AI's Growth Stunted by Lack of Public Trust

While politicians emphasize AI's potential for growth and efficiency, a recent report highlights a significant trust deficit among the public. Widespread skepticism is creating major challenges for government initiatives.

A comprehensive study by the Tony Blair Institute for Global Change (TBI) and Ipsos quantifies this unease. It reveals that lack of trust is the primary reason people hesitate to use generative AI. This isn't just a vague concern—it's a real obstacle to the AI revolution that politicians champion.

Public trust in AI increases with usage

The report identifies a notable divide in public perception. Over half of respondents have experimented with generative AI tools in the past year, representing rapid adoption for technology that was virtually unknown just years ago.

Yet nearly half the population has never used AI personally or professionally. This usage gap creates vastly different perspectives on AI's development. Data indicates that familiarity with AI correlates strongly with trust levels.

Among those who have never used AI, 56 percent view it as a societal risk. For weekly users, this concern drops to just 26 percent—demonstrating how firsthand experience reduces apprehension. Without positive exposure to AI, people are more likely to believe alarming narratives. Direct experience also helps counter exaggerated fears about widespread job replacement.

Demographic factors further shape these trust divides. Younger generations generally express more optimism, while older adults remain cautious. Technology professionals feel prepared for AI's advancement, but workers in healthcare and education—sectors facing significant AI impact—report much lower confidence levels.

It’s not what you do, it’s the way that you do it

The report's most revealing insight concerns how public acceptance varies by application.

People generally welcome AI in traffic management or medical diagnostics because they see clear benefits to their daily lives—technology that visibly serves human needs.

But attitudes shift dramatically regarding workplace monitoring or political advertising. Acceptance plummets when AI feels intrusive or manipulative. This suggests public concern centers not on AI technology itself, but on its intended purposes and ethical boundaries.

People want assurance that AI serves societal good and that robust regulations prevent technology companies from operating without oversight.

How do we increase public trust in AI to support growth?

The TBI report proposes concrete steps to build what it terms "justified trust."

First, governments must reframe their AI narrative. Instead of abstract economic promises, they should highlight tangible benefits: faster medical appointments, streamlined public services, or reduced commute times. Demonstrating real-world value matters more than theoretical advantages.

Second, evidence of effectiveness is crucial. When implementing AI in public services, officials must show how it improves outcomes for citizens—not just operational efficiency. Success should be measured by user experience, not technical metrics alone.

Finally, robust regulation and education are essential. Regulators need authority and expertise to oversee AI development, while citizens require training to use these tools safely and effectively. The objective is collaborative technology that empowers people, rather than something imposed upon them.

Ultimately, building public trust in AI requires trust in the institutions guiding its development. If governments demonstrate genuine commitment to responsible AI that benefits everyone, public acceptance will likely follow.

See also: Trump jokes about AI while US and UK sign new tech deal

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