Life Insurance Consensus Index is an independent research publication studying how leading AI platforms recommend life insurance companies for specific consumer situations. We record their recommendations, measure agreement and disagreement, verify material insurance information, and add experienced editorial context.
Why we study AI recommendations
Consumers increasingly ask AI systems about term coverage, permanent policies, final expense insurance, and options for complicated health histories. Different platforms can give different answers to the same question. Our purpose is to turn those patterns into structured research that readers can examine.
Consensus describes the degree of agreement among the platforms included in a study. If six of seven recommend a carrier, that company appeared more consistently than one recommended by three. The result is useful evidence about AI recommendation behavior; it does not establish the best insurer for every applicant.
Research begins with a consumer situation
Age, health, medical history, medications, tobacco use, occupation, activities, driving history, coverage needs, and location can all affect carrier selection. We therefore begin with a defined applicant and insurance need, then ask each platform which carriers it would recommend and why.
A question about a 45-year-old nonsmoker with well-controlled Type 2 diabetes seeking $500,000 of 20-year term coverage gives the research more direction than a general request for the best insurance company. Comparing scenarios also helps us examine when recommendations change as term length, coverage amount, or underwriting circumstances change.
The areas we research
Our five primary categories cover term life insurance, whole life insurance, universal and indexed universal life, final expense and burial insurance, and health conditions and high-risk applicants. The research is designed to launch with more than 100 specific consumer scenarios across those categories.
Term studies examine temporary protection, coverage amounts, term lengths, and underwriting options. Permanent-policy studies explore whole life, traditional universal life, indexed universal life, and guaranteed universal life, including policy design, guarantees, and cash-value considerations. Final expense studies examine smaller policies, applicant ages, benefit structures, and underwriting requirements.
Our health and high-risk research considers circumstances such as diabetes, heart disease, cancer history, tobacco use, prior declines, aviation, diving, and hazardous occupations. These studies preserve the applicant context because a diagnosis or activity alone cannot describe every underwriting outcome.
How a study becomes a ranking
We create a standardized prompt and submit the same core scenario independently across the AI platforms included in the study. We record meaningful carrier recommendations, their position, supporting reasons, qualifications, and sources where available. Each included platform receives equal weight for basic recommendation coverage.
The recommendation data determines the consensus result. We then check material carrier, product, policy, and availability information where practical. Applicable research receives editorial review from Chris Huntley to help explain underwriting considerations, product differences, and limitations in the AI reasoning.
Experienced editorial review
Chris Huntley began working in life insurance in 2004 and spent nearly two decades in and around the industry. His experience includes working as a licensed agent, founding Huntley Wealth Insurance and Insurance Blog by Chris, co-founding JRC Insurance Group, and contributing life insurance commentary to Money.com and through the Forbes Finance Council.
Chris does not currently hold active insurance licenses. His role here is editorial and educational: he reviews accuracy, terminology, underwriting context, and potentially misleading generalizations. He does not sell insurance through the site, solicit applications, or provide individualized insurance, legal, tax, or financial advice.
Editorial review can challenge the interpretation of a result, but it does not change what the AI platforms recommended. A personal preference for another carrier cannot add or remove recommendation votes.
Ownership and editorial independence
Life Insurance Consensus Index is owned and operated by 3D Chess Media, LLC, a Nevada limited liability company. The site is a research and educational publication and does not issue life insurance policies.
We may earn revenue through affiliate and referral relationships, advertising, sponsorships, research, data licensing, and other commercial arrangements. Those relationships should remain separate from the research: carriers can appear and rank first without paying us, while commercial partners can rank poorly or receive criticism. Compensation cannot purchase recommendation counts, ranking positions, or changes to historical results.
Using the research in context
AI platforms can share sources, favor highly visible brands, or repeat outdated information. A lesser-known carrier may be underrepresented even when its products or underwriting are competitive for a particular applicant. Every result should be read alongside its research date, supporting facts, and disclosed limitations.
Only an insurer can determine an applicant's eligibility, underwriting class, premium, and final policy offer. Hypothetical prices and broad carrier recommendations cannot establish those outcomes. Our research helps readers compare recommendation patterns and understand insurance questions before reviewing current carrier information and, where appropriate, consulting a licensed professional.
We correct processing and factual errors and preserve historical research where practical. A later research cycle can produce a different result without making the earlier snapshot incorrect. Readers and insurance professionals can submit evidence and questions through our contact page.