Do you trust AI? Global perspectives
Trust in artificial intelligence isn’t monolithic—it shifts by industry, use case, and how familiar people are with the technology. Yet a few clear signals are emerging: people want transparency, they reward plain-language labeling, and hands-on experience often turns skepticism into comfort.
Key signals from consumers
- Transparency is non-negotiable: 83% of people want clear disclosure whenever AI is being used.
- Experience shapes comfort: 73% of AI users say they’re comfortable with the answers AI provides, compared with just 40% among non-users.
- Labels matter: About half of consumers say “AI-powered” labels would increase their trust.
Where AI earns trust
AI is most trusted in the technology, food, and entertainment sectors. In tech, AI’s utility is visible—think search, recommendations, coding assistants, and productivity tools. In food, trust tends to rise when AI enhances safety and logistics behind the scenes, or personalizes recommendations without feeling invasive. In entertainment, algorithmic curation is widely accepted as a convenience, provided there are controls to tune or turn off personalization.
Across other industries—finance, health, public services—the stakes and sensitivities are higher. People want stronger assurances about accuracy, accountability, and how decisions are made. The takeaway: context defines what “trusted AI” looks like, from playful recommendations to high-stakes decisions that demand human oversight.
The transparency effect
Clear disclosure is the biggest trust multiplier. When companies plainly state where AI is in the loop—and how it influences outcomes—consumers are more willing to engage. That aligns with the finding that half of consumers say “AI-powered” labels would boost their trust. Labels should be more than a badge, though: they should link to concise explanations of what the AI does, what data it uses, and how to get help from a human.
The experience gap
The difference between users and non-users—73% versus 40% comfort with AI answers—highlights the role of familiarity. Direct interaction demystifies the technology and helps people understand its strengths and limits. Thoughtful onboarding, examples of safe use, and visible guardrails can shorten the path from curiosity to confidence.
What organizations should do now
- Disclose clearly and consistently when AI is used, in plain language and at the point of interaction.
- Explain the “why” and “how”: what the AI is optimizing for, what data it relies on, and where its limits are.
- Offer user control: easy ways to opt in or out, adjust personalization, or escalate to a human.
- Show your work: provide citations, quality metrics, and safety practices where appropriate.
- Measure trust continuously across segments and scenarios, not just overall satisfaction.
How consumers can navigate AI
- Look for labeling and disclosures—seek out what “AI-powered” means in context.
- Check for recourse—can you verify results, correct errors, or reach a human when needed?
- Be mindful of data: understand what’s collected, how it’s used, and your control options.
- Treat AI as an assistant, not an oracle—use it to draft, explore, and compare, then verify.
The bottom line
Trust in AI is growing where the value is clear and the stakes feel manageable—technology, food, and entertainment lead the way. Across the board, transparency and real-world experience are the strongest drivers of confidence. Label it, explain it, and give people control, and trust follows.
