In March 2024, Wacks Law Group, a six-attorney estate planning firm in New Jersey, was hit by ransomware. The attack exposed Social Security numbers, driver's licenses, and confidential client documents. The Qilin ransomware group claimed responsibility, and the firm's five-month delay in notifying victims triggered a class-action lawsuit.
That same year, at least 21 law firms reported data breaches, making 2024 the biggest year in the history of law firm breach reports. According to IBM, professional services organizations including law firms now face an average breach cost of $5.08 million per incident.
Against this backdrop, attorneys across the country are using AI assistants like Google's Gemini to draft motions, summarize depositions, and research case law. The question they should be asking: does using Gemini with client data create the next breach headline or ethics violation?
The short version: If you need to redact sensitive documents before they reach AI systems, PaperVeil handles that layer. The rest of this article explains where it fits in the broader governance architecture.
What "Safe" Means for Legal Practice
When lawyers ask whether Gemini is "safe," they're asking multiple questions at once.
Privilege preservation: Will confidential client communications remain protected, or does sending them to Gemini constitute disclosure to a third party?
Ethics compliance: Does using Gemini satisfy the competence, confidentiality, and communication requirements under the Model Rules of Professional Conduct?
Malpractice exposure: Could AI usage create liability if something goes wrong?
Regulatory defensibility: If the state bar investigates, can I demonstrate reasonable safeguards?
The answer to each question depends on how you use Gemini and what data you expose to it.
Legal Data at Risk
Law firms handle some of the most sensitive information in any industry. A partial inventory of what flows through typical legal workflows includes:
Privileged communications: Attorney-client correspondence, legal strategy discussions, case assessments, and settlement negotiations.
Work product: Legal research, draft briefs, internal memoranda, and case theories developed in anticipation of litigation.
Client personal information: Social Security numbers, financial records, medical histories, immigration documents, and family information for estate planning.
Litigation materials: Deposition transcripts, witness statements, expert reports, and discovery documents.
Transaction documents: M&A materials, due diligence findings, contract drafts, and closing documents.
Criminal defense materials: Case files containing accusations, evidence, and defense strategies where disclosure could harm clients or obstruct justice.
Every category carries distinct obligations. Privileged communications require confidentiality to maintain their protected status. Work product requires protection from disclosure to adversaries. Client personal information must be safeguarded under state and federal data protection laws.
How Gemini Handles Data
Google offers Gemini through multiple tiers with substantially different data handling.
Free Gemini: Your prompts and responses can be reviewed by human reviewers and used to improve Google's products. Data may be retained for up to three years. Google's terms give them broad rights to use content you submit. This tier is categorically inappropriate for any client data.
Gemini for Google Workspace (Business/Enterprise): Your content is not used for model training outside your domain without permission. Google states that prompts and responses aren't reviewed by humans or used for training. Content stays within your organization.
Gemini for Google Cloud: Similar enterprise protections. Prompts and responses are stored for up to 30 days for debugging and abuse detection, then deleted. Google does not use this data for model training.
Google has achieved significant compliance certifications for enterprise Gemini: ISO 27001/27017/27018 for information security, ISO 27701 for privacy management, ISO 42001 for AI governance (achieved May 2025), FedRAMP High authorization, and HIPAA compliance capability.
Enterprise features include Data Loss Prevention (DLP) policies that can prevent Gemini from accessing sensitive files, client-side encryption (CSE) for maximum data protection, and comprehensive audit logging through Google Vault for eDiscovery purposes.
The Attorney-Client Privilege Problem
Even with enterprise-tier Gemini, fundamental questions remain about privilege.
The American Bar Association addressed this directly in Formal Opinion 512, issued in July 2024. The opinion confirms that Model Rules related to competency, confidentiality, and informed consent apply to generative AI use. Specifically:
Model Rule 1.6 (Confidentiality): Lawyers must keep confidential all information relating to client representation. Using AI with client information requires the lawyer to be cognizant of this duty and take appropriate precautions.
Model Rule 1.1 (Competence): Lawyers must maintain technological competence. This means understanding how AI tools work, what happens to data submitted to them, and what safeguards are available.
Model Rule 1.4 (Communication): Depending on circumstances, lawyers may need to inform clients about AI use in their matters, particularly when confidentiality concerns arise.
Several state bars have issued additional guidance. Florida's Advisory Opinion 24-1 recommends obtaining "affected client's informed consent prior to utilizing a third-party generative AI program if the utilization would involve the disclosure of any confidential information."
The privilege concern is specific: inputting confidential client information into AI platforms may constitute disclosure to a third party. If the AI provider's terms allow them to retain or use the data, privilege could be waived. Public AI systems that retain inputs as training data create particular risk, as privileged content could theoretically resurface in responses to other users.
Where Gemini Falls Short
Let's be specific about the gaps.
No attorney-client privilege certification: Google's enterprise certifications address security and privacy, but they don't specifically address the legal requirements for maintaining attorney-client privilege. That determination ultimately falls to courts.
