Counterpart's latest endorsement lands at this pivotal moment.

Consequently, the Los Angeles insurtech has expanded coverage to include first- and third-party agentic AI harms.

The move positions the company as an early supplier of affirmative wording in a market leaning toward sweeping exclusions.

Importantly, the firm labels the approach Agentic Insurance for the AI era.

Moreover, brokers gain a Technology E&O insuring agreement embedded within Miscellaneous Professional Liability and Allied Health forms.

This article examines the product details, underwriting mechanics, and the broader implications for Insurance Liability.

AI Coverage Gap Widens

Historically, most professional and cyber policies stayed silent on artificial intelligence.

However, several major carriers recently inserted broad exclusions that remove cover for algorithmic decisions or deepfakes.

In contrast, independent counsel at BatesCarey notes that such exclusions can leave directors and officers personally exposed.

Swiss Re SONAR data similarly tracks rising losses from systemic model failures and sophisticated Misinformation campaigns.

Consequently, demand for clear Insurance Liability language has accelerated among small businesses.

These dynamics illustrate a widening protection gap.

Therefore, stakeholders are scrutinizing new endorsements like the insurtech's offering.

Counterpart's New Endorsements

Counterpart announced its Affirmative AI Coverage on 24 November 2025 through Business Wire and multiple trade outlets.

The expansion adds an explicit Tech E&O insuring agreement plus defined triggers for hallucinations, misclassification, and hiring bias.

Furthermore, coverage applies whether the insured builds or merely deploys third-party agentic models.

Affirmative wording is backed by Aspen, Markel, and Westfield Specialty, adding rated capacity to the proposition.

Meanwhile, the insurtech stresses that every policy includes its Agentic Insurance branding to signal a focus on autonomous systems.

Market watchers highlight that this clarity could narrow Insurance Liability disputes during future claims.

In sum, the endorsements translate emerging AI risks into familiar policy mechanics.

Nevertheless, successful underwriting hinges on robust risk scoring.

Data-Driven Underwriting Approach

Unlike many incumbents, the insurtech collects more than 2,000 data points when evaluating applicants.

Moreover, questions probe governance frameworks, bias testing, incident response, and vendor contracts.

Governance Scores Matter Most

Therefore, organizations with documented human-in-the-loop controls may secure reduced premiums.

In contrast, firms lacking model inventories often face higher retentions or sublimits.

Additionally, the MGA ties capacity to AI audit results, echoing Swiss Re recommendations on quantifying agentic exposures.

Consequently, underwriting discipline may improve industry understanding of Insurance Liability frequency and severity.

Data analytics thus inform selective appetite.

Subsequently, attention turns to policy wording comparisons.

Comparing Policy Language Details

Not all affirmative clauses are equal.

For example, some competitors limit cover to specific software releases or exclude Misinformation entirely.

However, Counterpart lists hallucinations, biased decisions, and data misclassification as named perils within its form.

The company also embeds a broad Tech E&O trigger, capturing failures in integrated vendor code.

Harvard Law Forum authors warn that courts will interrogate whether AI directly caused alleged harm.

Therefore, insureds should map workflows to definitions before relying on any Insurance Liability promise.

• Verify how "artificial intelligence" is defined.
• Check sublimits tied to agentic tasks.
• Review carve-outs for privacy or Misinformation claims.
• Confirm interplay with standalone Cyber or E&O programs.

These checks reduce unpleasant surprises during claims.

Clear language remains the ultimate risk hedge.

Consequently, market forecasts deserve attention.

Market Impact Forecast Trends

Technavio estimates the AI-in-insurance market will add roughly USD 30 billion between 2025 and 2029.

Mordor Intelligence projects an even larger USD 88 billion size by 2030 under a similar growth curve.

Meanwhile, the company reports 28,000 policies sold through 2,800 brokers, signaling momentum in the small-business channel.

Moreover, its survey claims 92% of small businesses already deploy some form of AI.

Insurers that ignore this adoption trend may sacrifice Insurance Liability leadership and premium relevance.

Therefore, affirmative Insurance Liability options could become a standard offering within three underwriting cycles.

Moreover, several broker networks are building dedicated Agentic Insurance practices to meet anticipated demand.

Forecasts reveal attractive, yet uncertain, revenue opportunities.

Nevertheless, proactive mitigation remains essential.

Practical Risk Mitigation Steps

Beyond buying cover, organizations should strengthen governance, testing, and documentation.

Additionally, maintaining a human reviewer for critical agentic outputs limits downstream damage.

Professionals can enhance their expertise with the AI Security Level 1 certification.

Such credentials align with underwriting questionnaires focused on secure development and monitoring.

Moreover, aligning vendor contracts to Insurance Liability definitions prevents coverage disputes.

In contrast, failing to review third-party indemnities can erode the value of E&O extensions.

Effective controls complement any policy purchase.

Subsequently, the discussion returns to overarching conclusions.

Insurance markets stand at a crossroads as agentic tools proliferate.

Counterpart has responded by embedding affirmative cover, rigorous data underwriting, and transparent language under its Agentic Insurance umbrella.

Consequently, small businesses gain a clearer path to managing Insurance Liability while innovation continues.

Nevertheless, buyers must still audit definitions, Misinformation exclusions, and E&O overlaps before signing.

Therefore, readers should consult brokers, review policies, and pursue certifications to future-proof their risk strategy.

Explore the linked credential and join the emerging community shaping safer AI adoption.