Answer Capsule
AIG is a mixed-to-good fit for life insurance in high-risk occupations, but only as one candidate in a multi-carrier comparison. Three of the seven included platforms named AIG during the ranking stage (grok, kimi, perplexity), and six of seven returned a usable fit assessment. The strongest reason to consider it: multiple platforms describe AIG/Corebridge as unusually willing to accept hazardous occupations and to price risk through flat extras or table ratings rather than decline. The main limitation: no public source verifies AIG-specific occupational flat-extra schedules, and AIG's former life business now operates as Corebridge Financial, so the issuing company must be confirmed before purchase.
Research Snapshot
| Field | Finding |
|---|---|
| Platform mentions in ranking stage | 3 of 7 included platforms (grok, kimi, perplexity) |
| Share of included platform responses | 42.9% |
| Average listed rank | 3.0 |
| Best listed rank | 2 |
| Relevant product/model/plan | Term life and permanent life insurance historically associated with AIG Life & Retirement; current U.S. offerings generally presented through Corebridge Financial, including Select-a-Term |
| Overall use-case fit | Mixed (openai, perplexity), good (anthropic, grok), strong (google), uncertain (kimi) |
| Research date | 2026-09-22 |
Why AIG Qualified for This Study
Questions This Section Answers
- Is AIG a good choice for Life Insurance for High-Risk Occupations?
- Why did AIG qualify for this high-risk occupation life insurance study if only three platforms named it?
AIG qualified because it was named by three of the seven included platforms during ranking discovery and received a usable fit assessment from six of seven. Its fit ratings were split: google rated it "strong," anthropic and grok rated it "good," openai and perplexity rated it "mixed," and kimi rated it "uncertain" [1]. That spread is itself the finding — AIG is a plausible candidate, not a settled answer.
The entity also qualified on relevance rather than consensus. AIG's former Life & Retirement business became Corebridge Financial, which currently lists term life insurance and permanent life insurance as product categories [6]. Those are the two coverage structures a hazardous-occupation household typically compares. AIG's own annual report identifies Corebridge as its former life and retirement business and reports the separation and disposition of Corebridge ownership [7].
AIG did not qualify on verified occupational competitiveness. No supplied source demonstrates that AIG is price-competitive for commercial fishing, logging, mining, offshore work, or hazardous construction, and the ranking-stage description of "hazardous occupation underwriting" should be treated as unverified rather than as an established product feature [6].
The Product, Model, Plan, or Service Most Relevant to Life Insurance for High-Risk Occupations
Questions This Section Answers
- Which AIG or Corebridge life insurance product should a high-risk occupation buyer ask about first?
- Is AIG Select-a-Term the right plan for a commercial fisherman, logger, or offshore worker?
The relevant product is individual term life insurance, with permanent life insurance as the secondary option. Platforms most often pointed to AIG term life — Select-a-Term appears in third-party quote examples and product materials [9] — and to permanent coverage through the same carrier family [12].
The naming is inconsistent across platforms. Anthropic and kimi described "Term Life Insurance and Permanent Life Insurance with Hazardous Occupation Underwriting"; grok described "Term Life Insurance with hazardous occupation underwriting"; openai and perplexity described term and permanent coverage generally, with perplexity emphasizing Select-a-Term [14]. No supplied source verifies a product specifically named "Term Life Insurance with hazardous occupation underwriting" [12].
Corebridge product materials describe term, permanent, and final expense life insurance with quick approval and streamlined delivery features [13]. Corebridge also offers Max Accumulator+ and Value+ Protector Index Universal Life products using Agile Underwriting+ (AU+) for faster decisions [17]. Whether AU+ is available to a hazardous-occupation applicant is not verified; one platform reported that AU+ applies to standard cases and that high-risk applicants typically require full underwriting [18].
What the AI Platforms Agreed About
Questions This Section Answers
- Do AI platforms agree that AIG is friendly to high-risk occupations like commercial fishing and mining?
