Succession planning has long been recognized as a cornerstone of effective human capital management, ensuring leadership continuity and organizational resilience. Traditionally, however, organizations have depended on manual assessments and reactive replacement strategies that were often undermined by bias, subjectivity, and limited foresight, leaving critical gaps in leadership pipelines. By mid-2023, the integration of artificial intelligence (AI) analytics within Oracle Talent Management Cloud has transformed this paradigm, enabling a shift from static, role-based replacement planning toward proactive, continuous, and data-driven workforce strategies. Predictive models and AI-enhanced dashboards now allow HR leaders to forecast attrition, evaluate readiness with greater precision, and identify high-potential successors earlier in the talent lifecycle. At the same time, workforce analytics and natural language processing enrich decision-making by incorporating both quantitative and qualitative insights into succession pathways. This paper draws upon Oracle’s product documentation, practitioner reports, and academic research to examine the frameworks, tools, and ethical considerations that underpin this transformation, arguing that AI-powered succession planning is not merely an incremental improvement but a strategic capability that redefines how organizations build and sustain leadership pipelines in the digital era.