Securing insurance for an AI business can be complex, but understanding key processes — procurement, underwriting, and claims — can make all the difference. 

In this post, we’ll break down each step to help you find the right coverage and work with insurers who truly understand AI risks. With the right approach, you can protect your company from financial and operational uncertainties

The procurement process for AI insurance

Navigating the procurement process begins with understanding your company’s specific risks and selecting a broker and insurers who truly understand AI.

Step 1: Assess your company’s AI insurance needs

Start by evaluating where your AI product or use of AI could pose financial, operational, or reputational risks. For example, consider potential liabilities related to biased decision-making, regulatory compliance, or intellectual property disputes.

Then determine the appropriate coverage levels. Work with your broker to calculate the coverage limits that align with your risk exposure, factoring in company size, industry standards, and contractual obligations.

Step 2: Select the right insurance broker and carriers

You’ll want to carefully evaluate brokers and their expertise in AI risks. Have they worked with many AI-related businesses? How do they address specific risks like AI-driven errors, algorithmic failures, or regulatory non-compliance?

Be sure your broker clearly outlines terms and conditions in your quote proposal. Ensure that policy language includes affirmative coverage for AI risks. Premiums are important, but remember to factor in coverage quality and claims support.

Key questions to ask a broker:

• What industries and AI technologies do you have experience with?
• Do you have access to carriers that offer policies with affirmative coverage for emerging risks, such as AI-enabled fraud or compliance with new regulations?
• Are there bundled policies or cost-saving measures that fit my company’s stage and needs?

The underwriting process for AI insurance

To maintain a robust risk management strategy, you first need to understand how insurance claims and underwriting work.

Common pitfalls in the underwriting process – and how to avoid them

Navigating the underwriting process for AI insurance can be challenging, especially for companies unfamiliar with its complexities.

Below are a few common missteps that companies should proactively address to secure comprehensive coverage while avoiding costly surprises.

Inadequate or misaligned coverage

Startups often underestimate their exposure to AI-specific risks, opting for standard policy language that doesn’t fully address the unique liabilities that arise from AI.

How to avoid it 

Conduct a detailed risk assessment that considers algorithmic failures, intellectual property disputes, and regulatory requirements. Work with a broker experienced in AI-related risks to ensure your coverage matches your company’s specific needs.

Ambiguous or overly restrictive policy terms

Policies with unclear definitions or excessive exclusions can leave critical gaps in coverage, particularly around algorithmic errors or failures to meet evolving AI regulations.

How to avoid it 

Use a trusted broker and scrutinize policy language, particularly exclusions related to AI-specific risks like model errors, data misuse, or outdated software patches. Have your broker clarify terms and advocate for adjustments if necessary.

Failure to Communicate Risk Management Practices

Insurers use underwriting criteria to price risk, and insufficient documentation of risk management protocols can result in higher premiums or even coverage denials.

How to avoid it 

Provide detailed documentation of your company’s risk mitigation practices, such as regular audits of AI models, cybersecurity measures, and compliance with data protection laws. Demonstrating strong internal controls often leads to more favorable underwriting outcomes.

Strategies for mitigating risk in AI coverage

Companies leveraging AI must provide detailed insights into their risk management practices, including robust cybersecurity protocols, model validation processes, and compliance with data protection laws. Documentation demonstrating these safeguards often helps in securing more favorable terms.

Mitigating risks associated with AI technologies requires a proactive approach that combines technical safeguards, operational policies, and strategic planning. Here are five key strategies:

1. Conduct Regular Algorithm Audits

Periodically evaluate your AI models to identify biases, errors, and vulnerabilities. Use third-party audits for an impartial perspective and ensure model decisions are explainable.

Transparent algorithms reduce the likelihood of biased outcomes or unintentional errors, minimizing reputational and legal risks.

2. Implement Strong Data Governance Policies

Establish clear protocols for data collection, storage, and usage, ensuring datasets are representative and compliant with privacy laws. Monitor for data drift that can impact model performance.

Proper data governance prevents regulatory violations and improves the reliability of your AI systems, safeguarding against data misuse claims.

3. Invest in Robust Cybersecurity Measures

Deploy advanced security measures like multi-factor authentication, encryption, and continuous monitoring. Conduct regular penetration testing to identify vulnerabilities.

Protecting your systems from breaches reduces exposure to AI-enabled fraud, data theft, and costly downtime.

4. Establish a Claims Response Plan

Create an internal protocol for addressing incidents, including clear roles for notifying insurers, gathering evidence, and managing communication with affected stakeholders.

A well-defined response plan accelerates claims processing and minimizes the impact of incidents on your operations and reputation.

5. Stay Ahead of Regulatory Changes

Monitor updates to AI-specific regulations (e.g., EU AI Act, GDPR) and industry standards. Engage legal counsel or compliance experts to stay aligned with evolving requirements.

Proactive compliance reduces the risk of fines, investigations, and reputational harm, particularly as AI regulations continue to develop globally.

Start evaluating your AI insurance options

The process of procurement, claims, and underwriting may seem complex, but with the right approach and questions, it can be streamlined and effective. Navigating these processes requires thoughtful planning and the right partnerships. 

By proactively engaging with insurers and brokers experienced in your specific technology and business needs, companies can secure tailored coverage, streamline claims, and mitigate risks effectively.

The Vouch Approach to AI Insurance

Understanding insurance costs can be daunting but Vouch is ready to streamline the process for you. Vouch is the premier broker for high-growth companies, and we can help you identify your specific needs and guide you through the process quickly.

Discover the must-have coverages for your startup and find tailored solutions that fit your unique needs. And, with just a few clicks, get a coverage recommendation based on your business stage and industry vertical.