- Does AIG use flat extra fees instead of declining hazardous-occupation applicants?
The clearest area of agreement is underwriting posture: AIG/Corebridge is described as willing to accept occupational risk and price it, rather than decline outright. Independent sources call it "very friendly to hazardous occupations" and "the working man's insurance company" [19]. AIG field underwriting guides describe a holistic approach and acceptance of aviation, avocation, occupation, and foreign-travel flat extras [24].
Platforms also agreed on the mechanism. Hazardous occupations are handled through flat extras or table ratings added to base premiums rather than through blanket refusal [24]. Industry-wide flat-extra ranges cited across platforms run roughly $2.50–$5.00 per $1,000 of coverage for elevated occupational risk, with higher tiers reported for very high-risk work [27]. None of those figures is AIG-specific.
A third point of agreement: work-related death is generally not excluded from standard life insurance. The primary exclusions are typically suicide during the contestability period, misrepresentation, or specific policy terms [30]. This is a general market feature, not an AIG commitment.
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Is AIG actually competitive on price for high-risk occupations, or is that unverified?
- Does AIG still issue new U.S. life policies under the AIG name, or only through Corebridge?
The largest disagreement is whether AIG is genuinely competitive for hazardous occupations. Google rated the fit "strong" and described AIG as "industry-leading" for high-risk workers [32]. Kimi rated it "uncertain," noting that no retrieved source confirmed AIG's underwriting appetite, rate competitiveness, or specialized structures for hazardous professions [34]. Openai and perplexity both landed on "mixed," with openai stating that public evidence does not show AIG is unusually competitive for hazardous occupations [35].
Corporate identity is a second unresolved issue. AIG's former Life & Retirement business is now Corebridge Financial, and AIG reports the separation and disposition of Corebridge ownership [38]. One platform reported that Corebridge Financial and Equitable Holdings announced an all-stock merger expected to close by the end of 2026, with independent operations maintained until then [39]. That claim is platform-reported and not corroborated elsewhere in the supplied evidence.
Pricing transparency is a third gap. AIG does not publish occupational surcharge rates, flat-extra schedules, or rate tables for high-risk occupations in the materials reviewed [40]. Illustrative third-party quotes for healthy applicants sit in the low tens of dollars per month, but none is occupation-specific [41].
A fourth uncertainty concerns accelerated underwriting. Some AIG term materials and reports indicate non-medical underwriting may be available in certain situations, but eligibility for high-risk occupations is unclear [44]. One platform reported that high-risk occupational cases likely do not qualify for AU+ [46].
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- What underwriting features does AIG offer that matter for a hazardous-occupation life insurance applicant?
- Can AIG's Flex Points program reduce the cost of coverage for a high-risk job?
The most concrete AIG-specific feature in the evidence is the Flex Points crediting program. Corebridge field underwriting materials describe Flex Points as applying to cases aged 18–70 to improve rating classes, using medical research to upgrade underwriting ratings [47]. The same materials state that flat extra ratings cannot be used by the Expanded Standard program, which limits how much credit a flat-extra case can receive [47].
Rating-class structure matters for this buyer. AIG underwriting guides indicate that Preferred classes do not permit ratable occupations, while Standard and Standard Plus classifications allow occupational adjustments [50]. In practice, a hazardous-occupation applicant is likely to land in a Standard-tier class with a flat extra rather than a Preferred class.
Coverage structure and servicing are also relevant. Corebridge provides online life-insurance policy management, premium payment, and claims-support functions, with availability dependent on the product [52]. Term products are described with standard level-premium periods, and one platform reported term minimum face amounts of $50,000 up to $10 million with a return-of-premium option under age 55 [53]. Those figures are platform-reported and not confirmed against a current AIG or Corebridge product filing.
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does AIG life insurance cost per month for someone in a high-risk occupation?
- What flat extra or table rating should a high-risk occupation buyer expect from AIG?
AIG does not publish occupational surcharge rates, flat-extra fees, or rate tables for high-risk occupations in the materials reviewed, so no reliable AIG-specific monthly cost can be stated here [54]. Pricing confidence across platforms was uniformly low.
