The Finance and Accounting (F&A) industry has reached an inflection point due to digital advancements and increasing hyper-competitiveness in the business landscape. Although the industry has been reliant on automation and traditional AI models for some time now, what has been lacking is true intelligence.
True intelligence, in this context, implies autonomous, goal-driven AI systems capable of independent decisions and acting across various F&A processes, such as forecasting, cash application, and compliance checks. So far, the lack of such AI systems has led to a gap between technology and humans. However, the paradigm is shifting, ushering in a completely new era of AI – Agentic AI systems.
What is Agentic AI?
Agentic AI systems are autonomous, intelligent AI models capable of learning from past data and actions and making decisions accordingly. Agentic AI systems go beyond binary, rule-based automation and perform tasks autonomously with minimal human intervention.
F&A Beyond Automation
Traditional RPA (Robotic Process Automation) and other AI tools help automate F&A tasks, such as expense approvals, invoice matching, and reconciliation. Conventional AI systems work in silos due to incompatible systems and fragmented data. Therefore, these systems allow actions to be performed based on instructions and pre-defined rules.
However, Agentic AI goes beyond automation and uses human-like intelligence to gain context of its environment and make decisions. It takes an outcome-driven approach, aligning actions with business goals, while continuously adapting and learning from market shifts, new and historical data, and regulatory updates. This kind of true autonomy is shifting the F&A industry from fragmented automation to an integrated intelligence-driven operating model.
Agentic AI Advantages
Agentic AI is known for its context awareness and cognitive intelligence, allowing AI agents to take parallel or sequential actions. And this can lead to tremendous advancements in the F&A space.
Interpretation Before Automation
Traditional AI agents relied on human inputs to perform tasks and transactions. But with increased cognitive independence programmed into Agentic AI systems, AI agents first understand intent and the desired outcome. They evaluate data from multiple sources before automating tasks and ensure that human inputs are taken only when necessary.
For example, Agentic AI simplifies the painful process of month-end data aggregation and reconciliation by learning to improve decision accuracy over time. AI agents orchestrate the closing process by automating journal entries with evidence, raising exceptions, and escalating issues intelligently. This not only uncomplicates the month-end tasks but also improves speed and accuracy dramatically.
Touchless Accounts Payable and Receivable
With the use of Agentic AI, payment applications, invoices, remittances, and exceptions can be handled intelligently by AI agents with zero to minimal human intervention. Agentic AI systems go beyond automation with their capability to reason and escalate exceptions intelligently. For example, an AI agent scans incoming invoices, extracts key information like purchase order references, amounts, due dates, tax codes, and invoice numbers, and then automates data validation against ERP records. AI agents understand organizations’ policies, assess risk, and escalate discrepancies, such as duplicate invoices, supplier health, liquidity risks, etc. Adaptive learning enables these agents to refine review and approval criteria, thereby automating workflows to a high degree. With Agentic AI, organizations can redefine their entire payment processing approach.
Enhanced Audit and Tax Compliance
With continuous learning and adaptation, Agentic AI monitors tax laws as they change. It proactively analyzes financial data and potential compliance risks, enabling agents to identify anomalies and predict probable disruptions. All transaction data is autonomously gathered before tax treatment is applied, with minimal human assistance and intervention. Moreover, for human-in-the-loop operations, AI agents assist users throughout the tax filing process.
The Added Benefit: New Standards of Accuracy and Efficiency
While traditional systems in the finance and accounting space were prone to inefficiencies and errors, Agentic AI has not only reduced the scope of mistakes but also enhanced overall efficiency. For example, AI agents automate complex tasks like reconciliation, analysis of variance, and reporting. They consolidate financial data from different sources in a matter of minutes and prepare audit-ready reports. These agents also identify discrepancies before they become errors that cannot be reversed. The idea is to utilize reasoning and decision-making in a manner that enables AI agents to complete tasks that typically take days in almost no time. This is possible because the Agentic AI systems are context-aware and continuously enhance the algorithm to not only speed up processes but also enhance the effectiveness of every outcome.
Conclusion
The finance and accounting industry is quickly adapting to the latest technological trends. But Agentic AI isn’t just another trend; it’s a gateway to transform whole organizations and become more agile and profitable strategically. Therefore, as leaders, it is our responsibility to guide this transition to be able to position ourselves for undeniable success in an increasingly complex financial landscape.
We must ensure that every team harnesses the full potential of Agentic AI while continuing to stay ethical. With transparency logs, clearly defined accountability structures, and human override rules, organizations can maintain trust and transparency. Very soon, Agentic AI will become integral in the F&A space, and those who jump on the bandwagon now will lead in the coming years.
