Artificial Intelligence and Accounting: What Businesses Need to Know

Artificial Intelligence (AI) is rapidly transforming various industries, and organizations are increasingly looking to leverage AI to gain a competitive edge. Whether you’re a thriving, multi-generational business, or a small community not-for-profit, preparing for AI is a multifaceted process that involves assessing readiness, developing a strategic roadmap, ensuring data security, managing change, and continuously monitoring performance. Here are a few points for decision makers to consider when implementing AI systems:

Data Integrity and Quality

• Accuracy of Input Data. AI systems rely on large datasets, and inaccurate or incomplete data can lead to flawed outputs.
• Data Governance. Establishing policies for data management, including data ownership, classification, and data lifecycle management, is crucial for ensuring AI systems function properly.

Model Governance

• Model Validation. AI models should be rigorously tested and validated before deployment to ensure they function as intended. Organizations must ensure their management team has processes in place for ongoing monitoring of AI models and should consult with advisors regularly.
• Bias and Fairness. Organizations must be aware of the risks of biased decision-making in AI systems. Regular audits and checks should be in place to detect and mitigate bias.

Cybersecurity Risks

• Data Security. AI systems often process sensitive data, making them targets for cyberattacks. It’s vitally important for organizations to consult with IT professionals to implement robust cybersecurity measures to protect data.
• Access Controls. Ensuring that only authorized personnel have access to AI systems is crucial. Organizations must implement strong access control measures and monitor access logs.

Compliance and Regulatory Considerations

• Regulatory Compliance. The management team must ensure the organization’s use of AI complies with relevant laws and regulations, such as General Data Protection Regulations (GDPR) for data protection. They should consult with their CPA and other professional advisors to understand and adhere to these requirements.
• Ethical Use of AI. Organizations must ensure their management team has policies in place to ensure AI is used ethically, particularly in areas like hiring, lending, and other decision-making processes.

Operational Risks

• Over-Reliance on AI. Organizations should be cautious about relying too heavily on AI for critical decision-making. When establishing internal controls surrounding AI usage, human oversight and a clear understanding of AI’s limitations should be emphasized.
• Systemic Risks. AI can introduce new risks into day-to-day operations, such as model drift or unexpected interactions with other systems. Organizations should consult with their CPA and other professional advisors to help identify and mitigate these risks.

Audit and Documentation

• Transparency and Explainability. AI models, especially complex ones, can be challenging to interpret. Organizations should engage with their CPA to maintain clear documentation and to explain AI-driven decisions, particularly for audit purposes.
• Audit Trails. It’s important to maintain audit trails of AI system activities, including data inputs, processing steps, and outputs. Organizations should consult with their CPA to ensure there are systems in place to capture this information.

Change Management

• Adaptation of Internal Controls. As AI systems evolve, so too must internal controls. Organizations must utilize their CPAs to guide them regularly in updating the organization’s internal control frameworks to accommodate changes in AI technologies.
• Employee Training. Organizations should invest in training for employees to understand AI systems, their implications, and the importance of maintaining robust controls.

Third-Party Risks

• Vendor Management. If an organization is using third-party AI services, the management team must ensure that proper due diligence is conducted on vendors, including evaluating their internal controls, security measures, and compliance with regulations.
• Contractual Safeguards. Contracts with AI vendors should include clauses that address data protection, intellectual property rights, and service level agreements (SLAs) to mitigate potential risks.

These are just a few of the strategies organizations can explore to prepare their AI implementation. But every situation is unique. As trusted advisors, CPAs play a crucial role in guiding organizations through this journey. By understanding AI technologies and their applications, CPAs can improve efficiency, accuracy, and decision-making, providing better services to their clients. Embracing AI will not only keep organizations competitive in the evolving landscape, but it will also drive growth, efficiency, and innovation.

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