With the United Nations (UN) push for sustainable development goals (SDGs), research on renewable energy resources has received significant renewed interest. Furthermore, major economies worldwide have committed to reducing carbon emissions significantly and eventually achieving the goal of carbon-neutral economies to tackle climate change. To meet the growing need for energy consumption, among several renewable options, the development of solar energy (SE) systems is an attractive solution. However, SE systems have several challenges, such as high installation and maintenance costs, conversion efficiency, and storage issues. With recent advances in material science focusing on discovering new material, storage and conversion aided by artificial intelligence (AI) have the potential to improve the efficiency of solar power systems significantly. AI approaches will greatly help model, analyze, and predict renewable energy performance and determine optimal operating conditions. This chapter provides an overview of recent advances in applying AI techniques to solar harvesting, storage, and conversion, along with challenges and potential future research directions.