关于

行为经济学与人类体验的交汇点,由此诞生了 Renascence 咨询公司。

René Studio
AI体验工作室

我们基于十年客户合作经验打造的客户体验设计平台。

探索 René Studio
Mysterya
神秘顾客审计,实时

我们运行的神秘审计,对每个地点进行实时评分。

探索 Mysterya
现正招聘

加入我们的团队,一起重塑世界体验品牌的方式。

查看开放岗位 →

公司

与我们共同成长

联系我们

服务

为企业品牌提供全面的客户体验和管理咨询。

René Studio
AI体验工作室

每一次互动,都在一个AI工作区中进行映射和评分。

探索 René Studio
Mysterya
神秘顾客审计,实时

神秘顾客,实时评分和取证。

探索 Mysterya
所有服务

探索 Renascence 提供的全方位客户体验和管理咨询服务。

浏览所有服务 →

核心业务

专家

解决方案

转化为可衡量的成果。" is smooth, authoritative, and perfectly captures the source meaning and tone.通过结构化解决方案,将 CX 愿景转化为可衡量的成果。

René Studio
AI体验工作室

借助AI,对我们重新设计的旅程进行绘制、评分和修复。

探索 René Studio
Mysterya
神秘顾客审计,实时

检查您设计的体验是否已交付。

探索 Mysterya
所有解决方案

探索我们提供的所有 CX 解决方案。

浏览解决方案 →

战略与治理

设计与交付

文化与体验

行业

跨越十年的客户体验转型,赋能本地区最具代表性的行业。

René Studio
AI体验工作室

AI 在数分钟内完成行业就绪旅程评分。

探索 René Studio
Mysterya
神秘顾客审计,实时

针对您所在行业量身定制的神秘顾客审计,实时评分。

探索 Mysterya
所有行业

了解我们如何服务各大行业。

浏览行业 →

建筑环境

金融与科技

人员与流动性

产品

Renascence专有的工具、平台和AI,赋能客户体验转型。

René Studio
AI体验工作室

利用AI设计、评估和优化客户旅程。

探索 René Studio
Mysterya
神秘顾客审计,实时

审计每个地点并根据发现采取行动。

探索 Mysterya
REBEL牌组A · 36种力量

塑造人类体验世界的各种力量。

探索 REBEL Reveal →
所有产品

探索 Renascence 的完整产品生态。

浏览产品 →

PLATFORMS

人工智能与技术

学习与框架

客户体验工具包

观点

Renascence:客户体验前沿的洞察、研究和对话。

René Studio
AI体验工作室

将您的阅读体验转化为可评分的旅程。

探索 René Studio
Mysterya
神秘顾客审计,实时

了解客户每次访问的真实体验。

探索 Mysterya
阅读体验日志关于CX、行为与转型的文章和研究。观看与收听体验蓝图我们的CX与行为视频播客。精选CX新闻CX行业重要新闻,去芜存菁。

最新文章

最新剧集

最新新闻

中心

免费工具、模板和资源,助您提升客户体验实践。

René Studio
AI体验工作室

利用AI设计、评估和优化客户旅程。

探索 René Studio
Mysterya
神秘顾客审计,实时

每次访问、每个地点、每个分数。实时呈现。

探索 Mysterya
宣言烧毁牌组。
十大美德。零借口。开始阅读 →
中心

所有免费工具、模板和资源尽在一个地方。

访问中心 →

AI 工具

免费工具

学习资料

文化

AI · 2026年10月12日

AI Trust: Daily US Users Still Worried, New Report Shows

A new report finds Americans who use AI daily are just as concerned about its risks and just as supportive of regulation as infrequent users, showing habitual use alone isn't building trust.

新闻中心
精选简报 · 2 分钟阅读
分享分享至 X分享至领英

What happened

A new report has found that Americans who interact with artificial intelligence tools on a daily basis are not noticeably more comfortable with the technology than those who rarely or never use it. According to the findings, frequent users of AI express similar levels of concern about its risks — and similar support for regulatory oversight — as infrequent users, suggesting that familiarity with AI tools is not, by itself, dissolving public unease.

The research indicates that repeated exposure to AI in daily tasks has not produced the kind of comfort or trust that often accompanies growing familiarity with other technologies. Heavy users appear just as likely as occasional users to want guardrails placed around how AI is developed and deployed.

Why it matters

For organisations racing to embed AI into products, services and workflows, this is a signal that usage and trust are not the same thing. Many digital transformation strategies implicitly assume that as adoption grows, scepticism will fade — that people will "get used to it." This report challenges that assumption: regular, habitual use of AI tools does not appear to be closing the gap between convenience and confidence.

That has direct implications for how AI-powered experiences are designed and communicated, and for how regulators and policymakers — including those shaping AI governance frameworks in the GCC and beyond — might read public sentiment. If daily users remain wary, organisations cannot rely on exposure alone to build trust; trust has to be designed in, not assumed as a byproduct of frequency.

The Renascence take

The finding runs counter to a comfortable industry narrative: that resistance to AI is really just a lag effect, destined to disappear as usage becomes routine. The data suggests something closer to a stable, structural wariness — one that sits alongside, rather than in opposition to, active use.

This is a classic behavioral-economics pattern: people can rationally adopt a tool for its convenience while simultaneously distrusting the system behind it — the two judgements run on separate tracks. Operators should stop treating "more usage" as a trust-building strategy and start treating transparency, control and recourse as the actual levers: visible explanations for AI decisions, easy opt-outs, and clear escalation to a human. Build for the sceptical daily user, not the imagined convert — because the report suggests that convert may never fully arrive.

来源

本简报由我们的新闻编辑部撰写,综合了以下媒体的报道。点击链接可查看原始报道。

FAQ

Questions we get on this topic

No. The report found that Americans who use AI tools daily show similar levels of concern about AI risks as those who use it rarely or never, indicating frequent use doesn't automatically build trust.

Yes. According to the findings, frequent AI users support regulatory oversight at rates comparable to infrequent users, showing that familiarity hasn't reduced demand for guardrails.

It suggests organisations can't rely on usage alone to build user trust; instead they need to design in transparency, user control, and clear human escalation paths.

The report illustrates that convenience-driven adoption and underlying distrust can coexist, meaning CX teams must actively design for scepticism rather than assume trust grows with exposure.

分享分享至 X分享至领英

保持CX领先

获取信号,而非噪音。

塑造客户体验的故事——以及《期刊》和“体验之梭”——尽在您的收件箱。