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This article focuses on the governance challenges and control frameworks required for integrating AI into financial reporting workflows. It highlights a critical gap where executive willingness to trust AI-generated outputs currently exceeds operational readiness regarding data quality and auditability. The core discussion centers on maintaining existing financial controls to prevent isolated AI errors from becoming systemic failures in regulated environments.

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Better controls clear a path for AI in finance

SiliconANGLE16 septembrie 20264 min de cititArticolul și perspectiva sunt în engleză.

AI governance is becoming essential as automation moves into financial reporting. Executives face pressure to adopt AI faster, yet many organizations lack the data quality and controls needed to trust its output. Workiva Inc. is addressing that gap by applying established reporting safeguards to AI-assisted processes, but its research suggests corporate confidence has already moved […] The post Better controls clear a path for AI in finance appeared first on SiliconANGLE.

AI governance is becoming essential as automation moves into financial reporting. Executives face pressure to adopt AI faster, yet many organizations lack the data quality and controls needed to trust its output. Workiva Inc. is addressing that gap by applying established reporting safeguards to AI-assisted processes, but its research suggests corporate confidence has already moved ahead of operational readiness, according to Steve Soter (pictured), vice president and industry principal at Workiva. “The thing that stood out to…

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