AI-Ready Data: Context-Aware Products

Juan Sequeda of data.world and Mohammed Aaser of Domo emphasized the limitations large language models (LLMs) face when working with structured data, underscoring the critical role of semantic layers and metadata in providing business context and improving accuracy—often tripling performance over raw data alone. They stressed that enterprises must embed semantics, governance, and metadata directly into data products to transition from flashy demos to scalable AI solutions. Introducing the ABCDE framework—accountability, boundaries, clarity, downstream awareness, and explicit semantics—they outlined how to design effective, trustworthy data products. To succeed, organizations should start small, iterate, focus on business value, and ensure data is accessible and well-defined to avoid wasted resources and ensure impactful AI adoption.