The rapid integration of artificial intelligence (AI) into higher education has revolutionized

teaching and assessment practices, yet it has also presented significant challenges to maintaining

academic integrity. The study focuses on higher education institutions in Sri Lanka. The purpose

of this study is to analyse the effectiveness of academic integrity practices in the context of AI

technologies within the higher education sector of Sri Lanka. Specifically, it examines AI-driven

assessment methods, concerns about plagiarism detection tools, and the effectiveness of current

certification methods in preserving academic integrity. A structured online questionnaire was

administered to 147 participants from diverse academic backgrounds and institutions across

Sri Lanka. Quantitative data were collected through extracted from Likert-scale responses and

demographic data. Hypothesis tests including the chi-square test and ANOVA were used to

assess the statistical significance of differences in perceptions among demographic variables.

The survey findings suggest mixed views on the effectiveness of academic integrity practices

in the AI age. While 64% of respondents expressed confidence in AI-driven assessment

methods, they raised particular concerns about the potential for algorithmic biases to influence

assessment fairness (χ2 (1) = 15.32, p < 0.001). Additionally, 79% of participants highlighted

the importance of increasing transparency and accountability in AI-based theft detection tools.

Statistical analysis reveals notable differences in perceptions based on participants’ academic

discipline and years of experience in higher education. In particular, respondents from

engineering disciplines showed greater confidence in AI technologies compared to those from

humanities and social sciences (F (2, 144) = 5.78, p < 0.01). Based on the research findings,

strategic recommendations are made to address these challenges and enhance academic

integrity practices in AI development. This survey-method study provides empirical insights

and compelling statistical evidence on the evolving landscape of academic authenticity in

higher education in the context of hybrid AI technologies in Sri Lanka. It provides practical

recommendations for institutions and policymakers to address ethical challenges and effectively

promote honesty in educational settings