Gen AI is reshaping data strategies, pushing leaders to enhance data quality, modernize platforms, and scale securely. Key actions include improving source data, using gen AI to build better data products, and enabling reuse through orchestration. Techniques like synthetic data generation, multimodal models, and automated pipelines accelerate development. Security and governance are vital, especially with unstructured data. Leaders should align coding standards, manage legacy systems, and select the right LLMs for migration. Success requires integrating gen AI into workflows to move from pilots to scalable, value-driven solutions​.

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