Artificial intelligence (AI) has quietly become part of everyday life, with many people already using it without even realizing. From tools like auto-complete and spellcheck to smart scheduling and data visualization, AI-powered technologies have been enhancing productivity and efficiency for years. However, the recent development of Generative AI (GenAI) has introduced new possibilities and challenges, pushing organizations into uncharted territory. As internal audit functions begin to assess and incorporate AI into their work, it’s essential to understand the risks and opportunities associated with this evolving technology.
AI Is Not as New as You Think
Before diving headfirst into the world of GenAI, it’s worth acknowledging that AI has already been integrated into many aspects of both personal and professional life. Common tools such as chatbots, sentiment analysis software, speech-to-text applications, and even object detection in cameras and robots are all powered by various forms of AI. Many organizations have already embraced machine learning techniques in their processes, and internal audit teams are no exception.
If your internal audit function hasn’t yet explored existing AI capabilities, there’s a good chance that you’re missing out on opportunities to increase efficiency, accuracy, and insight. Even before engaging with more advanced GenAI tools, your team can reap significant benefits by optimizing current AI-driven solutions already at your disposal.
The Rise of GenAI: New Opportunities and Risks
While traditional AI applications have been quietly transforming business processes, the emergence of GenAI tools has sparked a wave of excitement—and concern. GenAI’s ability to create text, images, and other media from simple prompts democratizes access to complex AI models, allowing more people to harness its power. The rapid development of these tools has opened up significant opportunities for innovation, but it has also introduced new areas of risk that many organizations are still struggling to comprehend.
Internal audit teams must be prepared to play a key role in providing assurance over AI use within their organizations, especially as these risks continue to evolve. Some of the key risks associated with GenAI include:
Key Risks Presented by GenAI
- Privacy Concerns: The use of GenAI tools that operate as third-party Software-as-a-Service (SaaS) platforms may expose organizations to privacy risks. Personal information shared with these services could violate privacy laws, potentially putting sensitive customer or employee data at risk. Ensuring that AI tools comply with privacy regulations is critical.
- Intellectual Property Issues: GenAI often gathers information from the web, which may contain protected intellectual property (IP). Prompts need to be crafted carefully to avoid leaking any proprietary or confidential information. Additionally, there are challenges with securing the intellectual property rights of content generated by AI, which can lead to legal and ownership disputes.
- Malicious Behavior: AI tools can be targeted by adversaries who may exploit vulnerabilities to access sensitive data or carry out malicious actions. Internal audit teams must ensure that adequate cybersecurity controls are in place to mitigate these risks and protect organizational assets.
- Ethical Use of AI: GenAI tools can be used in unintended ways that circumvent organizational policies or even laws. For example, AI-generated content could be inappropriately submitted in competitive settings or used to manipulate outcomes. Ensuring ethical use of AI is a growing concern that internal auditors must address.
- Hallucination and Misinformation: GenAI models sometimes generate outputs that are inaccurate or entirely false—a phenomenon known as hallucination. These errors can be problematic, especially when models don’t provide clear sources or citations for their information. Organizations must ensure that they’re validating the accuracy of AI-generated outputs.
- Bias in AI Outputs: AI models are only as good as the data they’re trained on. If training data contains biases (e.g., gender, racial, or socioeconomic biases), the AI’s outputs could reinforce these biases. This can result in unfair, discriminatory, or inaccurate conclusions, which could harm an organization’s decision-making process and reputation.
- Model Performance Limitations: AI models are not infallible, and their performance can be limited by the quality of the data they’re trained on. If the model’s limitations are not considered, organizations could face suboptimal outcomes—such as poor-quality reports, inaccurate forecasts, or ineffective decision-making. Internal audit must evaluate AI model performance to ensure it meets the organization’s standards.
Internal Audit’s Role in AI Assurance
As organizations increasingly adopt AI and GenAI tools, the role of internal audit is becoming more critical in ensuring that these technologies are used responsibly and effectively. Internal audit teams should focus on the following areas to provide assurance over AI use:
- Governance and Oversight: Ensure that AI applications are aligned with organizational policies and legal requirements. This includes managing risks related to privacy, security, and intellectual property.
- Ethical AI Practices: Develop frameworks that promote the ethical use of AI, ensuring that tools are used in compliance with laws and organizational values.
- Risk Management: Continuously assess and mitigate risks associated with AI, such as data privacy breaches, biases, and model inaccuracies.
- Performance Monitoring: Regularly evaluate the performance and outputs of AI models to ensure that they are delivering accurate, reliable, and useful results.
Partner with I.P. Pasricha & Co. for AI Risk Assurance
Navigating the complexities of AI adoption requires a well-thought-out approach and robust internal controls. At I.P. Pasricha & Co. (IPPC Group), we specialize in helping organizations manage the risks and opportunities of AI, ensuring compliance and operational excellence.
Contact us today to learn more about how we can assist your internal audit team in AI governance and risk management.
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