The human review question: Even enterprise Gemini may involve some human review for safety and abuse detection. While Google states business data isn't used for training, any human review outside your firm creates potential privilege concerns.
Retention creates risk windows: Even with enterprise controls, prompts and responses are retained for debugging purposes. A 30-day retention window is better than indefinite retention, but it's still a period where confidential data exists outside your direct control.
Integration with firm systems: For Gemini interactions to be part of your matter files (as they arguably should be under some records retention policies), you need proper archival workflows. Google Vault helps with eDiscovery, but integration with legal practice management systems requires additional configuration.
The shadow AI problem: Up to 40% of law firms have experienced security breaches. Associates using personal Gemini accounts outside approved workflows create uncontrolled exposure that firm management may not detect.
Making Gemini Safe for Legal Practice
The solution follows the same pattern that works across regulated industries: remove confidential information before it reaches the AI.
Legal document with confidential information
↓
Automated redaction (client names, case details, privileged content)
↓
Redacted content sent to Gemini
↓
AI processes only sanitized data
↓
Confidential information never leaves firm control
With proper redaction:
- Privilege is preserved (no confidential information disclosed)
- Ethics obligations are easier to satisfy (the AI never receives protected data)
- Malpractice exposure is reduced (you can demonstrate reasonable safeguards)
- Regulatory defense is strengthened (clear documentation of data handling)
Practical Implementation for Law Firms
Step 1: Audit current AI usage
Before you can secure AI usage, you need to know where it's happening. Survey your attorneys and staff:
- Who is using Gemini or other AI assistants?
- What types of matters involve AI assistance?
- What data is being inputted?
- Are they using personal accounts or firm-approved tools?
Expect to find shadow AI usage. The goal is to understand and redirect to secure workflows.
Step 2: Classify by sensitivity
Highest risk (mandatory redaction or prohibition):
- Active litigation materials
- Attorney-client privileged communications
- Criminal defense case files
- Settlement negotiations
- Client Social Security numbers and financial data
High risk (strong redaction recommended):
- Draft briefs and motions containing case specifics
- Deposition transcripts
- Discovery documents
- M&A due diligence materials
Lower risk (enterprise controls may suffice):
- Legal research on general topics
- Form document templates without client specifics
- Firm administrative matters
Step 3: Deploy enterprise-grade access
Upgrade from consumer Gemini to Workspace or Cloud enterprise tiers. Configure:
- Single Sign-On with your firm's identity provider
- Data Loss Prevention policies to flag sensitive content
- Audit logging connected to your compliance systems
- Clear policies about what data requires redaction
Step 4: Implement automated redaction
Manual review doesn't scale and misses things. Deploy automated detection and removal of:
- Client and party names
- Case numbers and matter identifiers
- Dates and locations that could identify matters
- Financial figures and account numbers
- Any information that could identify specific clients or matters
Step 5: Establish firm-wide governance
Document and enforce:
- Which AI tools are approved for which tasks
- What data categories require redaction before AI processing
- Review and approval workflows for AI-assisted work product
- Incident response procedures if confidential data is accidentally shared
- Client disclosure practices regarding AI use
Step 6: Train your attorneys
Lawyers need to understand:
- ABA Formal Opinion 512 requirements
- Why AI creates privilege and ethics risks
- How to use approved redaction workflows
- When to escalate questions to the ethics partner
The Client-Side Encryption Option
For matters requiring maximum protection, Google Workspace offers client-side encryption (CSE). When enabled, data is encrypted with keys your firm controls. Google's AI assistants cannot access CSE-protected content.
This creates a hard barrier: documents protected by CSE are completely inaccessible to Gemini. For the most sensitive matters, this may be the appropriate approach, accepting that AI assistance won't be available for those specific files.
The Ethics Trajectory
The legal profession's approach to AI is evolving rapidly. In 2024, courts certified 40% of data breach class actions, up from 16% in 2023. Orrick, Herrington & Sutcliffe agreed to pay $8 million to settle class action claims from a 2023 breach. The litigation risk for firms that mishandle data has never been higher.
The ABA and state bars are actively developing AI guidance. Formal Opinion 512 was just the beginning. As AI capabilities expand and more attorneys adopt these tools, expect additional guidance addressing specific scenarios and more detailed requirements.
The firms that avoid ethics complaints and malpractice claims will be those that implemented controls before problems emerged. Waiting for a bar complaint to clarify your obligations is not a strategy.
Your Next Step
Gemini can enhance legal practice. The productivity gains from AI-assisted research, drafting, and analysis are real. But realizing those gains while maintaining your professional obligations requires intentional implementation.
If your firm is using AI with any documents that could contain confidential client information, automated redaction before processing is the safeguard that protects both your clients and your license.
PaperVeil lets you redact all your sensitive information from PDFs in a simple drag and drop flow. Detect and remove PII, match custom patterns, strip metadata, and generate audit trails. The redaction layer that makes AI document processing actually safe.