The AI Company’s Risk & Insurance Guide
9 Risk Areas Every AI Startup Should Audit
Artificial intelligence is reshaping entire industries, but it’s also creating entirely new exposures. Whether you license your model to clients or deliver it through SaaS, the same traits that make AI valuable (autonomy, scale, unpredictability) also make it risky.
This guide outlines nine key risk areas AI companies should address, and which insurance coverages typically respond.
1. Professional Liability (Technology Errors & Omissions)
Exposure: Your software fails to perform as promised, producing bad outputs, downtime, or financial loss for clients.
Example: An AI model used for loan underwriting produces biased results, leading to a client lawsuit for economic harm.
Coverage: Tech E&O protects against claims of negligence, software bugs, or contract performance failures.
2. Data Privacy & Cyber Liability
Exposure: Your system collects or processes user data that’s breached, leaked, or misused.
Example: A training dataset containing personal information is exfiltrated or sold. Regulators and customers take action.
Coverage: Cyber Liability covers data breach response, legal defense, regulatory fines, ransomware, and business interruption.
3. Intellectual Property Infringement
Exposure: Your model uses copyrighted content, code, or voices/images without permission.
Example: A generative AI tool outputs content resembling a copyrighted image or a celebrity’s voice.
Coverage: Media Liability or IP Infringement insurance covers defense and settlements for copyright, trademark, and likeness claims.
4. Directors & Officers (D&O) Liability
Exposure: Investors, regulators, or employees allege mismanagement, misrepresentation, or breach of fiduciary duty.
Example: A shareholder claims the company overstated its AI capabilities during fundraising.
Coverage: D&O Insurance protects founders, board members, and executives from lawsuits tied to business decisions or governance issues.
5. Employment Practices Liability (EPLI)
Exposure: Rapid growth, remote hiring, and equity negotiations lead to HR-related claims.
Example: A former employee sues for discrimination or wrongful termination.
Coverage: EPLI covers defense costs and settlements from employment-related claims.
6. Product Liability (for Embedded AI)
Exposure: If AI is embedded in hardware or physical devices, it could cause bodily injury or property damage.
Example: A robotics product powered by AI malfunctions and injures someone.
Coverage: General Liability and Product Liability respond to injury or damage caused by your product.
7. Contractual & Vendor Liability
Exposure: You rely on third-party vendors (cloud, APIs, data providers) whose failures impact your clients.
Example: A cloud outage prevents your SaaS platform from delivering services, and clients sue for losses.
Coverage: Tech E&O typically responds to contractual negligence or failure-to-perform claims.
8. Regulatory & Compliance Risk
Exposure: AI regulations (California AI Bill, EU AI Act, FTC oversight) bring scrutiny to model transparency and bias.
Example: You face an investigation for non-compliance or deceptive marketing of your model’s capabilities.
Coverage: D&O covers regulatory defense of leadership; Cyber may respond to data-handling violations.
9. Reputational Harm & Crisis Management
Exposure: Public backlash, PR crises, or viral errors in your model damage your brand.
Example: A biased or offensive AI output goes viral and erodes customer trust.
Coverage: Media Liability or Cyber often includes PR and crisis-management coverage.
