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AI-Driven Asset Management is transforming investment operations by enabling real-time portfolio analytics, intelligent risk management, and cloud-native data processing. This study presents a Cloud-Native Asset Management framework that integrates SimCorp Dimension, Snowflake, Informatica ETL, machine learning, and real-time analytics to modernize enterprise portfolio management. The proposed architecture supports the management of 30,000 investment portfolios through scalable cloud infrastructure while replacing traditional batch processing with real-time AI-driven decision-making. The framework incorporates Snowflake Cortex Machine Learning and Fama–French risk models to improve portfolio optimization, risk-adjusted performance, and investment decision support. Performance evaluation demonstrates a 25% improvement in Sharpe ratio, a 20% increase in risk-adjusted returns, a 35% reduction in operational costs, 90% portfolio coverage, and 99.9% platform availability. The implementation achieved a 25× return on investment (ROI) and high user satisfaction while exceeding operational performance objectives. The proposed cloud-native architecture provides a scalable foundation for enterprise asset management and supports future expansion to more than 100,000 portfolios, enabling advanced AI capabilities, intelligent automation, and sustainable growth across modern investment management organizations.