Will AI Replace Insurance Agents? The Work Is Splitting
Will AI replace insurance agents? What current employment projections can show, which tasks are changing, and where agency AI use creates compliance exposure.
NAIC
The NAIC's AI workstream: the Model Bulletin, the evaluation tool, working-group meetings, and the state adoption map.
How AI Governance Works in Insurance →Guides & analysis
AI Governance Documents to Prepare for a Market Conduct Exam
The insurance AI exam documentation to have ready for a market conduct exam: an insurer-built readiness file of eight evidence categories, and how to record a gap.
AI Model Monitoring After the Model Goes Live
A playbook for insurers on AI model monitoring, validation, drift detection, and retesting records that satisfy NAIC Model Bulletin and Exhibit C expectations.
Generative AI in Insurance, Explained
What generative AI is, how it differs from the predictive models insurers already use, where it is being applied, and why regulators treat its risks differently.
Does AI Insurance Regulation Apply to You? A Plain-Language Self-Check
Five questions that flag when the AI regulations for insurance companies may reach your business, and what to review before treating the answer as settled.
The NAIC Insurance Data Security Model Law, Explained
NAIC Model Law 668 binds where a state enacts it: a written security program, third-party oversight, breach investigation, and notice to the insurance commissioner.
What the NAIC Is, and What It Cannot Do
The NAIC is the nonprofit standard-setting organization run by state insurance commissioners. States supply the regulatory power and decide whether its documents bind.
How U.S. Insurance Regulation Actually Works
U.S. insurance is regulated state by state, not federally. Why that is, what regulators control across the policy lifecycle, and how the pieces fit together.
Model Data Documentation for NAIC Exhibit D
A playbook for insurers preparing NAIC Exhibit D responses: document the 25 data elements, show internal and third-party sources, and close the data gap before the exam.
How Insurers Can Implement an AI Governance Framework for NAIC Exhibit B
A practical guide to implementing an AI governance framework for NAIC Exhibit B, from AIS programs to vendor oversight and consumer evidence.
AI in Insurance Fraud Detection and the Governance of Suspicion
How insurers use AI to detect fraud, how generative AI changes the fight, and what governance is needed to avoid false positives and bias.
Prior Authorization Is Where Health AI Gets Tested
How health insurers use AI in prior authorization, claims adjudication, and risk adjustment. What the NAIC, CMS, and recent litigation mean for governance.
AI in Homeowners Insurance Pricing and the State Rate Review
How homeowners insurers use AI, aerial imagery, and catastrophe models to price property risk, and what state regulators now require for transparency.
AI in Insurance Distribution and the Producer Services Layer
Producer services AI sits in NAIC Exhibit A. Learn how insurers use AI for lead scoring, producer onboarding, licensing, and product recommendations.
AI in Life Insurance Underwriting and the New Regulatory Test
How life insurers use AI in accelerated underwriting and what regulators now require for proxy testing, fairness, and documentation.
AI in Reinsurance Treaty Pricing and Catastrophe Modeling
How reinsurers use AI in treaty pricing, catastrophe modeling, and contract analysis. What model transparency and capital governance mean for risk carriers.
How to Build an AI Inventory by Line of Business for NAIC Exhibit A
Map your insurance AI systems by line of business for NAIC Exhibit A. Use this template to capture underwriting, pricing, claims, fraud, and customer service AI.
How Shadow AI Undermines NAIC Exhibit A
Shadow AI corrupts the counts reported in NAIC Exhibit A. What ungoverned AI use means for insurers, and a practical plan to close the gap.
What Trump's AI Executive Order (EO 14365) Means for State Insurance Regulation
Trump's AI executive order tells agencies to challenge state AI laws. Why McCarran-Ferguson still shields state insurance rules, and how far the federal push has got.
AI in Health Insurance and Who Governs It
A map of AI in health insurance: plan and jurisdiction differences, high-stakes workflows, and the right guide for prior authorization, claims, and risk adjustment.
How Insurers Assess AI Vendor Risk
A practical NAIC-aligned checklist for AI vendor risk assessment: due-diligence questions, contract clauses, and the ongoing monitoring that stays with the insurer.
AI Use Cases in Insurance by Business Line
A business-line map of insurance AI: the decision each system shapes, the risk that makes the line distinct, and the guide to read next.
How AI Governance Works in Insurance
A plain-language map of AI governance in insurance: the regulatory stack, the program it expects, and where to go for rules, implementation, and evidence.
UnitedHealth AI Governance and the nH Predict Case
A sourced UnitedHealth AI governance case study on the unresolved nH Predict dispute, prior authorization data, and the limits of the public record.
Agentic AI in Claims and the Human Review Test
How agentic AI in insurance changes claims decisions, where Exhibit C records the risk, and how carriers can test whether human review is meaningful.
The NAIC AI Systems Evaluation Tool, Exhibit by Exhibit
What the NAIC AI Systems Evaluation Tool is, what Exhibits A through D ask, how regulators select them, and where each evidence task belongs.
Inside the NAIC AI Model Bulletin
What the NAIC AI Model Bulletin is, how adoption works, what belongs in a written AIS Program, and which implementation guide to use next.