UPDATE

Artificial intelligence is no longer an emerging technology. It has become part of routine business operations across nearly every industry.

Organizations are using AI to analyze data, draft contracts, screen job applicants, create marketing content, automate customer interactions, detect fraud, support underwriting decisions, process claims, and improve operational efficiency. In many cases, AI functionality is already embedded within software platforms that employees use every day.

While organizations have moved quickly to adopt AI, insurance policy language has not evolved at the same pace.

This disconnect is creating important questions for risk managers, legal departments, finance teams, and executive leadership. The central question is whether an organization’s insurance program accurately reflects how AI is being used today and how a claim involving AI would be handled tomorrow.

Why AI Is Becoming an Insurance Issue

Many organizations assume that if an AI-related event occurs, coverage will fall under their cyber insurance policy. In reality, AI-related claims can trigger multiple lines of coverage, depending on the circumstances.

Consider the following scenarios:

An employee receives an AI-generated voice call impersonating a senior executive and authorizes a fraudulent wire transfer.
A customer alleges that an AI-generated recommendation caused financial harm.
An AI-powered hiring tool is accused of producing discriminatory outcomes.
AI-generated marketing content results in allegations of copyright infringement.
Confidential information is entered into a third-party AI platform and later exposed.
Shareholders allege that management failed to properly oversee AI-related risks.

Each of these situations involves AI, but each could implicate a different insurance policy. Depending on the facts, coverage may be triggered under a commercial crime, cyber liability, professional liability, employment practices liability, directors’ and officers’ liability, or commercial general liability policy.

That complexity is one reason insurers are increasingly focusing on AI during underwriting and renewal discussions.

Policy Language Is Beginning to Change

For several years, insurers generally addressed AI-related exposures through existing policy language. This approach is beginning to evolve.

In January 2026, ISO introduced several optional endorsements addressing exposures related to generative AI under commercial general liability policies, including endorsements CG 40 47, CG 40 48, and CG 35 08 (ISO Commercial General Liability Multistate Revision Filing, Effective January 2026).

While individual carriers determine whether and how to adopt these endorsements, their introduction signals an important shift in the marketplace. Insurers are beginning to address AI exposures directly rather than relying solely on policy language developed before generative AI became common.

Organizations should expect policy language, underwriting requirements, and insurer scrutiny to continue evolving as AI-related claims emerge and coverage disputes begin to develop.

Where Coverage Questions Commonly Arise

Commercial Crime
Deepfake fraud has become one of the most visible AI-related exposures facing organizations. Advances in voice cloning, video manipulation, and AI-generated communications have made it increasingly difficult to distinguish legitimate instructions from fraudulent ones.

Coverage may depend on policy provisions addressing:

Computer fraud
Funds transfer fraud
Social engineering fraud
Fraudulent instruction coverage
Voluntary parting exclusions

The outcome of a claim may depend on how the policy defines a fraudulent act and whether the transfer was initiated voluntarily, even if it was based on deceptive information.

Cyber Liability

Cyber liability policies remain an important source of protection for privacy breaches, network security failures, ransomware events, regulatory investigations, and cyber extortion.

However, not every AI-related loss is necessarily a cyber loss. For example, a flawed recommendation generated by an AI tool, an inaccurate output relied upon by a customer, or a business decision based on erroneous AI-generated information may not fit neatly within traditional cyber coverage grants.

Organizations should understand whether their cyber program addresses only security-related events or also responds to broader AI-related exposures.

Professional Liability and Technology E&O

Organizations that develop, customize, license, implement, or rely heavily on AI systems should carefully review professional liability and technology errors and omissions coverage.

Important questions include:

Is AI-assisted advice considered a covered professional service?
How would the policy respond to inaccurate AI-generated outputs?
Are third-party AI platforms considered covered technology?
Does the policy contemplate claims arising from algorithmic recommendations or automated decision-making?

