Blog - Tag: AI
Insurers Start Excluding AI Risk in Commercial General Liability Policies, More
Some insurers have begun introducing exclusions for artificial intelligence-related claims from standard business insurance policies, creating potential coverage gaps for businesses that rely on AI tools for marketing, customer service, product development or daily operations.
The changes come after the Insurance Services Office, the industry’s clearinghouse for policy language, introduced three new artificial intelligence exclusions for commercial general liability policies that insurers are beginning to add to coverage forms.
Roughly 86% of all U.S. property/casualty insurance policies contain some form of ISO language, meaning these exclusions could soon become widespread and leave coverage gaps for many employers when their CGL policies come up for renewal. Insurers are also starting to add similar language to other policies with a liability component.
New coverage gap
The three new ISO endorsements include:
- CG 40 47 — The broadest form, excluding coverage for bodily injury, property damage or personal/advertising injury arising out of generative AI.
- CG 40 48 — A narrower endorsement excluding only personal and advertising injury claims tied to AI.
- CG 35 08 — An exclusion applying to products and completed operations liability coverage.
These endorsements could affect how coverage applies to certain AI-related claims, depending on policy language and endorsements.
One of the largest concerns involves Coverage B of the CGL policy, which traditionally covers claims such as defamation, invasion of privacy, misappropriation of advertising ideas or certain intellectual property-adjacent disputes. Under the new exclusions, those claims may no longer be covered if they arise from AI-generated text, images, audio, video or code.
Even businesses using third-party AI tools, rather than developing their own systems, may still trigger the exclusions. In some cases, incidental use of AI may be enough.
The businesses likely to feel the greatest impact are those integrating generative AI deeply into operations, including:
- Marketing and advertising firms using AI-generated campaigns,
- Technology companies embedding AI into products or software,
- Manufacturers relying on AI-assisted product design,
- Professional service firms using AI to draft documents or communications,
- Retailers deploying AI chatbots or recommendation engines,
- Nonprofits using AI for outreach or donor engagement, and
- Employers using AI tools in hiring or HR decisions.
Insurers are not stopping with general liability coverage. AI exclusions are also beginning to appear in:
- Directors and officers liability,
- Employment practices liability,
- Fiduciary liability,
- Cyber, and
- Errors and omissions policies.
Some insurers have already received regulatory approval for AI exclusions in Florida, Connecticut and Maryland. Others, including W.R. Berkley, have adopted broader exclusions that eliminate coverage for claims arising out of the use, deployment or development of AI across multiple lines of coverage.
What you can do
Businesses should expect insurers to ask more detailed questions about AI usage during renewals and underwriting. Companies that fail to evaluate potential coverage gaps could find themselves uninsured for lawsuits, regulatory investigations or shareholder claims tied to AI-generated content or decision-making.
Organizations should consider taking the following steps:
- Identify where AI is being used throughout the organization.
- Strengthen internal AI governance and oversight procedures.
- Require human review of AI-generated content and decisions.
- Train employees on acceptable AI use.
- Evaluate contracts with AI vendors and third-party providers.
- Discuss AI exposures and coverage gaps with us before renewal.
- Explore specialized protection options.
Some organizations may ultimately need dedicated technology errors and omissions coverage, cyber liability insurance or emerging standalone AI insurance products designed to address AI-related risks. Call us with questions.
New AI-in-Hiring Rules Are in Effect: What You Need to Know
Starting Oct. 1, 2025, any California employer that uses artificial intelligence and other automated tools in recruiting, hiring, promotion and related human resources decisions will have to ensure that the tools don’t discriminate against protected classes.
The new regulations, promulgated by California’s Civil Rights Department, cover any “automated decision system” (ADS) which the rules broadly define to include any computer-based process that makes or influences employment decisions, such as:
- Artificial intelligence,
- Machine learning,
- Algorithms,
- Statistics, and
- Other data-processing techniques.
If your firm uses AI or another data-driven system in hiring, you’ll want to beef up record-keeping and set testing procedures to ensure that the tools you use comply with the new regulations.
What counts as an “automated-decision system”
Examples of systems that are covered by the new regulations include:
- Résumé screeners — These may favor applicants who use certain wording, which can disadvantage older workers or those from different cultural or educational backgrounds.
- Targeted job-ad delivery — Tools may push job ads to preferred genders, age groups, races and other protected classes.
- Puzzle or game-style assessments — These tools may screen out people with certain physical or neurological conditions.
- Voice and facial analysis tools — Tools that assess “enthusiasm” or “communication style” may produce biased results against applicants with disabilities, speech differences or accents.
Basics of the new rules
Discrimination risk — It is unlawful to use an ADS or other selection criteria that discriminate based on any protected characteristic such as race, gender and ethnicity. Crucially, an employer can be liable even without intent if the ADS causes an adverse disparate impact on a protected class.
Anti-bias testing — Employers are required to perform anti-bias testing of their automated systems. In any investigation or lawsuit, regulators and courts may look at six factors to determine whether an employer took reasonable steps to avoid discrimination:
- Quality of the testing
- Efficacy (how well it detects bias)
- Recency (how current it is)
- Scope (which systems or data were tested)
- Results of the testing or due diligence
- The employer’s response to those results (what was changed or fixed afterward)
Failing to conduct or document bias testing could weigh against an employer in a discrimination case.
Record-keeping — The rule requires employers to keep ADS-related records for four years.
What you can do
If you use an ADS system in your personnel decisions, focus on the following to comply with the new rules:
Tracking — Track your ADS system’s involvement in recruiting, hiring, promotion, training selection, performance screens or advertising. Include vendor tools and “off-the-shelf” filters.
Testing — Build a defensible bias-testing program and document the six factors that regulators will look at:
- Quality,
- Efficacy,
- Recency,
- Scope,
- Results, and
- Your response.
Planning — Establish a plan to regularly test your ADS systems for bias-tainted decisions. Most importantly, if you detect deficiencies, document the steps you took to address the problems.
The takeaway
One of the keys to a successful defense is showing you have taken steps to remedy issues with tools that you use in employment decisions. That means being able to show that you have ensured your data-driven personnel tools do not discriminate.
As a side note, employers should expect more AI-related legislation in the years to come as more companies use it in their day-to-day operations.