AI Risks: 10 Critical Strategies Every Company Needs Now
Summary: As organizations deploy AI across products and operations, familiar liabilities resurface under new technical guises. This guide shows how legacy insurance and targeted governance combine to manage AI exposures effectively.
AI Risks: Why Legacy Insurance Still Matters for Companies
When the Raine v. OpenAI case surfaced, legal teams and insurers revisited long-standing coverage principles. Lawsuits such as Raine, et al. v. OpenAI and A.F. et al. v. Character Technologies demonstrate that the core allegations — bodily injury, failure to warn, misrepresentation — echo traditional claim types.
- Commercial General Liability (CGL) often covers physical harm and remains relevant for AI-related incidents.
- Directors & Officers (D&O) policies address alleged leadership failures tied to AI investments or disclosures.
- Cyber and professional liability can respond when AI models mishandle data or cause algorithmic harm.
Risk managers should map each AI incident to potential legacy coverage lines rather than assuming exclusions apply. For hands-on guidance on analyzing claim pathways, review our coverage primer at Insurance Coverage & Claims Guide.
Key insight: Even as AI technologies evolve, foundational insurance concepts remain the first line of defense.
Top 10 Crucial Strategies for Managing AI Risks
Below are ten practical, prioritized actions that risk leaders can implement now. Each item pairs a risk with a concrete insurance or governance response, illustrated by a short example from a fictional company, Aurelia Tech, which integrated AI into its customer platform.
- Review legacy coverage — Audit existing policies to uncover unexpected protections. Example: Aurelia found its CGL responded to a third‑party bodily injury claim triggered by an AI-driven device.
- Analyze all implicated policies — Treat AI incidents as multi-policy events (CGL, D&O, cyber, EPL). Aurelia coordinated claims counsel across three carriers.
- Leverage vendor insurance — Ensure vendors list you as an additional insured and validate their limits. Aurelia negotiated vendor coverage after a supplier’s model failure.
- Watch for AI-specific exclusions — Insurers increasingly add carve-outs; track policy language and renew proactively.
- Underwrite transparently — Disclose AI uses accurately to avoid rescission. Aurelia improved disclosure during renewal and retained coverage clarity.
- Explore AI-focused products — Where gaps exist, consider specialized policies for algorithmic errors and regulatory fines.
- Engage cross-functional stakeholders — Involve HR, IT, legal, compliance, and operations in risk assessments to capture enterprise exposure.
- Institute regular coverage reviews — Schedule assessments before launches and on renewal cycles; involve experienced coverage counsel.
- Appoint a Chief AI Officer — Centralize governance, ensure consistent vendor due diligence, and maintain insurer relationships.
- Invest in AI training — Train employees, managers, and boards to detect algorithmic risks early and to document controls.
For technical cyber defenses that complement insurance, consider pairing these strategies with dedicated cyber risk resources such as our guide at Essential Strategies for Safeguarding Against Cyber Risks.
Key insight: Combining thorough policy review with governance and vendor controls turns insurance from a last resort into a strategic tool.
Underwriting, Exclusions, and Practical Claims Mapping
Underwriters now ask targeted questions about model lifecycle, data sources, and human oversight. Transparency during binding protects coverage and prevents disputes later.
- Answer underwriting questions precisely — Misstatements can void coverage.
- Monitor for exclusion trends — Carriers like those backing major tech-sector programs may add AI carve-outs over time.
- Map claims to coverage triggers — Physical harm to CGL; governance failings to D&O; data misuse to cyber/P&PI.
For examples of claim scenarios and state-specific guidance, see our resources on claims in California and Florida at Navigate Insurance Claims California and Insurance Claim Denials Florida.
Key insight: Accurate underwriting and intentional claims mapping reduce the likelihood of coverage disputes and speed recovery.
Coordination with Technology Leaders and Consultants
External advisors—consulting firms and technology partners—play a critical role in quantifying risk and shaping mitigation.
- Work with firms like PwC, Accenture, or Deloitte for governance frameworks.
- Engage technology providers—Microsoft, Amazon Web Services, Google DeepMind, IBM—to document model controls.
- Use data analytics partners such as Palantir Technologies or strategic advisors like McKinsey & Company for scenario testing.
Aurelia Tech contracted an external audit from a major consultancy to validate controls, which proved persuasive to carriers during renewal. For sector-specific parallels, review our real estate cybersecurity checklist at Cybersecurity Real Estate.
Key insight: Documented third-party assurance strengthens both risk posture and insurer confidence.
Litigation Trends and the Role of Legacy Policies
Legal researchers have tracked hundreds of AI-related cases; the number continues to grow. Still, many claims invoke long-familiar legal theories of negligence, product liability, or breach of duty.
- Raine v. OpenAI and similar suits highlight bodily injury and content-related harms.
- Claims alleging misrepresentation or nondisclosure often implicate D&O policies.
- Mental health and safety allegations, like in A.F. et al. v. Character Technologies, map to product warnings and duty-to-warn doctrines.
To learn how AI risks may intersect with travel or operational exposures, see our practical tips at Travel Insurance Tips and claims resources such as Flood Insurance Claims Advice.
Key insight: Tracking litigation patterns helps insurers and risk teams anticipate coverage questions and shape preventative controls.
Do standard CGL policies cover AI-caused physical harm?
Often, yes. If the element of physical injury is present and the policy’s insuring clause is triggered, a Commercial General Liability policy can respond even when technology is the proximate cause. Always review the specific policy language for exclusions tied to emerging technologies.
Should a company buy an AI-specific insurance product?
Consider specialized AI policies if audits of legacy coverage reveal gaps—especially for algorithmic errors, regulatory fines, or novel data harms. Combine such products with strong governance and accurate underwriting disclosures.
How can vendors help expand protection?
Require vendors to carry adequate insurance limits and add your organization as an additional insured where appropriate. This extends recovery options and clarifies subrogation pathways in multi-party incidents.
What operational roles reduce insurer concerns about AI risk?
Designating a Chief AI Officer, maintaining documented model inventories, and running regular model audits demonstrate control maturity and can favorably influence underwriting.