Trust underpins the acceptance and sustained adoption of AI. Yet many enterprises are at an early stage of understanding how to support trust in their deployment of AI. Drawing on our large survey of public attitudes toward AI across 17 countries (N = 17,193), we find low levels of public trust and acceptance of AI systems, particularly in countries with advanced economies. This low trust is underpinned by shared concerns about the risks of AI across all countries, despite the majority of people expecting benefits from AI use. We find a clear public mandate for robust governance and regulation of AI systems to mitigate these risks and universal endorsement of the principles and practices of trustworthy AI across countries. Yet current safeguards are falling short of public expectations. Drawing on trust theory, we propose four pathways to support trust and acceptance of AI—the institutional, motivational, uncertainty, and knowledge pathways. We test these pathways using structural equation modelling, finding strong support for the model. Taken together, the findings suggest that enterprises can strengthen trust in their use of AI by (a) designing and deploying AI in ways that create demonstrable benefit for stakeholders, (b) implementing robust governance and assurance mechanisms to mitigate risks and demonstrate trustworthy use of AI, and (c) supporting AI literacy.