AI Governance Enters the Workflow Era

As AI agents take on consequential tasks in finance and compliance, governance must evolve beyond plausible outputs to full traceability. Companies need to track where information came from, who approved actions, and reconstruct what AI agents did on their behalf, according to theCUBE Research analyst Krista Case. Speaking at Workiva's Amplify event, Case highlighted that fragmented data and inconsistent definitions predate AI but become more dangerous as agents act at speed and scale. Businesses must define when AI can act autonomously versus when human approval is required, with those boundaries expected to shift as use cases mature.