Data migrations, often fraught with challenges such as outdated data formats and unexpected demands, can be significantly streamlined through the use of AI-powered data migration frameworks. These frameworks offer a structured approach that incorporates automation, intelligence, and adaptability, simplifying the transition of data between systems and ensuring efficiency, reliability, and security. By leveraging modern tools and AI capabilities, such as Datafold's Data Migration Agent (DMA), organizations can automate repetitive tasks, enhance data accuracy, and handle complex discrepancies with precision, reducing the typical burdens of manual migration processes. AI also aids in pre-migration planning, data profiling, validation, and post-migration optimization, ultimately transforming the migration process into a faster, smarter, and less stressful experience. The implementation of AI in data engineering is likened to having an expert guide, allowing teams to focus on strategic goals while AI manages the technical intricacies, yielding significant time and cost savings, as demonstrated by DMA's success in reducing migration timelines for companies like SevDesk.