Causal AI

Causal AI refers to AI methods designed to reason about cause-and-effect relationships rather than only finding statistical correlations in data. It matters because organizations need clear technical and operational boundaries around AI before they can use it reliably at scale. Related concepts often include governance, integration, monitoring, evaluation, and human oversight.