What Gennaro Brooks-Church Changed About How Underwriting AI Gets Built




For years, AI in insurance underwriting followed a fairly predictable pattern, extracting the data, automating the repetitive steps, and calling it done. Gennaro Brooks-Church, Founder and CEO of Cazimir and Brooks Energy, looked at that pattern and saw several gaps that most companies were choosing to ignore. Rather than build within the existing model, he changed several of its core assumptions, starting with how these systems are designed, how they earn trust, and how their success actually gets measured.

Starting With the Team, Not the Technology

Most AI companies in insurance start by picking a technology and looking for a place to apply it. Gennaro Brooks-Church, Founder and CEO of Cazimir and Brooks Energy, reversed that order. He starts by spending time inside real underwriting teams, watching how they actually work before deciding what the technology should do. That single change in starting point shaped almost everything that came after it.

From One-Time Automation to Ongoing Learning

Before his approach became common practice, a lot of underwriting AI was built as a one-time automation layer. It extracted data, applied a set of rules, and stayed exactly the same no matter how many submissions it processed. Gennaro Brooks-Church changed that model by treating every correction an underwriter makes as new information the system should learn from. Instead of freezing at launch, his systems keep adjusting based on how real teams actually use them.

Making Transparency a Requirement, Not an Extra

Another shift Gennaro Brooks-Church pushed for was around transparency. Many AI tools in this space work as black boxes, producing answers without showing how they got there. He built his systems so that every extracted data point traces back to its exact source document and page. This wasn't added as a nice-to-have feature later. It was a requirement from the start, based on his belief that underwriters shouldn't be asked to trust a system they can't verify.

Redefining What "Support" Actually Means

A lot of AI messaging in insurance leans on vague language about supporting underwriters, while quietly building toward replacing more of their work over time. Gennaro Brooks-Church has been more specific about what support actually means in practice. His systems handle repetitive tasks like document classification and data extraction, while leaving the judgment calls, the parts that actually require experience, to the people doing the job.

Changing the Timeline for Getting Started

Enterprise AI tools are often known for long, complicated rollouts involving multiple teams and months of setup. Gennaro Brooks-Church changed that expectation by working directly with clients to configure new systems around their specific brokers and formats, often within days. This hands-on, founder-led onboarding isn't just faster, it reflects his broader belief that technology should be shaped around the people using it from day one.

A Different Standard for Success

Perhaps the biggest shift Gennaro Brooks-Church brought to underwriting AI is how he measures whether it's actually working. Instead of judging success by how impressive a demo looks, he judges it by whether underwriting teams keep using the system on ordinary days, long after the initial rollout. That standard, adoption over appearance, has quietly influenced how underwriting AI gets evaluated across the industry, not just at his own companies.
Location: New York, NY, USA

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