The rapid evolution of energy systems, coupled with the emergence of intelligent communication technologies, has necessitated a paradigm shift in the design and operation of modern Smart Grids. While traditional grids are limited in flexibility, scalability, and responsiveness, integrating Artificial Intelligence (AI) and Sixth Generation (6G) communication networks presents transformative opportunities for secure, autonomous, and sustainable grid infrastructures. However, this convergence also introduces new challenges, including system heterogeneity, latency constraints, cyber threats, and data privacy concerns, which are gaps that existing studies have only partially addressed. Motivated by these challenges, this paper presents a comprehensive survey that investigates the synergistic potential of AI and 6G in advancing the Smart Grid landscape. The main objectives include (i) a critical analysis of Smart Grid architectures and applications, (ii) an exploration of AI-driven enhancements in forecasting, optimization, and anomaly detection, (iii) an in-depth assessment of 6G capabilities tailored to grid requirements, and (iv) a synthesis of security and privacy mechanisms suitable for next-generation grids. The paper introduces a novel conceptual framework, SAFES-6G, that integrates edge intelligence, scalable AI, and explainable cybersecurity solutions to address latency, trust, and interoperability challenges. The findings highlight significant opportunities in edge-native intelligence, quantum-safe encryption, and federated learning for privacy-preserving analytics. Ultimately, this paper aims to guide researchers and practitioners toward building future-proof, resilient, and ethical energy systems that align with global sustainability and digital transformation goals.