As artificial intelligence (AI) continues to reshape industries, internal audit will play a crucial role in ensuring that innovation is balanced with integrity, accountability and risk awareness. Internal auditors are uniquely positioned to evaluate how organizations govern and deploy AI, helping to safeguard against unintended consequences while enabling responsible innovation.
Understanding the AI Landscape: Traditional AI vs. Generative AI
Traditional AI encompasses rule-based systems and machine learning models designed for specific tasks such as fraud detection, predictive analytics and process automation. These systems rely on structured data and operate within clearly defined parameters.
Conversely, generative AI represents a paradigm shift. It can create new content — text, images, code and even music — based on vast datasets and sophisticated neural networks. Tools like ChatGPT, DALL-E and GitHub Copilot exemplify this capability. While generative AI offers immense potential for innovation and efficiency, it also introduces novel risks that internal auditors must be prepared to assess.
Benefits of Using AI in Internal Audit
Thanks to the significant incentive of driving efficiency, many internal audit teams are already leveraging AI to enhance their functions. Internal audit teams are using AI for:
- Fraud Detection: AI can analyze large volumes of transactional data to identify anomalies and patterns indicative of fraudulent activity, often in real time.
- Documentation Control: Automation tools streamline the documentation of internal controls, improving accuracy and reducing manual effort.
- Data Analysis: AI enables auditors to process and interpret complex datasets more efficiently, uncovering insights that might be missed through traditional methods.
- Risk Assessment: AI models can help auditors identify emerging risks by analyzing trends across industries, geographies and regulatory environments.
These capabilities not only improve audit quality but also allow teams to shift their focus from routine tasks to strategic advisory roles, adding greater value to the organization. However, the risks of AI adoption also need to be understood and addressed.
Navigating the Risks of AI in Internal Audit
Despite its benefits, generative AI adoption can come with significant risks. The key concerns that internal auditors must address are:
- Bias and Fairness: AI systems can perpetuate or amplify biases present in training data, leading to unfair or discriminatory outcomes.
- Hallucinations: Generative AI models may produce plausible sounding but factually incorrect information, posing risks in decision-making, reporting and customer interactions.
- Outdated or Incomplete Data: AI models trained on historical data may not reflect current realities, especially in fast-changing industries or regulatory environments.
- Ethical Implications: The use of AI raises questions about transparency, accountability and the ethical boundaries of automation. Internal audit must ensure that organizations uphold ethical standards in AI deployment.
- Overreliance on Generative AI Results: Excessive dependence on AI tools can lead to complacency, where critical thinking and human oversight are diminished.
These risks underscore the need for internal auditors to develop a nuanced understanding of AI technologies and their implications.
Building a Robust AI Governance Framework
From understanding the nuances of generative AI to implementing governance frameworks and conducting AI-specific audits, internal audit can provide a comprehensive roadmap for auditors navigating this complex terrain. To manage AI-related risks effectively, a strong internal audit program must advocate for a comprehensive AI governance framework. Key components include:
- Transparency: Organizations should clearly document how AI systems operate, including data sources, algorithms, decision-making processes and limitations.
- Accountability: Roles and responsibilities for AI oversight must be defined, ensuring that someone is always accountable for outcomes and potential failures.
- Responsible Use Policies: Guidelines should be established to govern the ethical and appropriate use of AI, including limitations on automation, human oversight requirements and acceptable use cases.
- Continuous Monitoring: AI systems should be regularly reviewed and updated to ensure they remain accurate, relevant, and aligned with organizational goals and values.
- Stakeholder Engagement: Governance frameworks should involve cross-functional collaboration, including IT, legal, compliance and business units, to ensure holistic oversight.
Such frameworks not only support regulatory compliance but also foster a culture of responsible innovation and risk-aware decision-making.
Defining the Scope of an AI Internal Audit
Internal audit teams can provide meaningful assurance and insights into AI governance and risk management. As organizations increasingly adopt AI technologies, internal auditors play a critical role in evaluating the integrity, transparency and accountability of these systems. There are several critical areas to include in the scope of an AI audit, including:
- Governance and Oversight: Legacy IT policies, procedures and controls simply don’t address the new risks introduced by generative AI. Rather than making tweaks and adjustments to existing IT governance and oversight, internal audit should ensure AI governance is purpose-built from the ground up and is based on recognized authoritative sources such as NIST and the EU AI Act.
- Training Data Evaluation: Auditors should assess the quality, diversity and relevance of the data used to train AI models. This includes checking for biases, outdated information and data integrity.
- Cybersecurity and Data Privacy: AI systems must be protected against threats such as data breaches, model manipulation and adversarial attacks. Auditors should evaluate encryption, access controls and incident response plans.
- Model Performance and Accuracy: Internal audit should review how AI models are tested, validated, and monitored for accuracy and reliability over time.
- User Behavior and Access Controls: Understanding how employees interact with AI tools can reveal potential misuse, gaps in training or unintended consequences. Role-based access and usage logs are key audit points.
- Third-party Risk Management: Many organizations rely on external vendors for AI solutions. Auditors must assess vendor risk, contractual obligations and compliance with data protection standards.
The Future of Internal Audit in an AI-driven World
The future of internal audit is not just about controls and compliance, but guiding organizations through technological transformation with confidence and clarity. AI is no longer confined to traditional compliance and control testing, and auditors are becoming strategic partners in technology oversight. This shift requires new internal audit skills and mindsets, including:
- Data Literacy: Auditors must be comfortable working with data, understanding statistical models and interpreting AI outputs.
- Ethical Reasoning: As AI raises complex ethical questions, auditors must be equipped to evaluate decisions through a moral and societal lens.
- Technology Fluency: Familiarity with AI tools, platforms, and development processes is essential for effective auditing and advisory.
- Agility and Innovation: Internal audit must remain agile, continuously adapting to emerging technologies and evolving risk landscapes.
Internal audit has a unique opportunity to shape how organizations adopt and govern AI. By embracing this role proactively, auditors can help their organizations innovate safely, ethically and sustainably.
Your Guide Forward
Now is the time to elevate your internal audit function. By combining deep industry knowledge and technology experience, we can help you assess AI risks, implement governance frameworks and unlock the full potential of AI-driven audit capabilities.
Guided by our Risk Advisory professionals, Cherry Bekaert’s Internal Audit Services will help you navigate the evolving AI landscape with confidence and clarity.
Contact Cherry Bekaert to proactively manage AI risks, strengthen governance and transform your audit capabilities into a forward-looking, value-driving force. Start your journey toward smarter, more strategic assurance.
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