AI governance moves closer to the workflow: theCUBE Insights at Amplify
SiliconANGLE Chad Wilson ● Covered by 7 sources
AI governance is moving into real work, not just chat. In finance and compliance, “looks right” isn’t enough anymore.
Based on reporting by SiliconANGLE, Chad Wilson — read the original for the full story.
Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error
AI governance is no longer just about stopping bad answers. At Workiva’s Amplify event, Krista Case of theCUBE Research said the bigger problem is what happens when AI agents start doing the work, especially in reporting, audit and compliance tasks where mistakes carry real consequences.
That changes the bar. If an agent takes an action in finance or another regulated process, companies need to know where the information came from, who approved it, and how to trace the steps afterward. Case’s point was blunt: in those settings, a response that merely seems plausible does not cut it. It has to be substantiated.
The harder part is that AI is not creating all the mess it has to manage. Case said fragmented data stores, inconsistent definitions and unclear ownership were already there. AI just makes the weaknesses louder, because flawed data can now move faster and touch more workflows.
And then comes the awkward tradeoff. If every action has to be reviewed by a human, a lot of the speed that makes automation attractive disappears. So companies are having to draw boundaries: when AI assists, when it can act on its own, and when approval is required. Case said those lines are still being defined, and they will keep shifting as business use cases change.
My take — AI-written commentary, not fact-checked reporting
The industry keeps talking about agentic AI like it is a productivity miracle, then acts shocked when someone asks who signed off on the mess. In regulated work, governance is not paperwork; it is the product. And the more vendors promise autonomy, the more they should expect boring questions about data, approvals and traceability to do the real deciding.
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