AI risk management is entering a new era – and traditional data lineage tools aren’t keeping up. In a powerful piece for Forbes, Relyance AI CEO Abhi Sharma lays out a clear and compelling case for why organizations need to rethink their approach.
Sharma argues that legacy data tracking methods – focused narrowly on tables and columns, lack the context and oversight today’s AI governance demands. Instead, companies must adopt “comprehensive data journeys” that map data across the entire AI lifecycle, from collection to consumption.
He outlines four key pillars for this next-gen approach: ecosystem context, business logic, consumption visibility, and embedded compliance. Together, these offer deeper transparency, stronger regulatory alignment, and ultimately, more trustworthy AI systems.
It’s an insightful read that reframes governance not as a roadblock – but as a strategic edge.