Energy improvements in the energy sector constitute a key strategy to mitigate climate change. These expected improvements increasingly depend on the development of materials with improved surface characteristics. To prospectively assess the large-scale benefits and trade-offs of such novel surface engineering (SE) technology deployments in the energy sector, an integrated modelling framework is proposed. This paper links an integrated assessment model (IAM) forecasting socio-economic changes in energy supply with life cycle assessment (LCA) models of targeted technology candidates. Different shared socio-economic pathway narratives are used with the MESSAGE IAM to forecast future energy supply scenarios. A dynamic vintage model is employed to model plants decommissioning and adoption rates of innovative SE. Potential benefits and impacts of SE are assessed through prospective LCA. The approach is used to estimate the prospective GHG emission reduction potential achieved by large-scale adoption of innovative SE technologies to improve the efficiency of four energy conversion technologies (coal power plants, gas turbines, wind turbines and solar panels) until 2100. Applying innovative SE technologies to the energy sector has the potential of reducing annual CO2-eq emissions by 1.8 Gt in 2050 and 3.4 Gt in 2100 in an optimistic socio-economic pathway scenario. This corresponds to 7% and 8.5% annual reduction in the energy sector in 2050 and 2100, respectively. The mitigation potential of applying innovative SE technologies highly depends on the energy technology, the socio-economic pathways, and the implementation of stringent GHG mitigation policies. Due to their high carbon intensity, fossil-based technologies showed a higher GHG mitigation potential compared to renewables. Besides, GHG emissions related to the SE processes are largely offset by the GHG savings of the energy conversion technologies where the innovative SE technologies are applied.