In this episode of Deconstructing Data, hosts David Finkelstein and Jessie Lizak sit down with Fern Halper, Founder of AI Foundations Group and VP of Research at TDWI, to explore what it really takes to make AI work inside an organization. Drawing on decades of experience in data analytics and AI, Fern explains why successful AI initiatives depend on much more than the model itself. From building a strong data foundation to understanding the business meaning behind data, she shares why organizations need to think about data as a living, continuously changing asset that requires ongoing attention.
The conversation explores how companies can bring together structured and unstructured data to unlock more valuable AI use cases, while also validating the signals being extracted from documents, emails, call center notes, images, and other sources. Fern explains why semantics, data freshness, ownership, provenance, and lineage are becoming increasingly important as organizations adopt generative and agentic AI. She also breaks down the difference between data governance and AI governance, why governance should be treated as an enabler rather than a compliance exercise, and how organizations can build a culture of collaboration around their data. Fern also shares insights into her technology stack, including how she uses AI tools for application development and data analysis.
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