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TRUVACE RECORD VERSION
record: TRV-2026-2541
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T07:50:50.123358Z
status: published
lens: trace
sector: business
headline: AI-driven advisory in insurance services : An experimental study on trust, transparency, and policy adoption
dek: Purpose: The rise of artificial intelligence (AI) in insurance advisory services has transformed how insurers advise their customers; however, empirical comparisons of alternative configurations of advisory services are limited.This study investigates the effects of AI-only, human-only, and hybrid human-AI advisory models on consumer trust, perceived transparency, perceived risk, and policy purchase intent.Design/methodology/approach: An experiment was designed to compare three advisory groups: AI only, human on…
gain_title: In a randomized experiment with 90 insurance consumers, hybrid human-AI advice produced the most trust, perceived transparency and policy purchase intent of the three advisory models tested.
problem_title: In the same 90-person experiment, AI-only insurance advice raised cyber security and privacy concerns among consumers, which worked against adoption.
trace_subject: AI-only versus hybrid advisory models in insurance policy selection
gain_reading: In a randomized experiment with 90 insurance consumers, hybrid human-AI advice produced the most trust, perceived transparency and policy purchase intent of the three advisory models tested.
gain_evidence: hybrid human-AI advisory creates the most trust, perceived transparency, and purchase intent
problem_reading: In the same 90-person experiment, AI-only insurance advice raised cyber security and privacy concerns among consumers, which worked against adoption.
problem_evidence: raises cyber security and privacy concerns, which works against adoption
quick_read: A randomized experiment with 90 insurance consumers compared three ways of getting advice on a standardized insurance policy selection: AI only, human only, and a hybrid of human and AI. The hybrid model produced the most trust, perceived transparency and intent to buy a policy.

AI-only advice was seen as more efficient, but it also raised cyber security and privacy concerns, which worked against adoption. The findings matter for insurers deciding how much of the advisory role to hand to automated systems in a trust-dependent financial service.

The analysis also found that the advisory mode mediated the link between perceived transparency and perceived risk and consumer outcomes. AI literacy and prior claim experience shaped which advisory mode people preferred. The sample is small and the scenario was standardized rather than a real purchase.
limitation: The experiment involved only 90 consumers in a standardized policy selection scenario, which limits how far the results extend to real insurance purchases.
tag: Dual reading
key_points: The experiment randomly assigned 90 insurance consumers to AI-only, human-only or hybrid human-AI advice. | Participants went through a standardized insurance policy selection scenario. | Hybrid advice scored highest on trust, perceived transparency and purchase intent. | AI-only advice raised perceived efficiency but also cyber security and privacy concerns. | Advisory mode mediated the relationship between perceived transparency, perceived risk and consumer outcomes. | AI literacy and prior claim experience moderated which advisory mode people preferred.
rundown: The researchers used a between-groups randomized design, so each of the 90 insurance consumers saw only one advisory model. They measured trust, perceived transparency, perceived risk and policy purchase intent with validated scales.

Analysis combined analysis of variance, mediation and moderation tests using the PROCESS macro, with robustness checks using structural equation modelling. The authors say this gives causal evidence on the effect of AI in insurance advisory.

The results suggest AI-only advice gains perceived efficiency but loses ground on privacy and security worries, while hybrid advice holds up better. The authors point to the strategic value of hybrid human-AI systems in financial services where trust is essential.
sources:
- peer_reviewed | Journal of Information and Optimization Sciences | https://doi.org/10.47974/jios-2449 | 2026-09-30
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