Introduction
Today’s accounting teams are shifting from manual processes to fully autonomous systems. This evolution is driven by agentic AI—multi-agent platforms that can act, learn, and adapt without constant human oversight.
What Is Agentic AI?
- A progression from RPA and generative AI, agentic AI is made of interconnected autonomous agents that monitor, analyze, and act across financial operations.
- Examples include software from Digits and Intuit QuickBooks which automate entire workflows, pausing for human review only when needed.
Core Benefits
- Reduced Close Cycles: End-to-end automation compresses month-end processes. EY’s agentic audit tools, for instance, allow sampling of 10,000 transactions versus 100, halving audit time.
- Higher Accuracy: Constant monitoring means fewer reconciliation errors—and richer internal controls.
- Scalability: As companies scale, autonomous systems handle growth without linear staffing increases .
Key Use Cases
- Autonomous General Ledger: Systems like Digits ingest data, aggregate transactions, reconcile, then ask for human validation, all automatically.
- Agent-Driven Audits: Big firms like EY are deploying agents to continuously analyze 100% of transactions, enabling anomaly detection in real time.
- AP/AR Automation: Tools from fileAI and Applied Epic use AI to match invoices with 99+% accuracy, cutting manual intervention.
Implementation Tips
- Start with workflows that are rule-based and repetitive.
- Build with modularity, integrating governance to address compliance concerns.
- Retain human-in-the-loop checks, crucial for maintaining trust and auditability.
Conclusion
Autonomous accounting is not the distant future—it’s here. Firms adopting agentic AI now are gaining speed, control, and strategic capacity, while those slow to act risk falling behind.