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Introduction Neurointerventional surgery involves minimally invasive procedures to treat cerebrovascular diseases, requiring high precision and rapid decision-making. Artificial Intelligence (AI) has the potential to revolutionize this field by enhancing diagnostic accuracy, procedural planning, and intraoperative guidance. However, the integration of AI raises significant ethical challenges that must be addressed to ensure patient safety, trust, and equitable care.Aim of Study This study aims to identify and analyze the key ethical issues arising from the implementation of AI in neurointerventional surgery, focusing on data bias, patient privacy, informed consent, accountability, and regulatory oversight.Method A systematic literature review was conducted across medical, ethical, and AI-focused databases to gather current evidence on AI applications in neurointerventional surgery and associated ethical concerns. Ethical frameworks and guidelines from healthcare and AI governance bodies were examined to contextualize these issues.Results The review identified several critical ethical challenges:Data Bias AI models trained on non-representative datasets risk perpetuating health disparities.Patient Privacy Handling sensitive neuroimaging and clinical data demands stringent security protocols.Informed Consent Patients must be adequately informed about AI’s role in their care and potential risks.Accountability Clear responsibility must be assigned for AI-driven decisions, especially in adverse outcomes.Regulatory Oversight Current regulations lag behind AI advancements, necessitating updated policies for validation and monitoring.Conclusion Ethical implementation of AI in neurointerventional surgery requires multidisciplinary collaboration to develop transparent, accountable, and patient-centered frameworks. Addressing these ethical issues proactively will foster trust and maximize AI’s benefits in improving neurovascular care.Conflict of Interest No