New Briefing Note: AI & Privilege: Part One, Internal Investigations – Key Considerations for Professional Services and Financial Services Firms

Why It Matters

As AI tools become ubiquitous, mishandling privileged information can expose firms to litigation and regulatory penalties, making guidance essential for risk‑averse advisors.

Key Takeaways

• Generative AI can unintentionally capture privileged communications in training data
• Firms must implement strict protocols for AI usage during internal investigations
• Improper AI prompts risk waiving attorney‑client privilege and evidentiary protection
• Upcoming guidance will cover FCA inquiry risks and actionable compliance steps

Pulse Analysis

The surge in generative AI tools—from large‑language models to image creators—has reshaped how advisory firms collect, analyze, and disseminate information. While these technologies promise efficiency, they also intersect with the delicate framework of legal privilege that shields client communications from disclosure. Attorney‑client privilege, work‑product doctrine, and related evidentiary rules were designed for human‑driven processes; introducing AI adds layers of complexity, especially when data is fed into cloud‑based platforms that may store or learn from privileged content. Understanding this intersection is now a prerequisite for any firm that relies on AI in client work.

Internal, firm‑led investigations are particularly vulnerable because they often involve the collection of emails, interview transcripts, and forensic data that fall under privilege protections. When investigators employ generative AI to summarize documents or generate interview questions, the AI may retain excerpts in its training set, creating a de‑facto waiver of privilege. To mitigate this risk, firms should adopt clear policies: restrict AI use to non‑privileged material, enforce sandboxed environments, log all prompts, and obtain explicit client consent where appropriate. Such safeguards preserve evidentiary integrity and reduce exposure to discovery challenges.

Regulators such as the UK Financial Conduct Authority are already probing how AI affects compliance and disclosure obligations. The forthcoming second briefing note promises practical recommendations for responding to FCA inquiries without compromising privilege, including document‑tagging strategies, AI‑audit trails, and cross‑functional governance frameworks. Early adopters who embed these controls can demonstrate proactive risk management, potentially influencing regulator expectations and avoiding costly sanctions. As AI integration deepens, firms that align technology use with privilege safeguards will gain a competitive edge, reinforcing client trust while navigating an increasingly complex legal landscape.