Worried about AI security risks in your legal practice? You should be—but that doesn’t mean you can’t use AI.
As legal professionals, you have ethical obligations to protect client confidentiality and maintain data security. Artificial intelligence tools offer powerful capabilities for research, document review, and analysis, but they come with unique considerations for law firms and legal departments. Let’s break down what you need to know about using AI without compromising your professional responsibilities or putting your practice at risk.
What are the main security risk areas?
When we talk about AI risks, we’re primarily concerned with two things:
- What the system produces (and why it produces it)
- Who can access the data flowing into and out of the AI model, including its training data
Privacy concerns
AI systems need lots of data to work well. This raises important questions:
- Will my clients’ sensitive information stay protected if I use AI to analyze it?
- Could my company’s intellectual property end up being used to help our competitors?
- How do we use AI while staying compliant with regulations like GDPR?
These questions often matter more than how well the AI performs.
Security vulnerabilities
AI systems can become targets for hackers and cybercriminals. Security breaches could lead to:
- Stolen data
- Compromised systems producing unreliable outputs
- Training data poisoning (where bad actors corrupt the learning process)
- Adversarial attacks that subtly manipulate inputs to change AI outputs without detection
Tip: Watch out for poor integration with your existing systems—this creates security holes and data inconsistencies.
Bias and fairness issues
AI can accidentally amplify biases found in training data, leading to unfair outcomes. This is especially concerning for legal decision-making, where questions of accountability and fairness are crucial.
Tip: Be critical of algorithm design. If certain factors get too much weight in decision-making, you’ll get skewed results.
The black box problem
Many AI systems, especially deep learning models, operate as “black boxes”—making it hard to understand how they reach conclusions. This lack of transparency is a major problem when you need explainable results.
Tip: Look for Model Cards that show their work. These provide details about how a model was built, including what data trained it. The best solutions clearly show how they reached specific conclusions.
Accuracy and reliability concerns
AI models only work as well as their training data. Poor quality or biased data leads to inaccurate results.
Tip: Beware of hallucinations—AI making things up has been a problem since day one. Always double-check AI outputs against trusted sources.
How to start mitigating AI-related risk
Working with AI securely requires a team approach. While legal teams might not handle the technical work, they should know how to partner with IT. Here’s what to consider and bring up when creating your plan:
Data governance
Put strong practices in place to ensure quality, security, and ethical use of data for training and operating AI.
Regulatory compliance
Stay current on relevant regulations and frameworks like ISO 42001 and NIST. Remember that rules differ across global jurisdictions.
Algorithmic auditing
Regularly check AI algorithms for bias and fairness, making adjustments to ensure equal outcomes.
Audit logs
Make sure you can access application logs within your network without third-party requests. This lets you monitor in real-time and spot problems before they escalate.
Explainable AI
Use AI models that explain their decisions when possible, or add systems that interpret complex models.
Human oversight
Have humans review everything your AI creates before using it or sending it to others. AI should enhance human decisions, not replace them.
Continuous monitoring
Ask IT to implement systems that constantly watch AI performance and outputs for unusual behavior.
Ethics guidelines
Create clear ethical guidelines for AI use. Start by understanding algorithmic bias in systems that influence decisions. Your guidelines should cover accuracy, privacy, and human oversight.
Training and education
Make sure everyone using AI understands its capabilities, limits, and risks. Develop workplace policies addressing data and system security.
Security measures
Put robust cybersecurity protections in place to guard AI systems and data. Encrypt everything and hold the keys yourself–called BYOK in IT-speak. This is essential for compliance with regulations like GDPR and HIPAA.
Diverse development teams
Promote diversity in AI development teams to help identify and address potential biases.
By following these guidelines, you can harness AI’s benefits while managing its risks in your legal practice.
The path forward: legal + IT partnership
The key to successful AI implementation lies in strong partnerships between legal and IT teams. Your legal expertise combined with IT’s technical knowledge creates the foundation for secure AI usage across your organization.
Don’t try to navigate these waters alone. Schedule regular cross-functional meetings to address emerging challenges and establish clear protocols for AI tool evaluation. IT can help implement the technical safeguards while legal ensures compliance with professional obligations and regulatory requirements.
Remember that security cannot be an afterthought. Build it into your AI implementation from the beginning, with IT leading technical security measures and legal providing governance oversight.
The goal isn’t avoiding AI—it’s using it thoughtfully and securely by leveraging the combined expertise of your organization. With proper collaboration, AI can enhance your legal practice while maintaining the human judgment that remains central to legal work.
For more on all things legal + AI, download our Legal AI Handbook.
Ironclad is not a law firm, and this post does not constitute or contain legal advice. To evaluate the accuracy, sufficiency, or reliability of the ideas and guidance reflected here, or the applicability of these materials to your business, you should consult with a licensed attorney. Use of and access to any of the resources contained within Ironclad’s site do not create an attorney-client relationship between the user and Ironclad.
