The integration of technology into science in general and scientific publishing, including both academic writing by scientists and the preparation of publications by publishers, has been a well-established practice since the mid-20th century. Over many decades, academic writing has been supported by personal computer applications for formatting, data visualization, grammar checking, and, recently, predictive text (supported by online services). These tools are now universally accepted, and their use is generally not viewed as a threat to academic integrity. (Perlo, 2026). Artificial Intelligence (AI) represents only the latest technological evolution designed to support the scientific community and its core activities.

Recently, the accessibility of AI tools, online and offline, has accelerated the integration of AI into various scientific fields. Earlier computer systems including expert systems have been superseded by machine learning, deep learning, chatbots and generative AI. Researchers now use AI tools like chatbots to develop research protocols / plans, process research data, and validate empirical results. AI tools also assist in conducting literature reviews, manuscript preparation by refining grammar, particularly for non-native speakers of the English language, automating citations creation, and extracting insights from large number of information resources (Ajiye & Omokhabi, 2025), including already published academic papers and books, available online, mostly in open access. These AI tools also facilitate research results visualizations, content summarization and restructuring, and the generation of abstracts and multimedia (Kocak, 2024). AI has also been used in the process of peer review, for finding potential reviewers and detecting instances of plagiarism but it has also introduced issues around accountability and transparency of the process as well as reviewers’ bias, so human oversight is still (Ateriya et al., 2025).

The rise of use of generative AI tools for content creation blurs the distinction between original authorship and machine created content intended for publishing. Over-reliance on AI tools may lead to academic dishonesty and a loss of intellectual rigor by undermining critical thinking and writing skills (Ajiye & Omokhabi, 2025). Major concerns additionally include ethical dilemmas throughout the research lifecycle like fairness, justice, and accountability (Vuyani, 2025) and reproducing biases, spreading misinformation, plagiarism, and lack of transparency (Cárdenas, 2026) as well as intellectual property issues (Ajiye & Omokhabi, 2025; What is publication ethics?; Ateriya et al., 2025).

The expanded use of AI tools in scientific publishing appears inevitable for both authors and publishers. To support researchers, journals should establish clear guidelines for the use of such technology. As Kocak (2024) notes, drafting these guidelines is difficult because ethical boundaries are rarely “black and white.” Nevertheless, formal guidance is essential; a lack of regulation may encourage the proliferation of “paper mills”, which produce AI-generated manuscripts often based on fraudulent research, and other forms of misconduct.

This poster examines the author’s dilemma of using AI supported tools in scientific publishing. It is based on a literature review and cases of publicly available AI resources or tools used by scientists during academic manuscript preparation and by journals and scientific publishers for validation of received manuscripts and for publishing processes.