What the evidence does describe is the pricing mechanism. Base term premiums are set by age, health class, coverage amount, term length, and state, then occupational risk is layered on as a flat extra or table rating [57]. Industry-wide flat-extra ranges cited across platforms run about $2.50–$5.00 per $1,000 of coverage for elevated occupational risk, with higher tiers reported for very high-risk work such as commercial diving [59]. One platform translated a $2.50 per $1,000 flat extra into roughly $250 per year per $100,000 of face value [59].
Contract terms are form- and state-specific and were not verified for any particular quote. Platforms flagged that term coverage generally lasts for the selected level-premium period and may become more expensive afterward, that permanent policies can lapse if required premiums or policy values are insufficient, and that free-look, cancellation, conversion, contestability, and reinstatement terms must be read in the contract [62]. One platform reported a standard 30-day free-look period and term periods of 10, 15, 20, or 30 years [64]. Another reported 18 term period options [63]. Those two statements conflict and neither was verified against a current policy form.
Best Suited For
Questions This Section Answers
- Who is AIG life insurance actually best for among high-risk occupation applicants?
AIG is best suited to applicants who want a mainstream carrier with both term and permanent options and who are willing to work through an independent broker to test AIG's specific appetite for their occupation [65]. It also suits applicants whose duties include significant supervisory or administrative time, which may reduce the risk classification [66].
Platforms specifically named commercial fishermen, miners and underground workers, offshore and oil/gas extraction workers, and construction workers in hazardous roles as plausible fits [67]. AIG is also cited as strong for international or offshore workers, though specific geographic and jurisdictional limits were not clarified [67].
A final fit category: applicants who value holistic underwriting over speed. AIG's documented approach weighs favorable factors against occupational risk, which can produce a lower rating than a purely formula-driven carrier [70].
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose AIG for Life Insurance for High-Risk Occupations?
AIG is probably not the best choice for applicants who need published, occupation-specific acceptance rules before applying. No authoritative, current U.S.-specific hazardous-occupation underwriting guide was verified in the supplied evidence [73].
It is also a poor fit for buyers who need guaranteed-issue or simplified-issue coverage. AIG does not offer guaranteed issue for high-risk occupations according to one platform, and no-exam options were not confirmed as an AIG strength for this segment [76].
Applicants who need a fast decision should look elsewhere. High-risk occupational cases likely require traditional full underwriting with a medical exam and labs, which one platform described as typically 30–90 days [78]. Aviation-related occupations face additional restrictions even under occupational flat-extra ratings [79]. And buyers who want to deal directly with AIG as the current issuer of new U.S. individual life policies should first confirm the actual issuing carrier, because the life business now sits under Corebridge [80].
When Another Option May Be Better
Questions This Section Answers
- When is a different carrier a better choice than AIG for a high-risk occupation?
- What should a buyer compare against AIG before signing a high-risk occupation life insurance contract?
Another carrier may be better whenever it returns a written preliminary underwriting decision with a lower occupational flat extra or better rating for the applicant's exact duties [81]. Because AIG does not publish occupational rates, a competing carrier with published surcharge structures is easier to compare before applying [82].
Specialty markets are a second trigger. If the applicant needs a broker-accessible carrier with documented experience in offshore, aviation, commercial fishing, logging, or mining, a specialist may outperform a mainstream carrier [81]. One platform noted that some carriers have actuarial data and pricing structures calibrated to specific high-risk occupations, while others price conservatively or decline [83].
Guaranteed-issue and simplified-issue needs are a third trigger, as are armed-forces deployment scenarios where war-risk accommodations may matter more than occupational flexibility [81]. Finally, if the applicant needs a fully current direct-to-consumer product and the issuer, availability, or occupational rules cannot be clearly identified, another carrier is the safer path [81].
Questions to Verify Before Buying
Questions This Section Answers
- What should a buyer confirm with AIG or Corebridge before signing a high-risk occupation life insurance contract?
