Julia Chirkova
Internal audit professionals are increasingly recognizing Artificial Intelligence’s (AI) potential to move beyond rudimentary tasks like content generation and summarization, extending its capabilities into the core functions of the audit lifecycle. However, despite this burgeoning awareness and anticipation, widespread and formalized adoption of AI within internal audit departments remains in its nascent stages. This sentiment was underscored by a recent survey conducted during a Wolters Kluwer TeamMate webinar, which garnered responses from over 2,000 internal audit professionals. The polling, a key component of the October 6th event titled "Beyond Chat Bots: The Evolution of AI in Internal Audit," aimed to gauge the current landscape of AI integration and the perceived future trajectory of its application.
The webinar, hosted by Wolters Kluwer TeamMate, a leading provider of audit management software, convened a significant segment of the internal audit community to discuss the transformative impact of AI. The event, held on October 6, 2026, delved into the practical applications and strategic considerations surrounding AI’s growing influence. Attendees were polled on various aspects of AI adoption, providing valuable, albeit specific to the participant group, insights into the profession’s sentiment and readiness. The polling questions focused on current AI usage, perceived value, and primary concerns regarding advanced AI applications.
Jim Pelletier, Lead Product Manager at Wolters Kluwer TeamMate, a prominent voice during the webinar, articulated a crucial distinction regarding AI’s role: "AI can be a contributor, but it can never inherit the auditor’s accountability," he stated. "The human has to be ultimately accountable and responsible for what ends up in your work papers or whatever you’re working on with AI." This statement encapsulates a fundamental tenet of professional auditing – that while AI can enhance efficiency and analytical capabilities, the ultimate responsibility for the integrity and accuracy of audit findings rests with the human auditor. This emphasizes the need for a robust framework of human oversight and professional skepticism, even as AI tools become more sophisticated.
Auditors Foresee AI Deepening Its Role Across the Audit Lifecycle
The polling results suggest a clear vision among internal audit professionals regarding AI’s most impactful applications. A significant majority of respondents indicated that they believe AI’s greatest potential lies in enhancing substantive audit work, the core of evidence gathering and analysis. When asked where AI could generate the most value for their respective teams, a notable 38.2% of participants pointed to the crucial initial stages of planning and risk assessment. This suggests a desire to leverage AI for more sophisticated and data-driven identification of audit areas requiring focused attention. Following closely, 31.2% of respondents identified evidence review and fieldwork as another key area where AI could deliver substantial benefits. This indicates a strong interest in using AI to streamline the laborious process of examining vast quantities of data and documentation, thereby freeing up auditors for more strategic and judgment-intensive tasks.
During the webinar, Pelletier elaborated on this observed evolution, describing a shift from AI’s initial utility in simply generating content to its more advanced roles in supporting critical decision-making processes, guiding audit workflows, executing specific, well-defined tasks, and ultimately, uncovering complex patterns and insights embedded within audit-related information. This progression signifies a move from AI as a passive assistant to AI as an active partner in the audit process, capable of performing tasks that were previously time-consuming and resource-intensive. The implication here is that AI could enable internal audit functions to cover more ground, identify more nuanced risks, and provide more comprehensive assurance.
"The more consequential the decision, the more important context, control, and review become," Pelletier emphasized. This statement highlights a key consideration for the integration of AI in high-stakes environments like internal audit. As AI systems become more autonomous and their outputs influence critical decisions, the need for transparency, explainability, and robust human oversight intensifies. This underscores the principle that AI should augment, not replace, human judgment, especially when the ramifications of an audit finding are significant.
Trust in Agentic AI Presents a Multifaceted Challenge
The survey also shed light on the primary concerns of internal audit professionals regarding the adoption of "agentic AI"—AI systems capable of acting autonomously to achieve objectives. Respondents were nearly evenly divided on their greatest apprehension, indicating a complex and nuanced view of these advanced technologies.
The polling revealed that 35.1% of respondents expressed concern about the potential for AI to perpetuate or introduce bias into audit processes. This is a critical issue, as biased data or algorithms can lead to skewed risk assessments, inaccurate findings, and ultimately, a loss of confidence in the audit function. The inherent nature of AI to learn from data means that if that data reflects existing societal or organizational biases, the AI will likely replicate and even amplify them.
