Data Privacy Risks in AI — and How to Manage Them

Artificial intelligence is transforming the way professionals work, particularly in the legal and investigative fields. But as AI adoption accelerates, so do concerns about data privacy. For law firms, investigators, and other organizations handling sensitive information, the risks are real — and they require more than just technical safeguards.

In this article, I’ll outline the key data privacy risks posed by AI and provide a framework for how to manage them responsibly.

1. The Nature of AI and Privacy Exposure

AI systems — particularly those based on large language models — process vast amounts of data to generate insights, summaries, or predictions. Unlike traditional software, AI is dynamic, probabilistic, and can be influenced by its training data and inputs. This creates unique privacy risks, including:

• Data Leakage: Sensitive client or case information could be unintentionally retained or exposed.

• Unclear Boundaries: Many AI providers do not disclose whether user data is used to further train models.

• Cross-Tenant Risks: In shared environments, there is the danger of one client’s data influencing another’s output.

• Jurisdictional Complexity: Data may be processed in locations subject to different (and sometimes conflicting) privacy laws.

2. Legal and Regulatory Risks

For law firms and regulated entities, these risks aren’t theoretical. They map directly onto obligations under:

• PHIPA (Canada) – regulating personal health information.

• GDPR (EU) – requiring explicit consent and strict data minimization.

• CCPA (California) – granting rights to deletion and transparency.

• Professional Duties – such as confidentiality, privilege, and client trust.

Failure to address AI-related privacy risks could expose firms to regulatory penalties, malpractice claims, or reputational harm.

3. Practical Strategies to Manage Data Privacy in AI

a. Data Governance First Adopt the principle that AI is just another software system subject to your firm’s governance. This means clear classification of what data can and cannot be used in AI systems, coupled with documented retention and disposal practices.

b. Vendor Due Diligence Not all AI providers are created equal. When assessing vendors, law firms should ask:

• Do you retain data? If so, for how long?

• Is data deleted automatically after processing?

• Is data encrypted in transit and at rest?

• Is user input used to further train the model?

• What controls prevent cross-tenant contamination?

For example, at Kolabrya | Legal AI , medical records are automatically deleted after use — ensuring that sensitive health information is never stored or reused. Firms should seek out similar guarantees from any AI vendor they engage with.

c. Human-in-the-Loop Controls AI outputs should never be blindly trusted. Establish review protocols so that human judgment validates what AI produces before it is shared externally.

d. Transparency and Disclosure Clients deserve to know if AI is being used in their matters. Simple disclosure policies build trust and protect against misunderstandings.

e. Access and Audit Trails Ensure administrative and user activity around AI systems is logged, monitored, and auditable. This provides accountability in the event of errors or breaches.

4. Turning Risk into Competitive Advantage

Handled poorly, AI introduces risk. Handled well, AI adoption becomes a competitive differentiator. Law firms and organizations that implement strong privacy controls can confidently assure clients:

• Their data remains secure and confidential.

• AI is used responsibly and in compliance with regulations.

• Innovation and efficiency do not come at the expense of privacy.

This combination — efficiency and privacy — is exactly what clients will demand going forward.

Closing Thought

AI is not inherently a privacy risk. The real risk lies in failing to manage it properly. With sound governance, robust policies, and a commitment to transparency, law firms and organizations can embrace AI’s benefits while protecting the trust at the heart of their client relationships.

Reach out if you need help with data privacy and assessment to info@kolabrya.com