Strengthening Personal Data Protection Law to Address Artificial Intelligence and Cybersecurity Challenges

The rapid advancement of Artificial Intelligence (AI) and the increasing sophistication of cybersecurity threats present unprecedented challenges to individual privacy rights and personal data sovereignty. Employing a qualitative legal research design grounded in a doctrinal approach and library research. The specific findings reveal four critical vulnerabilities: (1) structural incompatibility between core privacy principles (consent, purpose specification, data erasure) and deep learning re-training models; (2) AI-specific attack vectors like prompt injection and model inversion that exfiltrate raw personal data directly from parameter weights without triggering traditional perimeter security breach alerts; (3) operational deficits in static Data Protection Impact Assessments (DPIAs) that fail to monitor post-deployment algorithmic drift; and (4) acute forensic auditing capacity deficits among regulatory authorities alongside the breakdown of cross-border data transfer tools in cloud-hosted AI environments.