Automation—ranging from robotic process automation (RPA) and workflow orchestration to machine-learning-enabled anomaly detection and generative AI—has reshaped how accounting work is executed, supervised, and assured. While many repetitive bookkeeping and compliance tasks are increasingly automated, the educational challenge is not simply “adding technology content.” Instead, accounting pedagogy must be re-architected to prepare graduates for an environment where value creation depends on (a) designing and governing automated processes, (b) interpreting outputs responsibly, (c) exercising professional judgment under uncertainty, and (d) communicating insights to stakeholders. This paper develops a pedagogy-forward framework that links automation capabilities to learning outcomes, course design, and assessment methods. Drawing on guidance from global professional bodies and emerging evidence from RPA integration case studies, the paper proposes (1) an “automation-to-competence” curriculum map, (2) scaffolded learning sequences for RPA/analytics/controls, and (3) assessment designs that evaluate higher-order judgment, auditability, ethics, and governance. The paper concludes with implications for faculty development, accreditation alignment, and future research, emphasizing that automation should be taught not as software training but as a new professional logic for accounting work..