Multi Perspective Effect Analysis of Quantum Computing in the Rise of Artificial Intelligence

Abstract

The rapid evolution of artificial intelligence (AI) and quantum computing (QC) is fostering a research landscape in which these two technologies increasingly shape each other across multiple technical layers. This study provides an overview of ten representative categories, including quantumenhanced machine learning, quantum optimization for AI models, quantum encoding, hybrid quantum-classical architectures, quantum-inspired models for AI, AI-assisted quantum circuit optimization, AI-driven variational parameter tuning, AI-assisted quantum hardware calibration, and AIdriven quantum architecture search. It approaches QC-AI interactions within a conceptual model framework that organizes these relationships across dimensions of directionality, layer, and modality. This framework aims to provide an integrative analytical basis that supports future methodological and system-level research. © 2026 IEEE.