This paper proposes a hybrid cooling system that utilizes the concepts of artificial intelligence (AI) to use solar energy and waste heat recovery (WHR) to improve the sustainability and efficiency of data centers. The data centers are estimated to use 1–2% of global electricity and cooling systems use about 40% of the total power. Traditional cooling systems like the computer room air conditioning (CRAC) units, chilled water systems are power-consuming and non-environmental. The main focus of earlier studies seems to be solar cooling or waste heat recovery in isolation and does not attempt to incorporate AI in significant combinations to optimize in real-time. The hybrid system manages to reduce these shortcomings by integrating photovoltaic (PV) panels, solar thermal collectors, absorption chillers, and an AI-controlled module. This new solution is the first hybrid cooling system that combines solar PV, solar thermal energy, and WHR with AI optimization and allows the real-time optimization of the energy consumption under changing workload and weather conditions. The system design is based on computational modeling, computational fluid dynamics (CFD), experimental validation and a 10 k W testbed. The outcome shows that 92.28% of cooling needs are supplied by renewable sources, which puts grid reliance at 7.72%. Its system will be energy efficient of 70–85% given varying operational and climatic conditions with cost savings amounting to 40–60% and carbon emission cut of 50–70%.