Objective: The emergence of Artificial Intelligence (AI) in education, despite its vast potential to enhance teaching and learning, has introduced critical challenges to maintaining academic integrity. This study aimed to systematically identify AI-related challenges to academic honesty, explore influencing factors, and review educational interventions addressing these issues.
Method: A systematic review was conducted in accordance with the PRISMA model. The Scopus database was searched using keywords related to “artificial intelligence,” “academic dishonesty,” “formal education,” and “intervention.” Out of 322 initially identified studies, 33 empirical papers met the inclusion criteria after screening and full-text evaluation.
Results: The findings revealed five major categories of AI-related academic integrity challenges: (1) ambiguity policy, (2) weakness of tools and difficulty of detection, (3) excessive use of AI, (4) threats to educational fairness and trust, and (5) declining learning quality. Conversely, effective interventions reported by teachers and instructors encompassed assessment and task redesign, ethical and skill-based empowerment, responsible AI integration, enhancement of human interaction, detection strategies, policy clarification, and prevention and punishment.
Conclusions: The study concludes that safeguarding academic integrity in the age of AI requires redefining the teacher’s role, developing techno-ethical literacy, and establishing coherent institutional policies that balance innovation with ethical responsibility.