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Latest Swiss AI Report Echoes UK Concerns Over Tech Giants' Power

ended 03. April 2026

When 90 percent of a population believes an entire industry operates purely for profitand not the greater good for humanity, it is a legitimacy collapse.

Swiss Info reported on 1st April that a new  survey by Swiss research firm gfs.bern conducted in December 2025 found near-universal distrust of big tech among the Swiss public. Conducted for the Mercator Foundation Switzerland, the survey revealed that 

  • 90 percent of respondents view major technology companies as profit-driven
  • 94 percent want stronger protections for children on social media. 

Concerns extended to political influence: 

  • 84 percent fearing interference from the countries where these firms are based
  • 82 percent worried about growing dependency on US and Chinese corporations.

The Swiss findings mirror a broader pattern across G7 democracies. 

In the UK:

  • only 18 percent of people trust AI systems to make decisions, according to YouGov research from 2025
  • 84 percent fear the government will prioritise tech companies over public interest.

 Across France, Germany, and Spain, majorities believe existing regulations are insufficient, with roughly two-thirds willing to enforce stricter rules even if it strains relations with the United States.

What distinguishes the Swiss survey is the inversion it reveals. While trust in big tech has collapsed, 75 percent of respondents still trust Swiss authorities to act in their interest. The public is not rejecting technological progress. It is demanding that democratic institutions take control of it. 

  • 88 percent want the state to ensure that AI decisions are comprehensible. 
  • 86 percent insist on human oversight in critical situations.

We'd like your views:

  • If 88 percent of citizens demand comprehensible AI decisions, but enforcement mechanisms depend on voluntary corporate compliance, who carries accountability when transparency fails?
  • When trust in state institutions remains high (75 percent in Switzerland) but trust in platforms collapses (90 percent see them as profit-driven), what does effective regulation look like when the regulator lacks infrastructure sovereignty?
  • At what threshold does public concern about platform power translate into enforceable policy, given that economic dependency on these firms constrains regulatory action?
  • If citizens across G7 democracies consistently demand human oversight in AI systems (86 percent in Switzerland), but procurement budgets favour hyperscale US providers, where does responsibility sit when human review is bypassed for cost efficiency?
  • European governments are building sovereign alternatives (OpenDesk, Eurostack). If these initiatives take a decade and cost €300 billion, as analysts estimate, how do regulators manage public expectations in the interim while dependency persists?

2 responses from the Newspage community

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Colette MasonVerified
AI Ethics Consultant at Clever Clogs AI
This creates a governance problem that regulation alone cannot solve. All citizens are asking democratic governments to enforce rules on companies whose economic leverage often exceeds that of the states attempting to regulate them. When the International Criminal Court replaced Microsoft services with European alternatives in November 2025 after an access incident, it demonstrated that sovereignty concerns are operational, not theoretical.

When the French government moved away from Zoom and Microsoft Teams for sensitive communications, it acknowledged the same risk.

The gap is not between people and technology. It is between what citizens expect democratic institutions to accomplish and what those institutions can enforce against foreign tech giants whose infrastructure underpins national economies. Dependency is not an abstract geopolitical concern, it's a global one.
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Rohit Parmar-MistryVerified
Founder at Pattrn Data
When nine in ten people think Big Tech is in it purely for profit, that is not a PR problem. It is a legitimacy crisis, and it makes self-regulation dead on arrival.

What I see in AI audits is that the argument is rarely about innovation. It is about accountability. People are fine with powerful tools, but they want clear lines: who is responsible when something goes wrong, what evidence shows the system is safe, and what meaningful recourse exists when it is not.

The awkward bit is sovereignty. If we rely on hyperscalers for the infrastructure, data flows, and model updates, regulators end up policing decisions they cannot technically reproduce or inspect end to end. So what does effective regulation look like when the regulator does not control the underlying stack?