How to build a data foundation for generative AI

Generative AI has quickly demonstrated its value and potential to help businesses innovate faster by generating new media from prompts. According to Gartner, 55 percent of organizations have plans to use generative AI, with benefits outweighing the risks for 78 percent of executives. The technology is being used across various industries, including medicine, education, scientific research, law, and more. Generative AI can combine proprietary data with foundation models, making it a powerful productivity aid that may become the most knowledgeable entity within an organization. However, its success depends on data readiness, which requires mastery over proprietary data, automated data movement and integration, and responsible data governance. Data maturity is essential for efficient deployment of generative AI, requiring technological capabilities such as cloud-based data repositories and automation, as well as organizational practices like product thinking and data cataloging. Organizations can unlock the full potential of generative AI by prioritizing mastery over their proprietary data through advanced data operations technologies and responsible data use.

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