Artificial Intelligence in the Quantum Era: Transforming Cybersecurity Paradigms

Abstract

The advancements in artificial intelligence (AI), quantum computing, cloud systems, and the Internet of Things (IoT) have fundamentally reshaped the landscape of cybersecurity requirements. This evolution has rendered many traditional cryptographic systems increasingly vulnerable, particularly given the emergence of quantum algorithms capable of compromising established classical encryption methods such as RSA and ECC. Within this context, the present study critically investigates the potential of AI to augment post-quantum cybersecurity solutions. Its primary objective is to facilitate the development of intelligent, adaptive, and resilient security frameworks. Specifically, this research evaluates the security implications posed by quantum computing, examines the efficacy of post-quantum cryptographic approaches, and analyzes the contributions of AI-based intrusion detection systems, predictive threat intelligence, and automated response mechanisms to fortify contemporary security postures. The performance of conventional cybersecurity systems is compared to quantum-resilient systems with an AI component using a comparative analytical methodology. Mathematical modelling is also used for anomaly detection probability and quantum attack complexity and AI classification accuracy. The results show that AI-powered post-quantum security solutions offer greater cyber resilience, quicker threat identification, and scalability in IoT and cloud setups. The paper concludes that AI's convergence with quantum-resistant technologies will be a key component to the security of next generation digital infrastructures.