As AI becomes increasingly integrated into products and services, these questions become more significant.

Employment Practices Liability

AI is increasingly being used in recruiting, resume screening, workforce analytics, employee evaluations, and hiring decisions. At the same time, regulators continue to examine whether algorithmic tools may create discriminatory outcomes.

Organizations should review how AI is being used within human resources functions and evaluate whether employment practices liability coverage aligns with those exposures.

Directors and Officers Liability

Boards and executive leadership teams are facing growing expectations regarding AI oversight, governance, cybersecurity, data management, and regulatory compliance.

Future claims could involve allegations relating to:

Failure to oversee AI-related risks
Inadequate governance controls
Misrepresentations regarding AI capabilities
Failure to disclose material AI-related exposures

As AI becomes more deeply embedded within business strategy, organizations should consider whether governance frameworks have evolved accordingly.

Commercial General Liability

Although AI is often viewed through a cyber lens, certain claims may implicate commercial general liability coverage. This is particularly true where allegations involve personal and advertising injury, defamation, intellectual property disputes, or other third-party claims.

The introduction of ISO’s new generative AI endorsements demonstrates that insurers are actively evaluating where traditional general liability coverage intersects with emerging AI exposures (ISO Commercial General Liability Multistate Revision Filing, Effective January 2026).

A New Insurance Market Is Emerging

At the same time, insurers are introducing AI-related exclusions and underwriting requirements, and some carriers are developing products designed specifically for AI exposures.

Examples include Munich Re’s AISure platform and HSB’s AI Liability Insurance product, both of which are intended to address certain AI-related performance, reliability, and liability concerns that may not fit comfortably within traditional insurance products (Munich Re aiSure; HSB AI Liability Insurance Product Overview).

The emergence of these products reflects a broader market reality. Insurers increasingly recognize that some AI-related exposures may require dedicated underwriting, policy language, and risk assessment rather than relying exclusively on existing coverage forms.

While the market remains relatively new, it is likely to continue evolving as AI adoption accelerates and claims activity develops.

What Underwriters Are Asking

Organizations should expect more detailed questions regarding AI during the renewal process.

Common areas of focus include:

Where AI is being used throughout the organization
Whether employees are permitted to use public AI tools
What information may be entered into AI platforms
Whether AI-generated outputs are reviewed before implementation
Third-party AI vendor management practices
Governance and oversight structures
Data privacy and cybersecurity controls
Internal policies governing AI use

Underwriters increasingly want to understand whether an organization uses AI, and how it is governed, monitored, and controlled.

Questions Organizations Should Be Asking Before Renewal

Organizations should consider asking their broker, carrier, and internal stakeholders:

Have any AI-related exclusions, limitations, or endorsements been added to our policies?
How would our commercial crime policy respond to a deepfake fraud event?
How would our cyber policy respond if confidential information were disclosed through an AI platform?
Does our professional liability policy contemplate AI-assisted services or recommendations?
Are AI-generated intellectual property claims covered?
Have underwriters documented any assumptions regarding our use of AI?
Are there affirmative AI endorsements or standalone products available that may be appropriate for our operations?
Which policy would be expected to respond first to a significant AI-related claim?
Have our insurance carriers requested information regarding AI use that differs from prior renewals?

These conversations can help identify potential coverage gaps before a claim occurs.

The Bottom Line

Artificial intelligence is becoming a standard business tool. Insurance policies, underwriting practices, and policy language are still adapting to the risks that come with it.

Organizations do not need to eliminate exposure to AI. They do, however, need to understand where AI is being used, how it is governed, and how existing insurance policies would respond if something goes wrong.

Questions or Need Guidance?

For additional risk management guidance, contact us today.

DISCLAIMER: This article is provided by SterlingRisk Insurance for general informational purposes only and should not be construed as legal or insurance advice. Always review your individual policy terms and consult your broker or legal counsel regarding your specific situation.