Leveraging Technology for Advanced Audits: Transforming Internal Audit Processes

The evolution of software, automation, and AI in audit improves efficiency and effectiveness, reshaping how auditors analyze information, document work, and execute audits. But, like so many groundbreaking advancements, adopting technology in auditing requires understanding the risks associated with technology usage and testing to evaluate whether it can produce complete, accurate, and high-quality results. 

Key Technologies Revolutionizing Audit Practices 

Data analysis and AI tools are among the most impactful technologies transforming internal audit practices. They enhance our ability to generate, collect, analyze, and review data, and layering these tools with other technologies and practices can amplify their impact. 

Artificial Intelligence in Audit 

AI integration into internal audit may include individual or layered activities, such as repetitive task automation, large and complex data and information sets analysis, and continuous monitoring of system entries and event information. While age-old, trusted audit technology providers have integrated AI functionality, the marketplace has welcomed a variety of new tools and providers specifically developed to enhance assurance and audit functions. Tool functionality can be expansive or narrow based on the type of AI model utilized, with generative (e.g., ChatGPT) and predictive (e.g., Google Cloud BigQuery) models being the most common for the audit industry. 

Adoption and responsible deployment of the rapidly evolving AI landscape offer promising advancement in auditing. However, it’s critical that we properly evaluate AI tools prior to implementation and use. 

Benefits of AI in Auditing 

• Speed and efficiency in routine tasks 
• More attention devoted to strategic tasks 
• Mitigation of human error or bias 
• Aggregation and analysis of large data sets and information sources 

Common Pitfalls of AI in Auditing 

• Lack of familiarity with tool limitations 
• Limited transparency and understanding of output
• Over-application where human oversight is still needed 
• Sacrificing quality for speed and perceived ROI 

 Data Analytics in Audit 

Data analytics are used throughout the audit life cycle to identify scope areas, risks, and develop context. This critical process analyzes large data sets quickly, providing valuable insights for risk-based audit plans. Countless auditors, accountants, and financial professionals utilize tools like Audit Command Language (ACL) and Interactive Data Extraction and Analysis (IDEA), using their enhanced capabilities to evaluate large data sets. 

Data analysis historically reviewed past activity; however, new tools offer real-time statistics. Strategically adopting advanced tools, like data-based analysis integration into workflows, offers automated analysis as activities occur. This real-time capability helps with:  

• Risk mitigation: Detecting anomalies to prevent errors, fraud, or inefficiencies. 
• Informed decision-making: Providing insights for strategic planning and resource allocation. 
• Compliance and security: Flagging unauthorized setups or policy violations to protect data and uphold policies. 

Data analytics insights enhance the effectiveness and efficiency of internal audits, ultimately contributing to your organization's success and continued evolution. 

Implementing AI-Driven Audit Strategies 

Internal audit relies on a systematic and disciplined approach, producing value through completeness, accuracy, and quality. While some speculate that technology could replace human auditors, AI can't fully replicate the nuanced judgment of skilled auditors. To facilitate a smooth technological transition for enhanced auditing, organizations should: 

• Understand AI benefits and limitations: Recognize your AI tools’ strengths and weaknesses to avoid over-reliance and misuse. 
• Enhance auditor contributions: Use AI to support, not replace, experienced auditors. 
• Plan for comprehensive costs: Consider all costs, including training, implementation, maintenance, and monitoring. 
• Configure AI systems properly: Tailor AI systems to meet specific audit needs.
• Train AI and human teams: Develop training plans for AI systems and human auditors. 

Overcoming Challenges in Audit Technology Adoption 

Even with careful planning, adopting new audit technologies comes with its own set of challenges. Organizations must balance potential value against risks and understand operational and compliance requirements to make informed decisions. 

Common Challenges in Adopting New Audit Technologies 

• Over-reliance on technology for ROI: Organizations may rush to adopt new tools, focusing too much on ROI and overlooking limitations. This leads to unrealistic expectations and irresponsible tool deployment. 
• Misunderstanding or lack of understanding: New technology can be unclear in its purpose and use, causing potential misapplication. 
• Inability to effectively use functionality: Even with an understanding of a tool's use, teams may struggle to leverage its functionality without proper training, guidance, and oversight.  

Mitigation Strategies 

To avoid common challenges and pitfalls, you’ll need to develop a measured and focused strategy for technology implementation and usage. Like any other process, your approach should include—and even begin with—a governance framework that considers technology requirements prior to implementation and throughout use. You can also consider leveraging specialists for training and application, as well as project management professionals, to assist in effective implementation.  

Investing in co-sourced professionals to support your organization can strategically increase your ROI, helping your organization transition smoothly and maximize the value of new audit technologies. 

Impact of AI and Automation on Data Privacy and Security 

Data privacy is one of the most common risks we address with our clients. Public AI tools pose risks, while private AI tools can restrict access and adoption of the latest functionalities. When considering how to address data privacy within your AI tools, remember three key best practices:  

• Maintain control over how, when, and where data is transferred, utilized, and stored. 
• Implement a structured and required process with parameters for common limitations, which may include the type of data processed through or stored within a tool as well as who is granted access and what type of access they are provisioned. 
• Focus automation on access and communication, notifying the right people promptly and limiting access to review results. 

The Future of Internal Audit: Emerging Technologies 

Emerging technologies, such as advancements in data availability, real-time monitoring, and automated audit tasks, are already shaping the future of internal auditing. The technology explosion enhances opportunities for first and second-line personnel, strengthening their monitoring efforts while helping third-line and independent auditors prioritize their impact.  

While some organizations embrace technology’s promise of process efficiency, many still experience lags due to outdated systems and tools. But, even if your organization is on the cutting edge now, AI capabilities will continue to expand. How can we keep up? 

Don’t panic! The "flying car effect" suggests that while we will continue to identify new areas for development and change, the biggest advancements won't be sweeping overnight transformation. We’re much more likely to see incremental shifts that align with our needs. The future lies in reducing repetitive and basic audit tasks, allowing auditors to focus on more strategic activities. 

The keys to preparing and leveraging these future advancements include two fundamental approaches: 

• Continuously identify areas where technology can reduce repetition and enhance assurance functions. 
• Train personnel and champion change and progress. 

The Intersection of AI and Internal Audit at EisnerAmper 

EisnerAmper leverages and continues to invest in technology solutions to enhance tried-and-true internal audit methods. A secure AI environment allows our teams to harness the power of machine assistance with data analysis, natural language processing, collaboration, and increased efficiency. Our professionals are our greatest resource, and the fusion of world-class talent with best-in-class technology enhances how we serve our clients.  

Whether providing a secure environment to share documentation or leveraging the latest technology to analyze records and data, we’re committed to identifying opportunities on the cutting edge of advanced audit. Our team guides clients through the complexities of modern audit processes and can help your organization stay ahead of the curve. Contact us below to discuss how we can help.