Emerging technologies like AI, blockchain, and quantum computing drive innovation but introduce systemic risks that outpace traditional governance frameworks. While standards such as ISO/IEC 27001, NIST Cybersecurity Framework (CSF), and FAIR provide foundational controls, they lack mechanisms for real-time, adaptive risk assessment in dynamic environments. This paper bridges this gap by proposing an AI-driven risk management platform that synthesizes governance, risk, and compliance (GRC) principles with a 22-dimension weighted scoring rubric. Deployed as a Dockerized container, the model evaluates organizational risk across technical, strategic, and operational domains-from cloud security posture to talent readiness-and generates large language model (LLM)-tailored mitigation strategies. A case study of a cybersecurity startup demonstrates the platform’s efficacy, yielding a normalized risk score of 70.71/100 and actionable recommendations aligned with NIST CSF and ISO 27001 controls. By automating risk quantification, benchmarking against industry standards, and prioritizing ethical integration, this approach enables organizations to adopt emerging technologies responsibly without stifling innovation. The results highlight how AI-augmented governance can sharmonize security, compliance, and agility in an era of exponential technological change, synthesizing with current established frameworks to build upon and improve risk mnagement to align with emerging technologies.