TITLE:
Artificial Intelligence in the Auto Insurance Market: Mechanisms of Empowerment, Consumer Perception, and Developmental Challenges
AUTHORS:
Zi Liu
KEYWORDS:
Artificial Intelligence, Auto Insurance, Smart Pricing, Smart Claims, Anti-Fraud, Consumer Survey
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.16 No.5,
May
28,
2026
ABSTRACT: Artificial intelligence (AI) is reshaping the value chain of the insurance industry, and auto insurance—one of the most important lines in China’s property insurance market—has become an active field for AI deployment. Drawing on a literature analysis combined with an online consumer questionnaire, this paper develops a three-dimensional analytical framework linking the value chain, key operational nodes, and corresponding AI technology families, and examines the mechanisms through which AI may empower pricing, claims handling, loss assessment, and anti-fraud activities. The survey retained 260 valid individual responses, among which 165 respondents reported prior experience with AI-enabled auto insurance services. To avoid mixing actual service experience with general expectations, usage-specific satisfaction analyses are conducted primarily among experienced users, while expectation-oriented analyses are conducted on the full sample. The findings show that consumers generally perceive AI-enabled auto insurance services positively: 76.25% of valid claim users are satisfied or very satisfied with claim efficiency, 90.18% of valid loss-assessment users regard AI loss-assessment information as clear or basically clear, and 83.64% of experienced users consider AI risk assessment accurate or comparatively accurate. Nevertheless, documentation burden, communication frictions, insufficient visualisation, weak deep personalisation, and the absence of clear dispute-resolution mechanisms remain salient pain points. At the industry level, data silos, inconsistent loss-assessment standards, product gaps for new energy and intelligent connected vehicles, privacy protection, and organisational change continue to constrain deeper AI adoption. The paper therefore offers mechanism-based and consumer-perception evidence on AI-enabled auto insurance, while recognising that further research using insurer-side operational performance data is needed to establish direct efficiency effects.