Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising advancements in diagnostic precision, personalized treatments, and resource management. The successful implementation of AI in specialized fields like nursing depends heavily on public acceptance and trust. This study explores public perceptions of AI in nursing, particularly focusing on telenursing in Saudi Arabia. The study aims to assess public awareness, perceptions, and concerns regarding AI in nursing, with a focus on understanding acceptance levels and identifying barriers to AI adoption in healthcare. A quantitative cross-sectional design was employed using an online questionnaire distributed to participants aged 18 years and above across Saudi Arabia. The questionnaire covered five areas: demographic information, awareness of AI in healthcare, perceptions of AI in nursing, concerns and barriers, and future expectations. Descriptive statistics and advanced analysis such as Chi-Square and logistic regression were conducted using SPSS. Of the participants, 49.9% were between the ages of 25-34, with females constituting 66.4% of the sample. A significant majority (85.2%) had heard of AI in healthcare, and 68.7% were aware of AI applications in nursing. Most participants (53.4%) were somewhat comfortable with AI in nursing, and 44.5% believed AI would improve nursing care quality. Concerns about data privacy (37.2%) and loss of human touch (33.9%) were prominent. Advanced analysis revealed several significant associations. A Chi-Square test indicated a significant relationship between education level and comfort with AI in nursing (χ² = 18.47, p < 0.01), with participants holding higher education levels reporting greater comfort. Similarly, there was a significant association between age group and willingness to participate in AI-related educational courses (χ² = 22.68, p < 0.01), with younger participants being more willing to engage in such opportunities. Logistic regression further demonstrated that education level was a strong predictor of trust in AI assistance, with participants holding higher education degrees being 1.5 times more likely to trust AI in nursing care (p < 0.01). The study indicates that public perceptions of AI in nursing in Saudi Arabia are generally positive, with strong awareness and acceptance levels. However, concerns about data privacy, job displacement, and the loss of human connection in care remain significant barriers to full acceptance. Addressing these concerns through education and policy development will be crucial for the successful integration of AI in nursing.