analytical models using generative simulation.
• GenAI-assisted testing of operational utility and/or design validity.

B. Highlighting Research Artifacts, Tools, and Infrastructures

• Design and evaluation of GenAI-based tools for IS research.
• Reproducible pipelines, benchmarks, and evaluation harnesses.
• Systems supporting transparency, provenance, and verification.

A reflective account of the human–AI collaboration involved and, more importantly, of the substantive and consequential contribution of GenAI to the research process must be included in the main body of the paper.

GenAI Use Appendix: Transparency and Documentation Expectations

Transparency is a core evaluation criterion. Each submission should document in a replicable way the technical details of how GenAI was used. Technical details should be provided in a separate GenAI Use Appendix describing:

• Tools/models used (versions and access dates).
• Stages of the research process involved.
• Prompting strategies or agentic workflows.
• Nature of human oversight and verification.
• Limitations or failure modes encountered.
• Experiences with hallucination, fabricated content, etc.

Authors may find it useful to structure the GenAI Use Appendix around a small number of guiding questions (e.g., models used, stages of involvement, verification steps), though no fixed template is required. However, the appendix should be easily auditable and replicable.

Innovating the Review Process

The editorial team will experiment with GenAI to augment—never replace—human judgment. This may include identifying inconsistencies, verifying citations, or enhancing consistency across reviews. All editorial decisions will remain fully under human control.

No submitted manuscripts or reviewer reports will be used to train models, and all AI support will operate within ISR’s confidentiality and data-handling standards.

Submission Requirements

• Manuscript: Prepared according to Information Systems Research guidelines. The manuscript should include a reflective account of the substantive and consequential contribution of GenAI to the research process, especially how it has enabled outcomes that would be difficult, infeasible, or qualitatively different without it.
• GenAI Use Appendix PDF: A separate appendix that documents in a replicable way the technical details of how GenAI was used.
• GenAI Code Zip: If applicable, containing all code scripts for agentic frameworks, fine-tuning, automating GenAI pipelines, etc.
• Optional Research Artifacts: Authors are encouraged to submit other relevant code, prompts, or datasets.

Projected Timeline

Submission Deadline: September 7, 2026
First-round Decisions: November 20, 2026
ICIS Workshop: December 13–16 (exact date TBA), 2026
Optional Online Workshop: January 15, 2027
Final Version Submitted: February 15, 2027
Final Decisions: May 1, 2027

In summary, this Special Issue invites bold, reflective, and forward-looking contributions that help articulate what the information systems research process can become in an age of generative machines. We anticipate that accepted papers will serve as reference points for future methodological standards in IS research.

Reference

Gopal, R., Li, J., Reimer, K., Sarker, S., Singh, P. V., Susarla, A., Bichler, M., Thatcher, J. B. “Inventing with Machines: Generative AI and the Evolving Landscape of IS Research,” Information Systems Research, Vol. 36, No. 4, 2025, pp. 1949–1967.