Trust in AI and Its Role in the Acceptance of AI Technologies

Trust is a critical factor in whether people will actually use AI technologies. Both studies found that trust significantly influenced people's intention to use AI systems, operating indirectly through how useful they perceived the technology to be and their overall attitude toward it.

There are two distinct types of trust that matter for AI acceptance: "functionality trust" and "human-like trust." Functionality trust—confidence that the AI will work reliably and do what it's supposed to do—had a greater impact on usage intentions than human-like trust (whether the AI seems natural or relatable), suggesting users prioritize competence over personality.

Building trust in AI requires demonstrating both usefulness and ease of use. The research shows that trust alone doesn't drive adoption; people also need to perceive the technology as actually helpful and easy to interact with, indicating that responsible AI development should focus on practical performance alongside trustworthiness.

Trust effects are consistent across different user groups and AI applications. The findings held true both for college students using voice assistants and for a representative sample of the general U.S. population, suggesting these trust dynamics are broadly applicable as AI becomes more widespread across different domains and demographics.