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AI-driven advisory in insurance services : An experimental study on trust, transparency, and policy adoption

Truvace record
TRV-2026-2541raw data (JSON)
Version
v1Published
First published
Evidence type
Randomized controlled trial
Sources
1 sourcePeer-reviewed
sha256
f8326af692c7…check it

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…

58Gain side

How the two sides scoreClose call

56Problem side

The gain

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.

The problem

In the same 90-person experiment, AI-only insurance advice raised cyber security and privacy concerns among consumers, which worked against adoption.

A fixed formula sets both scores from the evidence and its sources. Reader votes don’t move them.

What the scores mean

G is the gain side, out of 100. It goes up when the gain is specific, when it measurably helped people and when the sources behind it are strong.

P is the problem side, out of 100. It goes up when the problem is specific, when it measurably hurt people and when the sources behind it are strong.

What this doesn’t fix

The experiment involved only 90 consumers in a standardized policy selection scenario, which limits how far the results extend to real insurance purchases.

Sources

1 on file
  1. Journal of Information and Optimization Sciencesdoi:10.47974/jios-2449
    Peer-reviewed2026-09-30

Cite this record

v1

Truvace Impact Record TRV-2026-2541, v1: “AI-driven advisory in insurance services : An experimental study on trust, transparency, and policy adoption.” Truvace, 2026-11-12. /record/TRV-2026-2541 (accessed on the day you copy it). sha256 f8326af692c71ff9…

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  1. Publishedv1f8326af692c7…

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