This paper investigates the macroeconomic determinants of renewable energy consumption in Saudi Arabia during 1990–2025 using a hybrid approach of ARDL bounds testing and Random Forest machine learning with SHAP (SHapley Additive ExPlanations) to improve model interpretability. We employ annual data from the World Development Indicators to examine the effect of high-technology exports, trade openness, foreign direct investment, inflation and GDP on renewable energy consumption. Our results indicate that renewable energy consumption is highly path dependent, with previous adoption playing a significant role in current consumption (β = 0.776, p < 0.01). Trade openness also shows a negative contemporaneous effect ( = 0.0013, p 0.05) in line with the carbon lock-in hypothesis that typifies hydrocarbon-dependent economies. High-technology exports as a proxy for technological innovation do not appear to be a significant driver, indicating that the innovation-led energy transition in Saudi Arabia is still maturing. The Random Forest model confirms the importance of persistence effects explaining about 73 % of the variance. The analysis of the different time periods indicates that, after 2016 (also known as Vision 2030), there has been a significant change in the structure of the analyzed data, with the statistical model of research becoming much stronger as its explanatory power has reached up to 83%. The analysis of the SHAP allows understanding of the obtained results by measuring the influence of each individual variable. The findings that were obtained pertain to Sustainable Development Goal 7 (which focuses on developing cheap and clean energy), Sustainable Development Goal 9 (which focuses on industry, innovation, and infrastructure), and Sustainable Development Goal 13 (which focuses on climate action). It is our proposal that Saudi Arabia adopt focused innovation strategies, careful management of its trade integration, and a commitment to the institutional framework in order to accelerate the transition to renewable energy. However, it is important to note that this recommendation is suggestive and not definitive.

The Gulf Cooperation Council (GCC) states have to find a way to balance their reliance on hydrocarbon resources and their ambitious aims on moving to renewable energy (for instance, the Saudi Vision 2030.) Despite the policies in place, the implementation of renewable energy technologies in the region is relatively low indicating that more needs to be understood about the reasons behind the use of renewable energy. The present research will analyze the macroeconomic determinants of renewable energy consumption in the 6 GCC states for the periods 2000-2025 using a combination of panel econometric techniques and machine learning. Panel data were constructed from data from the World Bank and the International Energy Agency. The econometric results show that R&D expenditure and trade openness are the two most important determinants of renewable energy consumption, which jointly explain about 63% of the variation (adjusted R² = 0.629). The random forest model is consistent with these findings, with R&D expenditure as the most important predictor followed by trade openness. No statistically meaningful relationship was found between GDP, foreign direct investment, inflation and renewable energy consumption in the final models due to the structural characteristics of GCC economies. The random forest model also had a low RMSE value of 0.032 and an out-of-sample R-squared of 0.425, indicating satisfactory predictive performance for an initial model. Sub-period analysis also indicates that the relationships between R&D expenditure and trade openness became stronger after 2015, which coincides with the introduction of national energy transition strategies in the GCC. The study implies that innovation in terms of technology as well as the open nature of economy could promote energy transition in the region whereby high amount of investments in research and development are required as well as deeper international trade linkages might be supporting the acceptance of green energy approach.