Generative Artificial Intelligence (GenAI) is transforming the educational landscape, reshaping research methodologies, and redefining the competencies required for doctoral students. This scoping review aims to map essential competencies for the effective integration of GenAI in PhD training, addressing gaps in existing frameworks such as ResearchComp. Following the PRISMA-ScR guidelines and the Joanna Briggs Institute (JBI) framework, we systematically analyzed 37 studies retrieved from the Scopus database. Our findings categorize competencies into five domains: hard skills (AI literacy, prompt engineering, and pedagogical applications), soft skills (critical thinking, interdisciplinary collaboration, and adaptability), ethical competencies (data privacy, bias mitigation, and academic integrity), management and innovation competencies (leadership, content management, and social innovation), and methodological and communication competencies (data analysis and academic writing). The study reveals that existing research frameworks, such as ResearchComp, inadequately address the challenges posed by GenAI in doctoral education. While digital literacy is emphasized, critical evaluation of AI-generated content, ethical decision-making, and AI-assisted research methodologies remain underexplored. To bridge these gaps, we propose a competency framework tailored to GenAI integration in PhD training. We recommend embedding structured GenAI training modules in doctoral curricula to enhance researchers’ ability to navigate AI-driven academic environments. Future research should validate this framework across disciplines and establish institutional guidelines for responsible GenAI use. By fostering an innovative and ethical AI adoption, higher education institutions can equip doctoral students with the necessary competencies to lead research in the era of GenAI.