Confirm the issuing entity first: which legal insurance company will issue the policy, and is it a Corebridge subsidiary rather than the AIG parent [85]. Then confirm occupational acceptance: does the underwriter accept the applicant's exact duties, including work at height, underground work, offshore work, commercial vessels, heavy machinery, explosives, confined spaces, or seasonal exposure [85].
Ask what the occupation produces — standard, table-rated, flat-extra, exclusionary, postponed, or declined — and if a flat extra applies, its amount, duration, and whether it can be removed after documented duty changes [85]. Ask whether work-related death exclusions or restrictions exist and whether they apply to the applicant's actual duties or travel [87].
Verify conversion rights from term to permanent coverage without new medical underwriting, and the age or policy year limits [85]. Request the guaranteed premiums, renewal premiums, conversion charges, riders, and policy fees in writing [85]. Ask what exam, medical-record, financial, driving, travel, aviation, and watercraft information will be required [85]. Finally, ask whether an independent broker can obtain comparable preliminary offers from multiple carriers using the same complete occupational description [85].
Final AI Consensus Verdict
AIG is a conditional candidate, not a default pick. Six of seven included platforms returned a usable fit assessment, and their ratings ranged from "strong" to "uncertain," which is a genuine split rather than a consensus [90]. The strongest supported claim is that AIG/Corebridge is willing to underwrite hazardous occupations using flat extras and table ratings instead of declining [92]. The weakest link is verification: no supplied source confirms AIG-specific occupational flat-extra amounts, current U.S. acceptance rules, or a product formally named for hazardous-occupation underwriting [95].
For a buyer in commercial fishing, logging, mining, offshore work, or hazardous construction, the practical path is to have an independent broker submit the same complete occupational description to AIG/Corebridge and to at least two carriers with documented experience in that specific occupation, then compare the written offers. The Life Insurance for High-Risk Occupations consensus index shows how AIG ranks against the other carriers that cleared this study. Buyers comparing carriers across health and occupational categories can also browse the broader life insurance directory.
How This Review Was Produced
This review was generated from seven configured AI platforms, each asked which life insurance carriers are generally worth considering for applicants in high-risk occupations. Six of seven returned a usable fit assessment for AIG; three of seven named AIG during ranking discovery. Platform responses were normalized into a common schema covering fit rating, strengths, limitations, pricing and terms, and questions to verify before buying. All factual claims are cited to the platform that supplied them. The study research date is 2026-09-22.
Methodology Limitations
Platform-reported research dates differ from the authoritative run date: anthropic reported 2026-01-15, while google, grok, kimi, openai, and perplexity reported 2026-09-23. Those dates are provenance metadata and do not independently prove freshness. Six of seven included platforms returned a usable fit assessment, so the fit findings are not unanimous and should not be described as such; platform mention counts reflect only platforms that named AIG during ranking discovery.
The supplied URLs were collected from platform responses and were not independently validated by the writer stage. Citations are platform-reported evidence, not independently verified facts. Several claims in this review — including the reported Corebridge–Equitable Holdings merger timeline, term minimum face amounts, and the number of available term periods — come from single platforms and were not corroborated elsewhere in the supplied evidence. AIG's official pages retrieved for this study contained investor-relations and terms-of-use content only, and did not verify product, pricing, or underwriting details. No public occupation-specific underwriting manual, premium table, exclusion schedule, or binding acceptance rule was located for the occupations in this use case.
