The industry is currently witnessing two major trends: the shift to a low-carbon economy and the integration of AI/ML technologies to revolutionize design and operational processes. The transition to a low-carbon economy requires substantial storage of CO2, natural gas, and hydrogen. AI/ML technologies are being applied to understand various mechanisms related to storage, thereby enhancing efficiency through solving complex optimization problems. While still in its early stages, hydrogen is expected to play a crucial role in the transition due to its abundant storage capacity and widespread distribution. Subsurface hydrogen storage, especially in porous media, is vital for addressing imbalances in supply and demand. AI/ML optimization of storage-development plans is becoming a catalyst for scaling up subsurface hydrogen storage. Carbon storage, a more mature sector, is utilizing AI/ML to improve performance and reduce costs through advanced geological modeling and numerical simulation. The industry is also focusing on repurposing storage sites, such as converting natural gas storage to hydrogen, to enhance overall economics. The merging of storage sites with different storage media is becoming a trend. Overall, storage operations of carbon, hydrogen, and natural gas are expected to be crucial in the global energy transition, with AI/ML technologies accelerating the process.