Artificial Intelligence (AI) Usage Policy

Responsible Use of Artificial Intelligence

Artificial Intelligence (AI) & Generative AI Policy

Ilomata International Journal of Management supports responsible AI use while maintaining human accountability, research integrity, confidentiality, transparency, managerial responsibility, and scholarly independence.

HUMAN ACCOUNTABILITY AI DISCLOSURE CONFIDENTIALITY
✓ AI may assist manuscript preparation. ✓ Meaningful AI use must be disclosed.
✓ Authors remain fully responsible for all content. ✕ AI tools cannot be authors or co-authors.
✕ Reviewers/editors must not upload confidential manuscripts or organizational data to AI. ✕ AI must not replace human scientific, managerial, or editorial judgment.
1. Use of AI by Authors

Authors may use generative AI or AI-assisted technologies to support activities such as language improvement, literature organization, idea development, qualitative coding assistance, business-data exploration, managerial-data organization, forecasting support, or manuscript preparation. AI tools must not replace the authors' critical thinking, scholarly judgment, managerial interpretation, strategic reasoning, analysis, or original contribution.

Authors are responsible for:

  • verifying factual accuracy and checking references generated by AI;
  • reviewing and substantially editing AI-assisted content;
  • checking for bias, hallucination, fabricated citations, misleading business information, or unsupported managerial recommendations;
  • protecting confidential organizational data, employee information, customer records, strategic plans, financial information, proprietary business data, copyrighted material, and unpublished information;
  • independently validating AI-assisted classifications, forecasts, business analyses, strategic recommendations, calculations, or interpretations; and
  • ensuring that the final manuscript represents the authors' own scholarly work.
Important: Authors remain fully responsible for the accuracy, originality, integrity, managerial relevance, and ethical compliance of all submitted content, regardless of whether AI tools were used.
2. AI Disclosure

Meaningful use of generative AI in manuscript preparation must be disclosed in a separate AI Declaration. The declaration should identify the tool used, its purpose, and the extent of human review and oversight.

Suggested AI Declaration
The authors used [tool/model name] for [specific purpose]. All AI-assisted outputs were critically reviewed, verified, and substantially revised by the authors. The authors take full responsibility for the accuracy, integrity, originality, and ethical appropriateness of the manuscript.

Basic spelling, grammar, or punctuation checks do not normally require disclosure. If AI forms part of the research method, organizational analysis, strategic analysis, forecasting, decision-support process, human-resource analytics, operational analysis, qualitative coding, predictive modeling, or data analysis, its use must be described in sufficient detail in the Methods section.

3. AI and Authorship

AI tools, chatbots, and language models must not be listed as authors or co-authors. Authorship requires human responsibility for the integrity of the work, approval of the final manuscript, accountability for its content, and the ability to respond to questions regarding the research, organizational context, analytical methods, and conclusions.

4. AI-Generated Images, Figures & Artwork

Generative AI must not be used to create, manipulate, obscure, remove, or introduce features in research images, organizational charts, dashboards, screenshots, business-process diagrams, figures, visualizations, or other visual evidence in a manner that misrepresents the underlying research data or organizational context.

An exception may apply when AI-assisted visualization, image generation, diagram generation, synthetic-data visualization, or automated design is part of the research design or methodology. In such cases, authors must describe the tool, model/version, procedure, inputs, validation process, and its role in generating or interpreting research data in the Methods section.

5. Use of AI by Reviewers

Submitted manuscripts are confidential documents. Reviewers must not upload manuscripts, manuscript excerpts, organizational records, employee data, strategic plans, proprietary business information, supporting files, or review reports into public generative AI systems.

Peer review is a human scholarly responsibility. AI tools must not be used to generate scientific assessments, independently evaluate management theories, assess methodological quality, judge managerial implications, or determine review recommendations. Reviewers remain personally responsible for the content, accuracy, fairness, methodological soundness, and integrity of their reports.

6. Use of AI by Editors

Editors must not upload submitted manuscripts, confidential correspondence, reviewer reports, author responses, unpublished organizational data, proprietary business information, employee records, or editorial decision letters into public generative AI systems.

AI must not replace human editorial judgment or be used to determine acceptance, revision, or rejection. Editors remain fully responsible for editorial evaluation, reviewer selection, confidentiality management, communication, conflict-of-interest management, and final publication decisions.

7. AI in the Publication Workflow

The journal may use appropriately controlled AI-assisted technologies for limited technical and administrative purposes, with human oversight.

✓ Technical submission checks ✓ Duplicate-submission detection
✓ Research-integrity screening ✓ Reviewer matching support
✓ Copyediting and production assistance ✓ Identification of technical inconsistencies
Human oversight remains mandatory throughout all editorial and publication processes.

Violations & Consequences

Misuse or undisclosed use of AI may be handled under the journal's publication-ethics procedures. Examples include fabricated references, invented survey responses, fabricated organizational data, undisclosed AI-generated analysis, false business forecasts, unauthorized processing of employee or corporate information, manipulated managerial evidence, or inappropriate dependence on AI-generated strategic recommendations. Depending on severity, actions may include request for clarification, manuscript rejection, correction, retraction, institutional notification, or restrictions on future submissions.

Policy Governance

This policy follows principles of transparency, accountability, confidentiality, human oversight, fairness, intellectual-property protection, organizational privacy, responsible decision-making, data protection, and research integrity. It will be reviewed periodically as AI technologies, management-research practices, organizational analytics, and international publication standards evolve.