End-of-life care involves complex decisions that impact a patient's dignity and quality of life. The use of AI in this context raises both opportunities and ethical challenges. This article explores the potential future role of AI in end-of-life care. Pros of AI in End-of-Life Care Enhanced Decision-Making Through Data-Driven Insights: AI analyzes patient data, including genetic information, past treatment responses, and clinical trial outcomes, to provide evidence-based recommendations on effective palliative care options. AI can also predict outcomes and provide more accurate prognostic information to aid end-of-life care decisions. Personalized End-of-Life Care Plans: AI can integrate a patient's values and preferences to create customized care plans that respect their wishes while optimizing their comfort and dignity. AI considers medical aspects, personal preferences, and ethical principles to ensure ethical consistency in end-of-life decision-making. When healthcare providers' personal beliefs or biases affect end-of-life decisions, AI can provide an unbiased perspective, balancing decision-making by focusing solely on data and ethical frameworks. AI-driven systems base their recommendations on evidence and ethical frameworks, reducing the risk of decisions being influenced by emotions or biases. Furthermore, AI can ensure consistent application of ethical principles across cases, reducing variability in end-of-life decisions caused by differences in human interpretation of ethics. Supporting Family and Caregivers in Difficult Decisions: AI can provide data-backed scenarios, predict outcomes, and offer guidance that is in line with the patient's wishes. This could help families better understand the consequences of different decisions, alleviating some emotional burdens. Cons of AI in End-of-Life Care Depersonalization of Care: End-of-life care managed primarily by AI may lack the human element of compassion, empathy, and emotional support, leading to dissatisfaction and a sense of alienation. This loss of human touch can result in decreased trust in the system, as patients and families may feel their emotional and spiritual needs are being overlooked in favor of data-driven decisions. Ethical Dilemmas and Lack of Moral Intuition: AI systems may not align with diverse ethical and moral beliefs, potentially leading to conflicts in real-world situations. These systems may lack the flexibility to handle complexities in ethical dilemmas, especially when patients and families hold diverse values and beliefs. Data Privacy and Security Concerns: An AI system processes sensitive health and personal data to create a personalized end-of-life care plan. A breach could expose this information, violating patient confidentiality and undermining trust in AI-driven healthcare. Privacy violations and security risks are critical concerns for using AI in end-of-life care. Legal and Accountability Issues: A patient's family disputes an AI-based recommendation to end life-sustaining treatment, questioning who is responsible if the decision results in an unjust or unethical outcome. Determining accountability—whether it lies with the healthcare provider, the AI system developers, or the institution—can be legally challenging. Ambiguity in Liability: If an AI system recommends that leads to harm, it may be difficult to determine responsible parties.