AI coupled with computational modeling can play a major role in designing the next-generation high-efficiency combustion engines for automotive and aerospace applications. Argonne researchers are using AI to investigate the underlying causes behind stochastic combustion phenomena, such as cycle-to-cycle variability with the goal of mitigating their deleterious impact on engine performance. Researchers are also using AI along with engine simulations and high-performance computing to enable fuel-engine co-optimization in large design spaces. This approach shortens the time-to-design drastically, from months to a few days, thereby offering the potential for significant time and cost savings by the industry. Lastly, researchers are developing AI tools that can lead to the development of more accurate computational models for turbulent combustion, thereby allowing for more reliable simulation-driven engine design and analysis.