This chapter examines the ethical, confidentiality, data protection, and legal dimensions of clinical audits and quality improvement (QI) projects. Unlike clinical research, these initiatives evaluate and improve existing healthcare practices without introducing new interventions or altering patient care pathways. They rely on routinely collected data such as patient records, nursing documentation, blood bank logs, and operating theatre entries to identify gaps and strengthen quality of care. The chapter addresses key ethical dilemmas related to patient surveys, publications, and the handling of identifiable data, providing practical approaches to resolve them. It emphasizes that clinical audit is an educational, confidential, and non-punitive exercise, where both patient and staff confidentiality must be safeguarded. Global and national regulations governing data privacy and digital health are discussed, highlighting their role in ensuring responsible data use. With the rise of artificial intelligence (AI) and machine learning (ML) in healthcare, the chapter also explores emerging challenges in data governance, consent, and ethical deployment. It outlines measures to protect confidentiality, promote accountability, and uphold ethical integrity and ensuring that clinical audits continue to serve their core purpose of improving patient safety and care quality within a legally compliant and ethically sound framework.