Internal audit is at a crossroads.
For decades, internal auditors have served as the steady hand of corporate assurance—evaluating internal controls, mitigating risk, and providing assurance to boards and executives. But the ground beneath them is shifting. The explosion of artificial intelligence (AI), machine learning (ML), and generative tools like ChatGPT are transforming not only how organizations operate but also how they are monitored and governed.
This new reality demands more than procedural rigor. It requires a workforce that is data-literate, AI-aware, and capable of speaking the language of digital transformation. For Chief Audit Executives (CAEs) and audit leaders, the challenge is clear: how do you ensure your team isn’t just keeping up—but leading?
The New Skillset for Internal Auditors
Modern internal auditors must embrace a broader, more technical skillset. In particular, three areas are emerging as non-negotiables:
- AI and Machine Learning Awareness
- Prompt Engineering and Generative AI Tools
- Data Literacy and Analytical Thinking
Let’s break each of these down—and offer practical advice for building them into your audit function.
1. AI and Machine Learning: From Black Box to Strategic Asset
AI is not just a back-office efficiency tool—it’s increasingly central to business strategy. From fraud detection to predictive analytics, organizations are embedding AI into operations. Internal auditors must develop a working knowledge of these systems—not to code them, but to audit and challenge them effectively.
Key Competency: Auditors should understand AI/ML lifecycle stages, data sourcing practices, model risk management principles, and ethical considerations such as bias and fairness.
Real-World Example: At a leading European bank, the internal audit team partnered with the data science department to review how credit risk models were deployed using machine learning. This required auditors to understand supervised learning, overfitting, and data drift—not at a PhD level, but enough to ask tough questions and assess controls.
Action Step for CAEs: Host regular “AI 101” sessions and invite internal data scientists to conduct brown-bag lunches with the audit team. This builds cross-functional understanding and encourages collaboration between auditors and data owners.
2. Prompt Engineering: Making Generative AI Work for Audit
Generative AI tools like ChatGPT, Claude, and Gemini are already reshaping knowledge work—and internal audit is no exception. But to unlock value, auditors must learn how to use these tools skillfully. That means mastering prompt engineering: the art and science of crafting inputs that yield accurate, actionable outputs.
Key Competency: Prompt engineering helps auditors use AI tools for tasks like summarizing policies, generating audit scripts, and analyzing large text datasets (e.g., contracts or emails). It’s a productivity multiplier—if used responsibly.
Real-World Example: A Fortune 500 technology company created a “Prompt Playbook for Auditors” that included templates for drafting audit reports, identifying anomalies in open-ended survey responses, and summarizing regulatory changes. The result? A 40% time savings in certain reporting activities.
Action Step for CAEs: Integrate prompt literacy into internal training programs. Encourage auditors to experiment with tools in sandbox environments and develop ethical guidelines for AI usage, including proper validation and human oversight.
3. Data Literacy: Turning Data into Insight
Data literacy is arguably the most foundational skill in the digital age. It’s not just about using Excel or Power BI—it’s about understanding what questions to ask, how to interrogate data sources, and how to interpret results.
Key Competency: Auditors must be comfortable with basic data querying (e.g., SQL), data visualization, and storytelling with data. Just as financial literacy was once a prerequisite for auditors, data literacy is now indispensable.
Real-World Example: At a U.S.-based healthcare provider, internal auditors used data visualization tools to map trends in patient billing anomalies. By integrating simple dashboards into their fieldwork, the team uncovered patterns that traditional sampling methods would have missed.
Action Step for CAEs: Build a tiered data literacy framework. Not every auditor needs to be a data scientist, but all should be able to consume and question data outputs. Consider certification programs like the Data Literacy Project or customized modules offered by professional associations.
Strategies for CAEs: Building a Culture of Continuous Learning
Upskilling isn’t a one-time initiative—it’s a shift in mindset. Here’s how audit leaders can embed this evolution into the DNA of the function:
- Create Learning Pathways: Develop personalized training roadmaps for each auditor based on current skills and future roles. Use a blend of internal workshops, external courses, and peer learning.
- Incentivize Innovation: Recognize auditors who experiment with new tools and techniques, and share their learnings across the team. Innovation awards or digital badges can build morale and motivation.
- Recruit for Curiosity: When hiring, prioritize candidates with digital curiosity and a willingness to learn over deep technical expertise. Today’s audit leaders need “learn-it-alls,” not “know-it-alls.”
- Align with Enterprise Digital Strategy: Work closely with IT, data governance, and innovation teams to ensure audit remains plugged into enterprise transformation efforts. This helps auditors understand the “why” behind tech changes—not just the “what.”
Conclusion: The Future Is Not Optional
As organizations embrace AI and data-driven decision-making, internal audit must evolve or risk irrelevance. But this isn’t a story of replacement—it’s a story of empowerment.
The auditors of the future won’t just check boxes—they’ll be data-savvy advisors, helping organizations navigate uncertainty with insight, integrity, and intelligence.
By investing in AI fluency, prompt engineering, and data literacy today, CAEs are future-proofing the profession—and elevating the strategic value of internal audit for years to come.
