Secure management and timely accessing the patient’s sensitive data are critical challenges in the healthcare industry. This research presents a novel called Quorum-Based Encryption (QBE) architecture which uses AI-driven analytics to safeguard and manage patient records in the remote healthcare system. By providing encryption keys among many participants like patients, doctors, and admins, the given method assures a preset quorum to be met to decrypt the data, restricting unauthorized access and improving security. This method uses artificial intelligence (AI) using a TensorFlow-based classifier which analyses the real-time ECG values to check the irregularities suggestive of emergency in medical. In such critical situations. The AI model automatically interacts with the QBE system to modify the quorum requirements, allowing for immediate access to critical data while sticking to strict security protocols. This implementation demonstrates the power of combining QBE with AI in medical settings. Giving a safe, scalable and intelligent solution that combines confidentiality with emergency medical data access. This study surely improves the subject by providing feasible framework for combining advanced cryptographic methods with AI, which shall be applied to other highly regulated industries.