Sources
Company-Owned Sources
- Life Insurance Field Underwriting Guide: http://www.cassaniinsurance.com/wp-content/uploads/2023/12/AIG-Underwriting-Guide.pdf
- Life Insurance for High-Risk Occupations: https://fidelitylife.com/life-insurance-basics/life-insurance-101/life-insurance-for-high-risk-occupations/
- Field Underwriting Guide: https://lbfg.net/wp-content/uploads/AIG-Field-Underwriting-Guide.pdf
- First Responders Life Insurance: https://www.afba.com/who-we-serve/first-responders-life-insurance/
- AIG 2025 Annual Report: https://www.aig.com/home/investor-relations/aig-2025-annual-report
- Life Insurance Field Underwriting Guide: https://www.corebridgefinancial.com/content/dam/marketing/corporate/en/corp-site/connext/documents/underwriting/life-field-underwriting-guide.pdf
- Life Insurance | Corebridge Financial: https://www.corebridgefinancial.com/content/marketing/corporate/en/corp-site/what-we-offer/life-insurance
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- Who We Are | Corebridge Financial: https://www.corebridgefinancial.com/ir/ria/who-we-are
- Support | Corebridge Financial: https://www.corebridgefinancial.com/support
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- Occupation and armed forces underwriting limits: https://www.legalandgeneral.com/adviser/protection/underwriting/occupation-and-armed-forces
- Life Insurance Field Underwriting: https://www.pinneyinsurance.com/images/underwriting/AIG--AGLC101638.pdf
- Official pricing and terms source: https://www.aig.com/home
- Official pricing and terms source: https://www.aig.com/terms-of-use
Additional AI research evidence96 records
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record grok:10
- AI research evidence record perplexity:c5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c2
- AI research evidence record openai:c3
- AI research evidence record openai:c5
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c6
- AI research evidence record openai:c2
- AI research evidence record google:1.2.3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record grok:10
- AI research evidence record google:2.2.7
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c1
- AI research evidence record anthropic:c5
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record grok:10
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record kimi:shieldpath_5
- AI research evidence record kimi:trinity_6
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
- AI research evidence record openai:c3
- AI research evidence record google:3.1.7
- AI research evidence record anthropic:c1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c3
- AI research evidence record perplexity:c6
- AI research evidence record perplexity:c7
- AI research evidence record anthropic:c7
- AI research evidence record google:3.1.1
- AI research evidence record google:3.2.1
- AI research evidence record google:3.4.1
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record openai:c6
- AI research evidence record grok:11
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record perplexity:c5
- AI research evidence record anthropic:c2
- AI research evidence record grok:10
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record openai:c1
- AI research evidence record anthropic:c7
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c1
- AI research evidence record google:3.1.8
- AI research evidence record google:3.3.2
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record perplexity:c4
- AI research evidence record perplexity:c5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c1
- AI research evidence record kimi:accuquote_2
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c3
- AI research evidence record openai:c3
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record kimi:afba_3
- AI research evidence record openai:c1
- AI research evidence record openai:c3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:shieldpath_5
- AI research evidence record perplexity:c5
- AI research evidence record google:3.1.5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record google:3.1.8
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
Independent Sources
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- Insurance Topics | Accelerated Underwriting: https://content.naic.org/insurance-topics/accelerated-underwriting
- AIG Enhances Select-A-Term - Insurance News - InsuranceNewsNet: https://insurancenewsnet.com/oarticle/aig-enhances-select-term
- Life Insurance for High-Risk Jobs 2025: https://insuredbytrinity.com/life-insurance-for-high-risk-occupations-a-2025-guide-to-coverage-and-costs/
- Life Insurance for High-Risk Jobs: Blue-Collar Trades Complete Guide: https://shieldpath.org/blog/life-insurance-for-high-risk-jobs-blue-collar-trades-guide
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Additional AI research evidence96 records
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record grok:10
- AI research evidence record perplexity:c5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c2
- AI research evidence record openai:c3
- AI research evidence record openai:c5
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c6
- AI research evidence record openai:c2
- AI research evidence record google:1.2.3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record grok:10
- AI research evidence record google:2.2.7
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c1
- AI research evidence record anthropic:c5
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record grok:10
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record kimi:shieldpath_5
- AI research evidence record kimi:trinity_6
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
- AI research evidence record openai:c3
