Abstract

Artificial intelligence technologies are transforming the way scientific research is reviewed to make verification processes more accurate, efficient, and objective. This paper considers AI's role in testing the veracity of academic studies, with a focus on concerns of research fraud, data integrity, and adherence to ethical and methodological standards. Powered by AI, emerging tools allow the tracing of anomalies, inconsistencies, and potential biases in published research works with the help of NLP algorithms and machine learning models. It is also applied to various fields such as plagiarism detection, statistical analysis checking, and the identification of fabricated or manipulated data. However, flaws regarding the use of AI technologies include relying too much on automation of systems and requiring human supervision. Academic institutions and journals can further enhance scientific research to make it more credible, transparent, and coherent-a reason to be trusted globally-by integrating AI into its evaluation process.