The Center for Data Innovation recently spoke with Samuel Gold, founder of Risklytics, a San Francisco-based company developing an AI-powered platform that analyzes commercial insurance policies and AI-related liability risks. Gold explained how the company’s platform identifies insurance coverage gaps created by emerging AI policy exclusions and helps businesses navigate the rapidly changing commercial insurance market.
David Kertai: What does Risklytics offer?
Samuel Gold: Commercial insurance is facing a new challenge as AI systems become embedded in more physical products and industrial operations, creating new types of liability that many existing insurance policies were not designed to address. Earlier this year, the Insurance Services Office, which develops standard policy language used by many insurers, introduced optional policy provisions that allow carriers to exclude liability arising from AI use. Some insurers have adopted these exclusions broadly, while others have applied them only to certain policies or not at all.
For companies developing robotics, industrial automation, autonomous systems, and other AI-enabled technologies, these changes can create unexpected coverage gaps. Risklytics addresses this challenge through an AI-powered platform that analyzes insurance policies, insurer filings, and AI-related liability risks to identify those gaps. The platform continuously tracks policy forms, endorsements, and regulatory filings so clients can identify carriers that either do not apply AI exclusions or are willing to provide affirmative AI coverage, meaning policies that explicitly cover AI-related liability rather than excluding it.
Kertai: What types of data does your platform analyze?
Gold: Our platform analyzes insurer policy forms, regulatory filings, policy endorsements, and our clients’ existing insurance coverage. We also review customer contracts, AI governance policies, and documentation describing how each company develops and deploys AI systems. This helps us identify where liability could arise and whether existing insurance policies adequately cover those risks.
As the insurance market evolves, our database continuously updates as carriers revise their policy forms and filings. This ensures every recommendation reflects current policy language rather than outdated assumptions.
Kertai: How do you determine whether a company has an AI insurance coverage gap?
Gold: We begin by understanding how a company uses AI and what types of losses it is most concerned about. From there, we identify which insurance policy should respond if something goes wrong and determine whether AI exclusions create coverage gaps.
For companies building physical AI systems, such as robotics manufacturers or industrial automation firms, those gaps often fall between general liability and professional liability insurance. General liability policies may now exclude AI-related claims, while professional liability policies often exclude bodily injury or property damage. Once we identify that gap, we work with insurers willing to remove the exclusion or provide explicit AI coverage.
Kertai: How does your approach improve on traditional insurance brokerage?
Gold: Traditional brokers often compare this year’s policy with last year’s to identify changes. That approach becomes much less effective when insurers rapidly rewrite policy language. Instead, we analyze the policy forms themselves, identify AI exclusions, and evaluate whether they align with how a client actually uses an AI tool.
We also help clients prepare the documentation underwriters increasingly request, including AI governance policies, human oversight procedures, safety controls, data provenance, and alignment with frameworks such as the National Institute of Standards and Technology’s AI Risk Management Framework. Strong documentation helps insurers understand and price risk more accurately, improving the likelihood of securing favorable coverage.
Kertai: What challenges have you faced building a company focused on AI-powered insurance?
Gold: The biggest challenge has been building credibility in a rapidly evolving market. Insurers typically want to see a track record of successful placements before working with a new brokerage, and establishing that reputation takes time.
We are addressing that challenge by partnering with wholesale brokers and managing general agents, specialized insurance firms that develop and manage insurance products on behalf of insurers, while expanding through startup ecosystems such as Y Combinator and Harvard. Our long-term goal is straightforward: as AI becomes part of more real-world products and operations, companies should be able to obtain insurance that reflects their actual risks rather than outdated assumptions.