- AI research evidence record google:3.1.7
- AI research evidence record anthropic:c1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c3
- AI research evidence record perplexity:c6
- AI research evidence record perplexity:c7
- AI research evidence record anthropic:c7
- AI research evidence record google:3.1.1
- AI research evidence record google:3.2.1
- AI research evidence record google:3.4.1
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record openai:c6
- AI research evidence record grok:11
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record perplexity:c5
- AI research evidence record anthropic:c2
- AI research evidence record grok:10
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record openai:c1
- AI research evidence record anthropic:c7
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c1
- AI research evidence record google:3.1.8
- AI research evidence record google:3.3.2
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record perplexity:c4
- AI research evidence record perplexity:c5
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- AI research evidence record anthropic:c1
- AI research evidence record kimi:accuquote_2
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c3
- AI research evidence record openai:c3
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record kimi:afba_3
- AI research evidence record openai:c1
- AI research evidence record openai:c3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:shieldpath_5
- AI research evidence record perplexity:c5
- AI research evidence record google:3.1.5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record google:3.1.8
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
Other Sources
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Additional AI research evidence96 records
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record grok:10
- AI research evidence record perplexity:c5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c2
- AI research evidence record openai:c3
- AI research evidence record openai:c5
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c6
- AI research evidence record openai:c2
- AI research evidence record google:1.2.3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record grok:10
- AI research evidence record google:2.2.7
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c1
- AI research evidence record anthropic:c5
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record grok:10
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record kimi:shieldpath_5
- AI research evidence record kimi:trinity_6
- AI research evidence record google:3.1.5
- AI research evidence record google:3.1.8
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record openai:c1
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
- AI research evidence record openai:c3
- AI research evidence record google:3.1.7
- AI research evidence record anthropic:c1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c2
- AI research evidence record perplexity:c3
- AI research evidence record perplexity:c6
- AI research evidence record perplexity:c7
- AI research evidence record anthropic:c7
- AI research evidence record google:3.1.1
- AI research evidence record google:3.2.1
- AI research evidence record google:3.4.1
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record openai:c6
- AI research evidence record grok:11
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record perplexity:c5
- AI research evidence record anthropic:c2
- AI research evidence record grok:10
- AI research evidence record google:2.2.4
- AI research evidence record anthropic:c6
- AI research evidence record kimi:trustmypolicy_7
- AI research evidence record openai:c1
- AI research evidence record anthropic:c7
- AI research evidence record google:1.2.3
- AI research evidence record openai:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c1
- AI research evidence record google:3.1.8
- AI research evidence record google:3.3.2
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record anthropic:c4
- AI research evidence record perplexity:c4
- AI research evidence record perplexity:c5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c1
- AI research evidence record kimi:accuquote_2
- AI research evidence record anthropic:c7
- AI research evidence record anthropic:c3
- AI research evidence record openai:c3
- AI research evidence record openai:c1
- AI research evidence record anthropic:c1
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record kimi:afba_3
- AI research evidence record openai:c1
- AI research evidence record openai:c3
- AI research evidence record anthropic:c1
- AI research evidence record kimi:shieldpath_5
- AI research evidence record perplexity:c5
- AI research evidence record google:3.1.5
- AI research evidence record kimi:diversifiedquotes_1
- AI research evidence record anthropic:c2
- AI research evidence record anthropic:c3
- AI research evidence record google:3.1.8
- AI research evidence record openai:c2
- AI research evidence record perplexity:c5
Verify this research
Check when the research was run, which platforms were included, and what supports the findings.
- Study date
- September 22, 2026
- Platforms analyzed
- 7
- Source records
- 41
- Ranking mentions
- 3 of 7
- Platform share
- 43%
- Final consensus rank
- #6
Behind the findings
Platforms in this study
- ChatGPT
- Claude
- DeepSeek
- Grok
- Perplexity
- Kimi
- Gemini
Source records
24 independent · 15 company-owned · 2 unclear
Evidence support
24 direct · 17 partial
Keep in mind
Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.
Technical verification details
Use this SHA-256 fingerprint to identify the source snapshot associated with this study.
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