<p>The valorization of carbon dioxide (CO₂) into fuels and chemicals represents both a scientific challenge and an opportunity for sustainable energy transition. This review bridges heterogeneous and homogeneous approaches, highlighting how molecular precision and materials robustness can converge to address the intrinsic stability of CO₂ and the complexity of its multi-electron transformations. Advances in single-atom catalysts, MXenes, and carbon nitrides demonstrate how structural control at the atomic scale can enhance activity and selectivity, while homogeneous complexes continue to provide mechanistic insights and tunable active sites. In parallel, machine learning (ML) is emerging as a transformative tool to accelerate catalyst discovery, identify descriptors, and guide rational design; however, its effectiveness depends critically on realistic datasets and experimental validation. We argue that future progress will rely on integrative strategies: combining computation, experiment, and automation within materials acceleration platforms. By adopting this integrative vision, CO₂ can evolve from an environmental burden to a versatile feedstock for next-generation sustainable fuels and chemicals.</p>