The integration of artificial intelligence (AI) into scientific research has significantly enhanced efficiency and accuracy but also introduced new forms of academic misconduct, such as data fabrication and text plagiarism. This study highlights the challenges posed by AI in maintaining research integrity and proposes solutions to address these issues. The paper emphasizes the need for the academic community to strengthen ethical norms, enhance researcher qualifications, and establish rigorous review mechanisms. Key recommendations include developing comprehensive AI research integrity guidelines, implementing mandatory AI ethics and integrity training for researchers, and fostering international collaboration to develop unified ethical standards for AI in research. AI technologies, particularly in data analysis, literature generation, and experimental design, have transformed scientific research by improving efficiency and accuracy. However, the misuse of AI tools has led to serious ethical concerns, including data fabrication, text plagiarism, and lack of transparency. These issues are exacerbated by the sophistication of AI algorithms, which can generate convincing but false data and texts. Empirical case studies demonstrate the potential for AI to be misused in research, undermining the authenticity and reliability of scientific findings. To combat these challenges, the paper suggests the use of AI monitoring tools and techniques, such as data integrity checkers, plagiarism detection software, and transparency tools for AI algorithms. These tools help detect and prevent unethical practices in research. Additionally, education and training programs are crucial for enhancing researchers' awareness of ethical AI practices. These programs should cover AI ethics, data management, and the responsible use of AI technologies. The paper also emphasizes the importance of formulating and implementing policies and procedures related to research integrity. These policies should ensure the ethical use of AI in research, including the development of a code of conduct, establishment of review mechanisms, and the creation of a regulatory framework for research integrity. The study concludes that while AI offers significant opportunities for scientific advancement, it also presents new challenges to research integrity. Therefore, the academic community must take proactive measures to ensure the responsible and ethical use of AI in research. This includes strengthening ethical norms, enhancing researcher qualifications, and establishing rigorous review mechanisms. International cooperation is essential for developing unified ethical standards and governance frameworks for AI in research. The paper underscores the importance of maintaining research integrity in the AI era to ensure the authenticity, reliability, and transparency of scientific work.The integration of artificial intelligence (AI) into scientific research has significantly enhanced efficiency and accuracy but also introduced new forms of academic misconduct, such as data fabrication and text plagiarism. This study highlights the challenges posed by AI in maintaining research integrity and proposes solutions to address these issues. The paper emphasizes the need for the academic community to strengthen ethical norms, enhance researcher qualifications, and establish rigorous review mechanisms. Key recommendations include developing comprehensive AI research integrity guidelines, implementing mandatory AI ethics and integrity training for researchers, and fostering international collaboration to develop unified ethical standards for AI in research. AI technologies, particularly in data analysis, literature generation, and experimental design, have transformed scientific research by improving efficiency and accuracy. However, the misuse of AI tools has led to serious ethical concerns, including data fabrication, text plagiarism, and lack of transparency. These issues are exacerbated by the sophistication of AI algorithms, which can generate convincing but false data and texts. Empirical case studies demonstrate the potential for AI to be misused in research, undermining the authenticity and reliability of scientific findings. To combat these challenges, the paper suggests the use of AI monitoring tools and techniques, such as data integrity checkers, plagiarism detection software, and transparency tools for AI algorithms. These tools help detect and prevent unethical practices in research. Additionally, education and training programs are crucial for enhancing researchers' awareness of ethical AI practices. These programs should cover AI ethics, data management, and the responsible use of AI technologies. The paper also emphasizes the importance of formulating and implementing policies and procedures related to research integrity. These policies should ensure the ethical use of AI in research, including the development of a code of conduct, establishment of review mechanisms, and the creation of a regulatory framework for research integrity. The study concludes that while AI offers significant opportunities for scientific advancement, it also presents new challenges to research integrity. Therefore, the academic community must take proactive measures to ensure the responsible and ethical use of AI in research. This includes strengthening ethical norms, enhancing researcher qualifications, and establishing rigorous review mechanisms. International cooperation is essential for developing unified ethical standards and governance frameworks for AI in research. The paper underscores the importance of maintaining research integrity in the AI era to ensure the authenticity, reliability, and transparency of scientific work.