Susan Laine

Trust by design: the new standard for AI-ready data

Instead of merely accelerating flawed processes with AI, organizations must prioritize building a robust data foundation through unified governance, modeling, and quality control. …

The #1 question to reduce AI costs

High AI costs are often driven by fragmented data that forces models to expend excessive tokens trying to interpret missing business context. Implementing a semantic layer provides…

The trust paradox: Why better data programs are still rebuilding from scratch 

Recent research reveals that even organizations with mature data programs are rebuilding assets instead of reusing them due to a fundamental lack of trust in existing data quality …

How a data marketplace unlocks the value of trusted data products

This article argues that a successful AI strategy *requires* a robust data strategy, specifically one centered around a data marketplace. While building trusted data products is im…

Building trusted data products at speed & scale with AI in 2026

This article highlights a shift in data management towards “data products”: packaged, curated, and governed data sets designed for specific business outcomes and AI applications. T…