China is deploying artificial intelligence faster and more broadly than any other country in the world, but it is doing so against a backdrop of public trust that lags behind many of the nations it is outpacing. That is the central finding of a new survey reported by the South China Morning Post, which captures a paradox at the heart of China’s AI ambitions: the country that has moved most aggressively to embed AI into its economy and society is also the one where confidence in AI systems is most fragile.
The survey, conducted by a London-based consultancy, found that more than 90 percent of respondents globally believe AI will fundamentally transform the world, a figure that reflects the near-universal recognition of the technology’s significance. China’s deployment targets are among the most ambitious anywhere: the government has set a goal of 70 percent AI adoption across major industrial sectors by 2027, rising to 90 percent by 2030. By the metrics of infrastructure investment, model development, and institutional integration, China is on track to meet or exceed those targets.
The Trust Gap
Yet the same survey reveals a persistent gap between deployment ambition and public confidence. Chinese respondents expressed lower levels of trust in AI systems than their counterparts in several Western nations, a finding that cuts against the narrative of China as a society uniquely comfortable with surveillance technology and algorithmic governance. The trust deficit appears to be driven by a combination of factors: concerns about data privacy, uncertainty about how AI-driven decisions are made and by whom, and a broader anxiety about the pace of technological change in a society where the economic disruptions of automation are already visible.
The gap matters for reasons that extend beyond public sentiment. Trust is a prerequisite for the kind of deep AI integration that China’s government is pursuing. When workers distrust AI-assisted management systems, when patients are skeptical of AI diagnostic tools, when consumers hesitate before AI-powered financial services, and when citizens question AI surveillance deployed at national exams, the practical adoption rate falls short of the deployment mandate. The survey suggests that China’s AI rollout is running ahead of the social infrastructure, the norms, institutions, and experiences, that would allow people to engage with AI systems confidently.
This dynamic is not unique to China. Surveys in the United States and Europe have consistently found that public trust in AI lags behind industry enthusiasm, and that trust is highly sensitive to high-profile failures and perceived misuse. But China’s combination of rapid deployment scale and relatively low trust creates a particular tension: the systems are being embedded before the trust has been built, which increases the risk that a significant failure, a widely publicized AI error in a high-stakes domain, could trigger a backlash that sets back adoption across multiple sectors simultaneously.
Deployment as a Trust-Building Strategy
The Chinese government’s response to the trust gap has been characteristically top-down: accelerate deployment in domains where AI demonstrably improves outcomes, and allow the accumulation of positive experiences to build confidence over time. The logic is not unreasonable, trust in new technologies has historically been built through use, not through reassurance — but it requires that the early deployment experiences be genuinely positive, and that failures be managed transparently rather than suppressed.
China’s AI governance framework has been evolving rapidly in parallel with its deployment ambitions. Regulations on algorithmic recommendation systems, generative AI, and deep synthesis technology have established a legal architecture that, at least in principle, provides citizens with some visibility into how AI systems affect their lives. Whether that architecture is sufficient to close the trust gap is an open question, one that the survey’s findings suggest has not yet been answered to the satisfaction of the Chinese public.
International Implications
The trust gap also has implications for China’s ambitions in international AI governance. Beijing has been pushing for a greater role in setting global AI standards and norms, arguing that the current governance frameworks are dominated by Western assumptions and interests. But the credibility of that push depends in part on demonstrating that China’s own AI governance model is working — that deployment at scale can be achieved without the erosion of public confidence that the survey documents.
The finding that China leads in deployment but trails in trust is, in this sense, not merely a domestic policy challenge. It is a data point in the ongoing argument about which model of AI development, the American emphasis on market-driven innovation with post-hoc regulation, the European emphasis on rights-based governance, or the Chinese emphasis on state-directed deployment with centralized oversight, is best suited to the demands of the AI era. The survey suggests that none of the models has yet produced a satisfying answer to the question of how to build and sustain public trust in systems that are becoming increasingly consequential.