Proactive AI Compliance for Law Firm Managers

In late 2024, a routine court filing turned into a cautionary tale when Judge Michael Wilner discovered that nearly a third of the citations in a legal brief were completely fabricated. The document, prepared using generative AI tools (e.g., ChatGPT, Google Gemini, etc.), appeared polished and professional until the cases cited were revealed to be completely fabricated. "These authorities persuaded me," Judge Wilner later remarked, "only to find that they didn’t exist. That’s scary."

The resulting sanctions made headlines, but the real warning wasn’t just for attorneys. It was for everyone responsible for managing legal operations.

This brings into question how legal teams can or even should incorporate AI into their practice. Under ABA Model Rule 1.1, all legal professionals – not just attorneys – are required to understand the benefits and risks of emerging technologies like generative AI. This article is the legal professional’s introduction to AI and how to use it ethically and responsibly.

With Rapid Adoption Comes Serious Risks

Adoption of artificial intelligence in the legal industry is accelerating quickly. According to the 2025 Generative AI in Professional Services Report, usage by legal professionals nearly doubled in one year, jumping from 14% in 2024 to 26% by April 2025. Some surveys show even higher adoption rates in large firms, where AI is being explored for everything from timekeeping to trial preparation.

But with increased usage comes increased scrutiny.

Popular tools like ChatGPT, Gemini, and other general-purpose AI systems are not HIPAA compliant, lack SOC 2 certification, and retain user inputs indefinitely. These consumer-grade platforms can store sensitive inputs, log metadata, and generate outputs that sound credible but contain false or fabricated information.

From a legal management perspective, this introduces serious challenges:

• Confidentiality Risk
  
  • Sensitive client data may be stored and potentially exposed, especially if AI tools aren’t vetted for secure use.
• Discoverability
  
  •  AI-generated work product could become part of the litigation record if subpoenaed.
• Policy Gaps
  
  • Many firms lack clear guidelines on how or if staff should use generative AI tools in client-facing work.

Even well-intentioned use of consumer-grade AI tools can expose the firm to reputational harm, bar complaints, or data security incidents. For managers, staying ahead of these risks now means proactively reviewing internal protocols, auditing platform usage, and coordinating with IT and compliance teams.

But what exactly are these AI tools doing behind the scenes, and why do they pose compliance challenges?

What’s Really Happening Behind the Scenes of Generative AI?

To manage AI risk effectively, it helps to understand how large language models (LLMs) like ChatGPT or Google Gemini work.

When someone enters a prompt, the system breaks it into tokens, matches patterns from billions of prior examples (mostly internet text), and then calculates the most statistically likely next word. This means that responses are not inherently factual but rather probable. Errors in this way lead to “hallucinations” in which the AI cites facts that sound correct but may be completely fabricated.

This means:

• AI models don’t verify facts or know the law
  
  
• Training data is often outdated and non-legal
  
  
• Inputs may be stored and reused, depending on the platform
  
  
• Outputs may sound accurate, but aren’t always reliable

Legal-specific tools like ProPlaintiff.ai mitigate some of these risks by using curated legal datasets and offering features like citation verification, privacy controls, and data retention transparency.

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Ethical AI Use: A Shared Responsibility

While attorneys remain ultimately responsible for ethical compliance, law firm managers play a critical role in ensuring that AI use aligns with professional standards.

Three core areas demand attention:

1. Technology Competence
   Under ABA Model Rule 1.1, legal professionals must understand the tools they use, including the risks, limitations, and data practices of any AI platform. Managers can support this by implementing training, maintaining documentation on approved tools, and ensuring informed use across departments.
   
   
2. Client Confidentiality
   Generative AI platforms often store inputs and metadata. Even if a tool claims not to use data for training, its storage policies may still present confidentiality risks. Managers should help enforce protocols for de-identifying data, vetting platforms for compliance (e.g., HIPAA, SOC 2), and ensuring that staff avoid inputting sensitive client information into unapproved tools.
   
   
3. Supervision and Review
   AI output must be reviewed with the same level of scrutiny as work from a junior associate or contract professional. Managers can standardize review processes, document QA steps, and make clear that AI does not replace human judgment.
   
   

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