AI in investigations: mitigating risks related to accuracy, transparency and accountability

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Artificial intelligence (AI) has the power to transform the way we live and work. As forensic advisers who specialize in tailoring innovative technology solutions to complex cases, we know the many ways this emerging technology is promising to increase efficiency in legal proceedings, including white collar investigations. To ensure AI enhances rather than undermines investigative processes, legal professionals must be vigilant about understanding and managing the risks inherent in AI applications. Failure to adequately prepare for AI adoption could lead to flawed methodologies, inaccurate observations, and the loss of credibility in courts, in front of regulators, and with client and other stakeholders.

Key themes explored in this article include:

• How AI can support fraud detection and document review in complex investigations
• The principles of accuracy, transparency and accountability in AI models and the underlying risks investigations teams should consider
• Examples of KPIs and stakeholder responsibilities in ensuring responsible use of AI
• Challenges in assigning accountability for AI-driven outcomes
• Practical recommendations for deploying AI tools responsibly in investigations