Purpose

In light of the limited published literature addressing the complex ethical, epistemic and systemic implications of artificial intelligence (AI) integration in research, this paper aims to build foundational conceptual frameworks that clarify these challenges. It aims to provide a comprehensive examination of the multifaceted issues involved and to propose principled strategies for responsible AI adoption that preserve scholarly integrity and foster sustainable research practices. It is hoped that this effort can start academic discussions on how AI can be used more responsibly for guarding academic integrity.

Design/methodology/approach

This study adopts a conceptual approach to explore the ethical, epistemic and systemic impacts of AI in scholarly research. Due to the emerging nature of this field, the analysis draws on a selective review of key academic and policy sources. Synthesizing diverse perspectives from research ethics, science and technology studies and critical AI scholarship, the paper identifies core challenges and proposes strategies for responsible and equitable AI adoption.

Findings

While AI tools dramatically enhance literature synthesis, data analysis and academic writing, they simultaneously introduce risks such as misattribution, data fabrication and erosion of trust. AI disrupts traditional notions of authorship and originality, raising urgent questions about accountability. Without careful human oversight, it risks compromising the reliability of research. Institutions must update policies to promote ethical use and ensure fair access to AI tools.

Originality/value

This paper offers a timely and comprehensive synthesis of the multifaceted ethical, epistemic and systemic challenges posed by AI integration in scholarly research. The study bridges technological innovation with foundational academic values and charts a clear path for responsible AI adoption, emphasizing human oversight, transparency and equitable access. Unlike prior studies that focus narrowly on technical capabilities or isolated ethical concerns, this work situates AI within the broader cultural and institutional ecosystems, providing actionable insights for researchers, policymakers and academic leaders committed to safeguarding the integrity and future of scholarship.

Keywords: Artificial intelligence, Ethics, Research ethics, Information ethics, Scholarly integrity,Authorship, Artificial agents, Epistemic responsibility, Academic integrity, Knowledge production,Transparency, Academic policy, Authorship ethics, AI and authorship ethics