Accounting analytics—the use of data methods and technologies to improve accounting, auditing, taxation, and managerial decision-making—has shifted from a niche topic to a core professional capability. Global employers increasingly expect graduates to interpret transactional datasets, design analytic tests aligned with assertions, build dashboards, and apply professional judgment under ethical and governance constraints. However, accounting programs worldwide face implementation challenges, including curriculum crowding, uneven faculty readiness, tool fragmentation, limited access to authentic data, and misaligned assessment cultures. This paper synthesizes global challenges and opportunities in teaching accounting analytics and proposes an integrated instructional architecture that includes an Analytics Learning Progression Model (ALPM), authentic task design, scalable assessment strategies, faculty development pathways, and a quality assurance scorecard for assurance of learning. Using an integrative literature review approach, the study consolidates evidence from accounting education research, auditing analytics literature, professional competency frameworks, and accreditation guidance. The paper contributes a practical roadmap for both high-resource and resource-constrained institutions to embed analytics in accounting education while strengthening ethical reasoning, transparency, and employability outcomes