Artificial intelligence is becoming part of how businesses make decisions, communicate with customers and maintain their records. Those uses can affect legal obligations, contractual rights and the evidence available when a dispute develops.
MJB Law advises banks and businesses on regulatory, compliance and litigation issues arising from artificial intelligence. Matthew Bialick brings his banking and commercial litigation experience to the decisions surrounding AI use: what information can be shared, how an output should be verified, who remains responsible and what records should be preserved.
Legal advice grounded in how AI is actually used
The legal analysis begins with the task. A tool used to polish an internal memorandum presents different questions from a system used to evaluate credit, communicate a consequential decision or process confidential customer information.
We help clients examine the use, the information involved, the people relying on the output and the consequences if something goes wrong. The objective is a practical approach to approval, oversight and accountability that fits the business and the significance of the decision.
That work can include reviewing AI-use policies, advising on proposed applications, assessing vendor terms and identifying circumstances that require legal review before a person acts on an AI-generated recommendation.
AI regulatory compliance for banks and lenders
For financial institutions, AI use can intersect with fair lending, adverse-action notices, customer privacy, information security, record retention and third-party oversight. The applicable analysis depends on the institution, the product and the role the technology plays.
Matthew helps banks evaluate these issues in the context of their lending and business practices. An AI-assisted credit analysis, customer response or workout memorandum should be considered alongside the underlying documents, the bank's obligations and the record supporting its decision.
Our advice addresses the distinction between binding legal requirements, supervisory guidance and internal policy. We also help clients identify when a proposed use requires additional compliance or technical review.
- Legal review of AI-assisted lending and credit-management practices.
- Fair-lending and adverse-action considerations.
- Customer communications and the accuracy of AI-generated explanations.
- Confidential borrower information and uploaded loan documents.
- AI-use policies, approval responsibilities and escalation procedures.
- Third-party arrangements and allocation of legal responsibility.
Confidential information, vendor agreements & internal policies
An AI tool's usefulness does not answer what happens to the information entered into it. Vendor terms, account settings, retention practices and permitted uses of customer data can affect the legal analysis.
We review AI-related agreements and policies with attention to confidentiality, permitted data use, access to records, retention and deletion, notice of incidents, indemnification, limitations of liability and termination rights.
Internal policies should also address how employees use AI in their daily work. We help clients establish clear expectations about approved tools, sensitive information, verification of generated content and decisions that require human or legal review.
AI litigation, discovery & evidence
AI use can leave a record beyond the final document. Prompts, uploaded materials, generated drafts, conversation histories and communications incorporating AI output may help explain what a person knew, considered or represented.
Matthew addresses the role of those records in commercial disputes, lender-liability claims, fraud investigations and other litigation. The work includes identifying relevant sources, evaluating preservation obligations, pursuing appropriate discovery and examining how AI-generated material relates to the underlying evidence.
A generated summary may change the meaning of a conversation. A prompt may record a person's understanding of an event. An AI-assisted draft may contain a factual assertion that never appeared in the source materials. Those differences can matter when reconstructing what happened and testing a claim or defense.
Writing & speaking on AI legal risk
Matthew's article, Your loan officer's AI chat history is Exhibit A, examines how routine AI use in credit management can create litigation evidence and why legal review may be needed before a decision is made or a factual record is revised.
Matthew's Minnesota Bankers Association program, "When AI Becomes Exhibit A: Legal Risks for Minnesota Banks Associated with AI," addresses AI-related legal exposure through commercial and agricultural lending scenarios, including confidentiality, preservation, discovery and broader banking risks. Program date: January 28, 2027, 9:00–10:00 a.m. Central.