Patient trust in artificial intelligence diagnostics may hinge more on regulatory credibility than on having doctors directly supervise AI systems—a finding that could reshape how hospitals implement AI tools. While conventional wisdom suggests patients prefer human oversight, new evidence points to governance mechanisms as the dominant trust factor. A national survey of US adults presented participants with hypothetical AI-assisted diagnostic scenarios, systematically varying six key attributes: clinician presence, AI performance levels compared to general practitioners and specialists, governance credentials including FDA approval and institutional certifications, and underlying data quality. Participants consistently chose visits and expressed higher trust when AI systems carried FDA approval, regardless of whether a physician was present to oversee the technology. This preference held even when comparing high-performing AI systems with different governance structures. The research challenges assumptions about patient preferences in the emerging landscape of AI-assisted healthcare. From a practical standpoint, these findings suggest healthcare systems may achieve greater patient acceptance by prioritizing regulatory approval and transparent governance frameworks over emphasizing physician involvement in AI workflows. However, the study's limitations are significant: hypothetical scenarios may not reflect real-world decision-making under medical stress, and the sample was limited to English-speaking adults with internet access. Additionally, trust expressed in surveys may differ substantially from actual behavior when facing serious health decisions. This represents confirmatory evidence for the importance of institutional credibility in healthcare technology adoption, though real-world validation remains essential.