This study explores the transformative role of bibliometrics and artificial intelligence (AI) in advancing Islamic studies. It highlights how these tools enhance Islamic knowledge's preservation, analysis, and dissemination while fostering intellectual and economic growth aligned with Islamic principles. The paper also examines the synergy between bibliometrics and AI and their collective potential to revolutionize the study of Islamic texts and traditions. A qualitative approach was employed, synthesizing existing literature and case studies to analyze the applications of bibliometrics and AI in Islamic studies. Bibliometric analysis was used to trace research trends and identify gaps in Islamic scholarship. At the same time, the review of AI applications focused on tools such as natural language processing, semantic analysis, and digitization techniques. Challenges such as the lack of digitized Islamic texts, the underrepresentation of Muslim scholars, and ethical concerns in AI applications were critically assessed. The findings reveal that bibliometrics provides valuable insights into the intellectual landscape of Islamic studies, while AI enhances accessibility, efficiency, and precision in text analysis and heritage preservation. These technologies enable data-driven decision-making, interdisciplinary collaboration, and global dissemination of Islamic knowledge. The study identifies practical challenges and proposes solutions, such as targeted investments, training programs, and ethical frameworks, to maximize the potential of these tools. This study underscores the importance of integrating bibliometrics and AI into Islamic studies to preserve heritage, promote innovation, and address contemporary challenges. Proposing actionable recommendations offers a roadmap for scholars, industry leaders, and policymakers to responsibly embrace these technologies and ensure equitable access to their benefits. This work contributes to the growing discourse on technology's role in shaping the future of Islamic scholarship.