Artificial intelligence (AI) has become a pivotal technology that heralds modern progress in all fields and is capable of addressing complex issues that depend on big data in a timely and rapid manner. As for renewable energy systems in general and photovoltaic energy in particular, AI has proven to be indispensable, facilitating optimal energy management by monitoring equipment in real time and predicting future maintenance while increasing production and reducing expenses. Deep neural networks, evolutionary algorithms, and hybrid neuro-fuzzy models constitute advanced techniques that leverage AI to improve energy forecasting, optimize resource allocation, and automate control of systems more intelligently. Through a comprehensive review of recent academic contributions, as well as detailed methodological frameworks and experimental results, this work identifies strategic implications, unresolved challenges, and future research directions.