The agentic future of audit: Governing AI across the audit workflow for assurance-grade outcomes

Audit and accounting firms face mounting complexity — expanding disclosure requirements, tighter margins and growing regulatory scrutiny — while operating with the same fixed capacity. AI has entered the conversation, but most tools remain disconnected from the core workflow, creating fragmentation and limited traceability between evidence and conclusions.

Agentic AI represents a meaningful shift. Unlike assistive or generative tools that address isolated tasks, agentic systems coordinate multi-step workflows within defined boundaries, carry context across stages and surface structured, evidence-linked outputs for professional review — all under continuous human oversight. This guide explains:

• How agentic AI differs from generative AI and traditional point-in-time automation
• Why governance, explainability and human control are foundational
• How agentic systems work in practice, with disclosure checklists as a concrete proof of concept
• Practical applications for audit and accounting firms at different stages of AI adoption
• How to build toward scalable, governed AI adoption without compromising professional accountability

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