Gallup survey of 37 countries: in 34, positive AI sentiment outweighed the negative; 90%+ of people in China and 66%+ in Nigeria say AI will improve daily life

Public opinion is broadly optimistic about AI's future, even where usage is low.

A Gallup survey conducted across 37 countries reveals that positive sentiment towards artificial intelligence (AI) generally outweighs negative sentiment, with this trend observed in 34 of the surveyed nations. While 81% of adults are aware of AI, only 43% have ever used it, and a smaller fraction uses it frequently. Adoption rates vary significantly by country, with Singapore showing high engagement and Malawi showing very low engagement. Despite lower adoption in many regions, a majority of AI-aware adults in 25 countries expect AI to improve their daily lives, and in 32 countries, optimists outnumber pessimists regarding AI's future impact. Notably, China and Vietnam show particularly high levels of optimism about AI's benefits for their countries. Trust in AI's accuracy, however, remains relatively low globally, with a median of only 36% trusting it completely or a lot across the surveyed nations, though trust increases with more frequent AI usage. Overall positive emotions toward AI are reported by a median of 72% of respondents, while negative emotions are reported by 41%.

The widespread positive sentiment toward AI, even in countries with low adoption rates, suggests a global optimism fueled by perception rather than direct experience. This disconnect between awareness and usage, coupled with high expectations, indicates a significant market opportunity for AI developers and providers to translate this potential into tangible, accessible applications. Companies that can effectively demonstrate AI's immediate benefits and build trust, particularly in emerging markets, could see rapid growth.

The findings highlight a crucial tension: while people are optimistic about AI, their trust in its accuracy is notably lower. This gap implies that early market success will likely depend on building robust systems that are not only functional but also demonstrably reliable and transparent. Future development should focus on user education and clear communication to bridge the trust deficit, potentially unlocking deeper engagement and more widespread adoption once initial skepticism is addressed.