Conversely, 32.8% of participants cited the risk of over-reliance on AI as their primary concern. This apprehension reflects a deep-seated understanding of the importance of human intuition, professional skepticism, and the ability to challenge assumptions – qualities that are central to the auditor’s role but not easily replicated by AI. The fear is that auditors might become overly dependent on AI-generated outputs, potentially overlooking critical nuances or failing to conduct independent verification, thus diminishing the overall quality and reliability of the audit.
Further highlighting the multifaceted nature of these concerns, 18.4% of respondents expressed worry about the potential for AI to make errors that could lead to incorrect audit conclusions. This concern is directly linked to the need for rigorous testing, validation, and ongoing monitoring of AI systems used in audit. The potential for even minor algorithmic errors to cascade into significant audit missteps is a tangible risk that audit functions must proactively address.
Pelletier reiterated the importance of maintaining auditor accountability, stating that responsibility and professional skepticism must remain with the auditor as AI takes on more work. He further stressed that for AI to be effectively utilized in assurance contexts, it must possess several key attributes: it needs to be explainable, allowing auditors to understand how it arrived at its conclusions; it must be traceable, providing an audit trail of its operations; it should be governed by clear policies and procedures; it must be grounded in trusted and verifiable information sources; and crucially, it needs to be human-directed, with auditors retaining control over its application and interpretation. This framework is essential for building trust and ensuring the ethical deployment of AI in the audit profession.
Governance and AI Literacy Emerge as Top Priorities
Reflecting the concerns voiced about AI’s potential pitfalls, the survey also identified the most critical next steps for internal audit functions looking to embrace AI. Establishing robust AI governance and developing clear acceptable-use guidance emerged as the top priority, with 35.1% of respondents highlighting its importance. This indicates a recognition that the successful and responsible integration of AI hinges on establishing a strong foundational framework that dictates how AI will be used, who is responsible, and what ethical boundaries must be maintained. Such governance is essential for mitigating risks related to bias, over-reliance, and errors.
Closely following, 28.9% of participants prioritized building AI literacy across their teams. This underscores the understanding that technological advancement requires a corresponding upskilling of the workforce. Auditors need to understand not only how to use AI tools but also their underlying principles, limitations, and potential implications. This proactive approach to education and training is vital for fostering confidence, enabling effective utilization, and ensuring that auditors can critically evaluate AI-generated insights.
The implications of these priorities are far-reaching. Without clear governance, the adoption of AI could be ad-hoc, leading to inconsistent practices and increased risk. Similarly, a lack of AI literacy could result in underutilization of AI’s capabilities or, conversely, the misapplication of tools due to a misunderstanding of their functions. Therefore, investing in both governance and education is paramount for internal audit departments to harness the benefits of AI effectively and responsibly.
For Pelletier, the long-term vision for AI in internal audit extends beyond mere efficiency gains. He posited that AI’s most profound impact could be in its ability to transform raw assurance information into actionable intelligence. This means moving beyond simply identifying issues to providing insights that enable proactive decision-making and strategic improvements within an organization. He reiterated the importance of keeping professional judgment at the center of this transformation, ensuring that AI serves as a powerful enabler of human expertise rather than a substitute for it. This vision suggests a future where internal audit functions are not just reactive in their assurance role but are also proactive strategic partners, leveraging data-driven insights to enhance organizational performance and resilience.
The polling, conducted among attendees of the Wolters Kluwer TeamMate webinar on October 6, 2026, involved between 2,078 and 2,327 respondents for each of the four polling questions. It is important to note that the results reflect the views of the webinar participants and should not be considered a representative survey of the broader internal audit profession. Nonetheless, the insights provided offer a valuable snapshot into the current thinking and future expectations of a significant segment of professionals actively engaged with the evolving landscape of AI in their field. The data points to a profession that is both optimistic about AI’s potential and keenly aware of the challenges and responsibilities that accompany its integration.
The path forward for internal audit departments involves a strategic and deliberate approach to AI adoption. This includes investing in the necessary technology, but more critically, investing in the people who will wield these tools. Building AI literacy, establishing clear ethical guidelines, and fostering a culture of continuous learning will be essential. As AI continues to evolve, so too will the role of the internal auditor, moving towards a more strategic, data-informed, and insight-driven assurance function, always with human accountability and professional judgment at its core. The journey from basic chatbots to sophisticated AI-driven analytics represents a significant paradigm shift, and internal audit is poised to be at the forefront of this transformation, provided it navigates the complexities with foresight and diligence.
