What AI Should and Should Not Do in Academic Publishing
Artificial intelligence is becoming a part of academic publishing, but its role needs clear limits. According to guidelines from major book publishers such as Omniscriptum, Elsevier, and Springer Nature, the AI should support researchers, not replace them.
When used responsibly, AI can make publishing faster, clearer, and intentional. When misused, it risks damaging trust, authorship, and academic integrity.
Where AI genuinely helps researchers
AI works best in the background, handling tasks that are time-consuming but not intellectually creative.
It can support language quality by improving grammar, clarity, and flow, especially for authors working in a second language. It can also help organise ideas, suggest outlines, and assist with early-stage brainstorming, as long as the research questions and arguments remain the author’s own.
Many publishers also accept AI for practical checks. This includes:
- reviewing structure;
- ensuring required sections are present;
- checking formatting consistency;
- and supporting compliance with submission guidelines.
Used carefully, AI can also assist with literature navigation, summaries, and technical tasks such as code formatting or data visualisation, provided everything is verified by the researcher.
At Omniscriptum, AI is applied in exactly this way. It’s in progress to be used to streamline the submission process, support clearer presentation, and reduce administrative friction, while keeping full control in the hands of the author. The research itself remains untouched, and they keep the publishing for free.
Where AI must stop
Ieva Konstantinova, CEO of Omniscriptum, explains that the goal of using AI in academic publishing is not to interfere with research itself, but to remove unnecessary barriers around it:
“AI should never replace the researcher’s intellectual work. Its real value lies in supporting authors with the parts of publishing that are time-consuming but not scholarly, such as submission workflows, presentation, and administrative tasks. When used responsibly, AI allows research to be evaluated for its academic merit rather than being slowed down by avoidable technical issues.”
Final editorial decisions must always be made by humans, not automated systems.
Using AI to create or alter research content undermines accountability and is considered unethical across the publishing industry.
The principles that matter the most
Regardless of the publisher, 3 main principles should stay consistent.
- Human accountability
The author is fully responsible for the accuracy, originality, and integrity of the work, including any AI-assisted elements.
- Transparency
When AI tools are used, their role should be disclosed clearly, including what was used and for which tasks.
- Data protection
Unpublished research, confidential material, or sensitive data should never be uploaded into public AI tools.
A practical takeaway for authors who want to publish their thesis as a book
AI is not the problem. Unclear boundaries are.
Used as editorial and administrative support, AI helps strong research move through the publishing process more smoothly. Used as a shortcut for intellectual work, it becomes a liability.
Publishers like Omniscriptum are investing in AI to improve user experience, not to dilute academic standards.
The goal is simple: less time spent on forms, formatting, and presentation issues, and more focus on the research itself.
The future of academic publishing is faster and more efficient, but it remains firmly human at its core.
