FAU Study Highlights Gaps in Journal Guidance on Responsible AI Use

As artificial intelligence tools become more common in scholarly work, new research from Florida Atlantic University’s College of Education finds that education journals are increasingly standardizing AI policies that emphasize regulation over practical guidance.

In a recent white paper, Scoping Review of Journal AI Policies in Education Research, Elizabeth Villares Sacks, Ph.D., professor and chair, Department of Counselor Education, and John E. Critelli Jr., Ph.D., clinical instructor and director of PROPEL (Principal Rapid Orientation and Preparation in Educational Leadership), Department of Educational Leadership and Research Methodology, examined AI-related policies across 81 peer-reviewed journals frequently used by College of Education faculty.

The analysis found that just 9% of the journals had a journal-specific AI policy, while 58% deferred to publisher-level guidance. Nearly one-third of the journals reviewed had no AI policy in place at the time of the study.

While AI policies are becoming more standardized across publishers, the authors conclude that most remain largely regulatory in nature. Existing policies tend to focus on disclosure requirements, prohibitions and author accountability, offering few operational definitions or practice-ready examples to guide researchers. Assistive uses of AI, such as grammar checks or language editing, are more commonly permitted, while generative uses — including drafting text or conducting analysis — are often restricted or explicitly prohibited.

Across the full sample, the researchers identified only 14 distinct governing AI policies, most originating from a small group of major academic publishers. This concentration promotes consistency but provides faculty and graduate students with limited direction on how to integrate AI responsibly into research workflows.

The authors recommend that universities take a more active role in defining responsible AI use within graduate education, supporting transparency through clear disclosure practices and offering guidance that reflects disciplinary differences. As AI continues to reshape academic research, they argue that policy frameworks should move beyond enforcement to offer guidance on ethical judgment, accountability and scholarly integrity.