The main problem with integrating artificial intelligence is that it needs to be trained and fixed after mistakes are made; but when dealing with such sensitive data mistakes can’t be made. This will likely cause these systems to be trained in a lab simulated setting further increasing the implementation of these systems. After implementation, healthcare organizations using these systems will need to comply with various regulations and standards designed to protect patient data. This includes the Health Insurance Portability and Accountability Act (HIPAA) in the United States or the General Data Protection Regulation (GDPR) in Europe. These regulations impose strict guidelines on how patient data should be handled, stored, and shared. While neither HIPAA or GDPR explicitly prohibits the use of AI for managing patient information, the process will prove to be quite the challenge. Any artificial intelligence companies acting as business associates working with such data under HIPAA must have a Business Associate Agreement (BAA) with healthcare providers and meet the security standards required of humans handling Protected Health Information (PHI). In addition to this, the GDPR also introduces the “right to explanation,” meaning that all individuals who have their data stored with such technology will have the right to understand how their data is being used by AI systems, which poses additional challenges in both explaining the artificial intelligence’s decision-making process as well as not providing enough information so that the data could be breached. To address privacy concerns and meet these regulations, healthcare providers can utilize techniques like anonymization and data-de–identification. These methods involve removing or obfuscating personally identifiable information (PII) from datasets, making it almost impossible to trace data back to individual patients. While this does help protect privacy, it also poses challenges for data analysis, as de-identified data is far less useful for certain AI applications. In this way, meeting the regulations of HIPAA and GDPR respectively, may indirectly worsen the performance and hinder the speed of improvements for these artificial intelligence systems. It is not a feasible option to contravene from these regulations as non-compliance can result in severe penalties, legal consequences, and loss of trust among patients.