01 · Insurance workflows
Start with the task, not the model.
I study and prototype where AI can improve the way insurance organizations handle intake, research, servicing, renewal preparation, document analysis, and knowledge retrieval.
Stanford AI Graduate Certificate · In progress
Insurance operator building at the intersection of AI, risk, and workflow transformation.
I focus on practical AI adoption in insurance—especially where frontier models can improve workflow, knowledge access, decision support, and operating leverage inside regulated environments.
Why this work matters
Insurance does not need more vague AI commentary. It needs people who understand how real insurance work gets done and where model capability can create measurable value without creating avoidable governance risk.
My background is in insurance leadership, growth, and risk advisory. I am now building at the intersection of insurance expertise, workflow design, and applied AI, with a focus on brokerage operations, knowledge systems, submission intake, client service, and responsible adoption in regulated settings.
I am using this site as a public portfolio for that work: projects, case studies, frameworks, and writing that connect AI capability to real insurance workflows.
What I focus on
Three areas determine whether AI in insurance becomes commercially useful or remains presentation material.
02 · Enterprise adoption
Operating model matters more than hype.
I focus on the questions that determine whether AI works in practice: process design, human review, role clarity, escalation paths, ownership, and measurement.
03 · Governance and trust
Regulated deployment requires boundaries.
Serious AI use in insurance needs controls around review, auditability, privacy, model risk, and decision accountability. Without those, the use case breaks down.
Featured work
Initial flagship projects are designed to be concrete, explainable, and directly tied to insurance workflows.
Flagship concept
Document intelligence
Insurance Document Assistant
A prototype for reviewing insurance-related documents, retrieving key information, and supporting structured question answering with human oversight.
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Workflow prototype
Brokerage operations
Broker Workflow Copilot
A draft-generation workflow for account briefs, renewal preparation notes, and meeting prep materials built from mock client inputs.
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Governance framework
Responsible AI
Insurance AI Governance Framework
A practical framework for classifying insurance AI use cases by risk, defining review expectations, and designing controls for deployment.
View projectWriting and insights
I write about the practical adoption of AI in insurance, with an emphasis on real workflows rather than abstract hype.
What AI Actually Changes in Insurance Distribution
Near-term value comes from workflow compression, internal knowledge access, and producer leverage—not replacing judgment or relationships.
Read essayWhere LLMs Fit in Brokerage Operations—and Where They Do Not
The useful boundary is not whether the model is impressive. It is whether the workflow is appropriate for draft assistance and review.
Read essayCurrent build
I am building a portfolio of applied AI work focused on insurance workflows, document intelligence, governance design, and enterprise operating models. That work includes prototype repos on GitHub, short-form and long-form writing, operating-model frameworks, and selected case studies.