Business Law Guidance on AI Errors, False Reports, and Liability Risk for Companies

Artificial intelligence is now embedded in everyday business operations. Companies use it to screen applicants, analyze customer behavior, forecast revenue, flag compliance issues, summarize contracts, and generate internal reports.

For many organizations, AI has quietly become part of how decisions are made.

What is changing is not the speed of adoption. It is the legal response when those systems get it wrong.

Across multiple industries, businesses are now facing disputes, regulatory scrutiny, and insurance challenges tied to inaccurate or misleading AI output. In many cases, the underlying problem is not the technology itself. It is the assumption that automated results can be relied upon without meaningful oversight.

As a business attorney licensed in Pennsylvania and New York, Todd Nurick of Nurick Law Group works with companies navigating this shift. Providing practical business law guidance on AI errors has become a critical part of helping clients manage risk in a rapidly evolving environment.

Why Business Law Guidance on AI Errors Matters Now

Until recently, most companies viewed AI tools as productivity aids. If a system produced inaccurate results, it was treated as a technical issue.

That approach is no longer sufficient.

When businesses rely on automated output to make hiring decisions, financial projections, pricing determinations, compliance reports, or customer communications, the consequences of error are legal, not just operational.

Courts, regulators, insurers, and counterparties increasingly expect companies to verify and supervise automated processes.

How AI Errors Are Creating Legal Exposure

In practice, liability often arises in predictable ways.

One common scenario involves employment decisions. Automated screening or evaluation tools may generate inaccurate assessments that influence hiring, promotions, or terminations. When challenged, companies are expected to explain how those outcomes were reviewed.

Another involves financial reporting. Some businesses rely on automated forecasting or summarization tools when preparing internal projections or external disclosures. Errors in these systems can lead to misrepresentation claims or regulatory inquiries.

Customer facing communications present similar risks. AI generated content that inaccurately describes pricing, terms, or product features can trigger consumer protection disputes.

In each case, the core issue is reliance without verification.

Insurance Coverage Is Not Guaranteed

Many companies assume that cyber or professional liability insurance will automatically respond to claims involving AI systems. That assumption is often incorrect.

Policies may contain exclusions related to automated decision making, professional judgment, or data practices. Some require specific disclosures about technology usage. Others impose strict notice and cooperation obligations.

When claims arise, insurers frequently examine whether reasonable oversight existed before extending coverage.

Vendor Contracts Do Not Eliminate Responsibility

Businesses often rely on third party platforms to provide AI tools. While vendor agreements may include indemnification or limitation of liability provisions, those clauses rarely eliminate all exposure.

If internal controls were weak or warnings were ignored, companies may still face direct liability regardless of vendor involvement.

Contractual protections work best when paired with sound governance.

Governance and Documentation Are Becoming Central

Boards and senior executives are being asked increasingly detailed questions about AI governance.

• Who approved the system

• Who reviewed outputs

• How errors are handled

• When human judgment overrides automation

• How reliance is documented

• Organizations without clear answers face greater scrutiny in disputes and audits.

  
  

Practical Business Law Guidance on AI Errors

Businesses do not need to abandon AI tools. They need structure.

Effective risk management includes:

• Establishing approval processes for new systems

• Defining when human review is required

• Documenting reliance standards

• Reviewing vendor agreements regularly

• Coordinating legal, compliance, and IT oversight

• Training leadership on accountability

These steps demonstrate reasonable governance and reduce exposure.

The Role of Outside General Counsel

Many companies lack internal legal teams dedicated to technology risk. This is where outside general counsel plays an important role.

An experienced business attorney can help align AI usage with contracts, insurance coverage, regulatory expectations, and governance frameworks before problems arise.

This proactive approach is far more effective than reactive defense.

Final Thoughts

AI errors are no longer hypothetical. They are producing real legal disputes, insurance conflicts, and regulatory inquiries.

Companies that treat automated output as unquestionable are assuming unnecessary risk. Those that implement oversight and documentation are better positioned to defend their decisions.

Todd Nurick and Nurick Law Group provide business law guidance to companies in Pennsylvania, New York, and nationally on AI risk management, governance planning, and compliance strategy.

This article is for informational purposes only and is not legal advice. Reading it does not create an attorney–client relationship. Todd Nurick and Nurick Law Group are not your attorneys unless and until there is a fully executed written fee agreement with Todd Nurick or Nurick Law Group.

Sources

Federal Trade Commission guidance on automated decision making and consumer protection

U.S. Securities and Exchange Commission internal controls and disclosure guidance

Insurance industry publications on technology risk underwriting

National Association of Corporate Directors governance resources