Artificial Intelligence in Education and Scientific Research: "Present Challenges and Future Opportunities"

Abstract

With the rapid expansion of Artificial Intelligence (AI) tools such as large language models, generative writing assistants, and data analysis systems, these technologies have become an integral part of research and educational processes. This study aims to analyze the reality of AI use in education and scientific research, while exploring the most prominent technical opportunities and ethical and regulatory challenges associated with this use within the academic environment. The study adopts a descriptive analytical approach, supported by a qualitative analysis of scientific literature published between 2019 and 2025, with the aim of classifying the most common applications at various stages of scientific research, such as hypothesis generation, academic writing, and statistical analysis. The results revealed tangible opportunities to improve researchers' efficiency, reduce completion times, and support non-English-speaking researchers. Serious ethical challenges were also identified, such as unintentional plagiarism, data bias, and lack of transparency in generative processes, along with the absence of a unified regulatory framework in most scientific institutions to regulate this use. In light of this, the paper proposes a number of recommendations, most notably: establishing clear institutional policies, training and empowering researchers academically and technically, and developing more transparent tools based on the principles of scientific research ethics. This will help ensure balanced use of this technology without compromising the essence of the academic process.