Carbon dioxide (CO₂) and methane (CH₄) are the main anthropogenic greenhouse gases. The European Copernicus CO₂ monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.