Raising the quality of insights in agentic analytics
TL;DR
In just a few years, generative AI has changed the face of enterprise analytics, notably by making analytics accessible to users across the organization. Agentic AI promises to do even more, by automating entire workflows and taking actions based on agent insights. But there is a problem: The quality of insights that agents currently generate….
Nauti's Take
Before an agent runs analytics workflows or triggers actions, a small team should test the quality of its conclusions on real cases. Check source traceability, reproducibility, and explicit approval points for uncertain recommendations.
The available summary is brief, so the scale of the problem remains unverified.
Summary
In just a few years, generative AI has changed the face of enterprise analytics, notably by making analytics accessible to users across the organization. Agentic AI promises to do even more, by automating entire workflows and taking actions based on agent insights.
But there is a problem: The quality of insights that agents currently generate…
Sources
