Abstract <p>Energy transition toward more renewable energy use is essential for lowering carbon emissions, securing long-term energy supplies, and meeting sustainability objectives. The role of knowledge and its application is vital in the energy transition process, but its effects remain unclear both in theory and in practice. This research examines the impacts of artificial intelligence and economic complexity on the energy transition and the moderating effects of geopolitical uncertainty on such relationships for 21 OECD countries over the period from 2002 to 2019. The study applies advanced panel quantile estimation techniques, including Methods of Moments Quantile Regression. It reveals that AI-related automation—proxied by industrial robot density—shows a positive but modest and stage-dependent association with the energy transition, suggesting a supportive role primarily in the earlier phases of the transition. On the other hand, advancement in productive knowledge, measured by the economic complexity index, hinders progress toward sustainability and efficiency. This challenge is most evident in nations at early and middle stages of their energy transition. However, in countries with a more established sustainable energy mix, this effect is negligible. Notably, during periods of geopolitical instability, artificial intelligence’s positive impacts are diminished, while the negative consequences of productive knowledge intensify. These findings offer valuable insights for developing a policy framework that integrates knowledge utilization, geopolitical dynamics, and sustainable development objectives. Governments should rebuild policies that effectively divert productive knowledge toward the inventions and applications of green technologies in practice, as well as enact policies that restrain the negative moderating impacts of geopolitical risk on the effects of artificial intelligence and economic complexity on the energy transition.</p> Graphical abstract <p></p>