A potentially transformative shift is underway in financial operations: the implications of leveraging Agentic AI for core finance functions, particularly with respect to the traditional cornerstone of internal controls – segregation of duties (SoD).
The traditional role of segregation of duties
For decades, finance teams have diligently implemented and monitored SoD to prevent fraud, errors, and conflicts of interest. This has involved carefully separating responsibilities across multiple individuals, ensuring no single person has control over an entire transaction lifecycle. It has been a necessary – albeit often complex and resource-intensive – endeavor.
What changes when AI replaces human actors?
A key question arises: what happens when the individuals performing these functions are no longer subject to human fallibility, bias, or the temptation of personal gain? What happens when the workforce is composed of intelligent, autonomous AI agents operating under strict algorithmic governance?
In a finance function predominantly powered by Agentic AI, the traditional imperative for strict, multi-person segregation of duties may diminish significantly, presenting a compelling array of benefits.
Let’s explore these implications in detail:
- Inherent impartiality and objectivity
Agentic AI operates based on pre-defined rules, algorithms, and data. It lacks personal motivations for fraud or error. Unlike human employees who may be susceptible to pressure, fatigue, or malicious intent, AI agents execute tasks with unwavering objectivity, consistently adhering to established protocols. This fundamentally reduces the risk of intentional wrongdoing – the very risk SoD is designed to mitigate.
- Unparalleled auditability and transparency
Every action taken by an Agentic AI is meticulously logged and time-stamped. This enables an unprecedented level of transparency in financial processes. Every transaction, decision, and interaction is recorded in a readily accessible and auditable format. This granularity facilitates the identification of anomalies, the tracing of errors, and thorough forensic analysis – potentially surpassing the effectiveness of traditional SoD practices.
- Elimination of collusion risk
A significant concern addressed by SoD is the potential for collusion between individuals to bypass controls. Agentic AI operates independently, strictly according to its programming. The notion of AI agents colluding for personal gain remains, at this stage, highly theoretical and extremely unlikely, given the current operational frameworks.
- Enhanced efficiency and speed
The implementation and monitoring of SoD across human teams often introduce process complexity and delays. In contrast, Agentic AI can execute tasks concurrently and at speeds well beyond human capability, eliminating the need for sequential handoffs and approvals. This enables a more efficient and responsive finance function.
- Strategic reallocation of human capital
By offloading routine and rule-based tasks – many of which are traditionally split to satisfy SoD – AI enables finance professionals to focus on higher-value activities. These may include strategic analysis, complex decision-making, stakeholder engagement, and oversight of AI systems. The result is a more effective use of human cognitive strengths.
- Long-term cost optimization
While initial investments in Agentic AI are considerable, the long-term reduction in personnel needed to maintain strict SoD across numerous processes can generate substantial cost savings. Organizational structures can be streamlined, and overhead reduced, without compromising control integrity.
Evolving the nature of internal controls
This evolution does not eliminate the need for controls; it redefines them. The focus shifts from multi-person oversight to system-level assurance, centered on:
- Robust AI governance frameworks: Ensuring AI operates ethically and in compliance with all relevant regulations.
- Rigorous testing and validation of AI algorithms: Identifying and correcting flaws or biases in algorithmic logic.
- Strong cybersecurity measures: Protecting AI systems from unauthorized access or manipulation.
- Continuous monitoring of AI performance: Using advanced tools to detect deviations from expected behavior.
- Clear accountability for AI-generated outcomes: Defining human responsibility for oversight and remediation.
Conclusion: A new era of financial control?
While internal control remains a foundational principle, the traditional reliance on multi-person segregation of duties may become less critical in finance functions powered by Agentic AI. This shift offers opportunities to enhance efficiency, improve accuracy, reduce risk, and optimize the value of human talent.
Embracing this technological advancement – anchored in careful planning and strong governance – can support a more agile, efficient, and secure financial future for organizations.
The broader debate centers on trust in autonomous systems and the pace of regulatory adaptation. The path forward requires caution and foresight to ensure the control environment evolves in step with these changes, preserving the integrity and reliability of financial information.
Profluo helps forward-thinking finance teams embrace the future with confidence. By automating document processing, enforcing rule-based workflows, and integrating seamlessly with your systems, Profluo lays the groundwork for governance in an Agentic AI-powered finance function.
Discover how Profluo can streamline your operations while maintaining control integrity!
