The Future of Auditing with Agentic AI

Agentic AI – A New Era of Artificial Intelligence

Artificial Intelligence (AI) has entered a new phase with the emergence of Agentic AI, a generation of systems designed not merely to respond to commands but to plan, reason and act independently, pursue objectives, and orchestrate tasks with minimal supervision. Unlike traditional tools that are reactive by nature, these systems integrate reasoning, memory, and planning, enabling them to function more like collaborators than assistants, using tools to execute complex, multistep workflows. The shift represents a profound transformation: instead of passively waiting for human input, agentic AI anticipates needs, adapts to circumstances, and executes strategies aligned with defined goals with minimal human intervention. Examples of these tools are AWE Agentic AI Services (Amazon); Google Cloud Conversational Agents Console; GitHub Copilot Coding Agents and for auditing we have MindBridge AI and AuditPal AI among other tools…

From Experiments to Real-World Adoption

This evolution is beginning to reshape the professional landscape, particularly in areas that rely on structured processes, large volumes of data, and rigorous oversight. Forecasts suggest that within few years, a meaningful share of enterprise decision-making will be informed or executed by such systems. Organizations are moving rapidly from experimentation to deployment, embedding agentic AI into workflows that span financial reporting, compliance monitoring, and risk management. The transition from manual and periodic oversight to proactive, continuous intelligence marks a turning point in how accountability and assurance are delivered.

As per Wolters Kluwer, a global provider of professional information software solutions and services, Agentic AI architecture is designed to outline four levels of agentic capabilities known as TACO framework[1].

• The Tasker: handling simple operations as data extractions;
• The Automator: managing end-to-end workflows;
• The Collaborator: working alongside auditors for advisory tasks and finally,
• The Orchestrator: coordinating multiple agents and systems for complex audit.

Transforming the Audit Function

For auditors, the benefits of this transformation are significant and offer transformative advantages for both external and internal audit functions. Agentic AI is capable of automating entire segments of the audit process, handling planning, testing, documentation, and reporting with unprecedented speed and consistency. Where audits were once constrained by time and resources, often limited to reviewing small samples of transactions, these systems can process vast datasets in real time, dramatically expanding coverage while reducing the likelihood of oversight or error and increasing consistency and accuracy. The ability to track and analyze every entry as it occurs creates the foundation for continuous auditing, shifting the role of the auditor from retrospective evaluation, reducing manual workload to real-time oversight and decision making, focusing on judgement-intensive tasks, risk assessment and internal control evaluation.

Strengthening Quality and Governance

Beyond efficiency, agentic AI also enhances the quality of assurance. By embedding decision logs and transparent audit trails into workflows, these systems provide a level of accountability that strengthens governance and regulatory compliance. At the same time, the automation of repetitive, labor-intensive tasks allows auditors to redirect their focus toward areas that require professional judgment, skepticism, and contextual insight. Instead of spending the majority of their time on data collection and verification, they can concentrate on interpreting results, assessing risks, and advising stakeholders on the broader implications for governance and strategy.

Human–AI Collaboration

Importantly, this technology is not a replacement for human auditors but a force that extends their capabilities. The judgment, ethical reasoning, and contextual understanding that auditors bring remain indispensable. Agentic AI acts as an amplifier, handling the heavy lifting of data processing and monitoring while leaving space for auditors to apply their expertise where it matters most. The collaboration between human oversight and machine intelligence creates an audit process that is faster, more accurate, and more relevant to the evolving needs of businesses and regulators.

Challenges and Responsibilities

Of course, the rise of agentic AI also introduces new responsibilities. Systems of this kind must be governed carefully, with transparency, fairness, and regulatory alignment at the forefront, ensuring that these agents reason effectively and provide useful feedback, requires extensive training on real-world data and clearly defined goals and objectives. Auditors will need assurance that the tools they rely on are themselves auditable, producing outputs that can be verified and trusted. Building confidence among professionals and stakeholders will depend on designing agentic AI architectures that prioritize accountability as much as efficiency. Audit teams must implement strong governance frameworks, set clear policies, develop new infrastructure and have the specialized AI talent, conduct vendor due diligence and ensure ethical AI usage.

The rise of agentic AI therefore signals both a challenge and an opportunity for the audit profession. By embracing this shift with thoughtful implementation and robust oversight, auditors can elevate their role, moving from compliance checkers to strategic advisors, from reactive monitors to proactive guardians of trust. When implemented responsibly, agentic AI promises to deliver not only faster and more accurate audits, but also a renewed sense of relevance and value in a world where oversight and assurance are more critical than ever.

[1] Beyond ChatGPT: How agentic AI is poised to revolutionize internal audit operations