Abstract: Steel is mainly used for structural purposes due to its rigidity, durability, flexibility, and high strength-to-weight ratio. Research and innovation in steel technology may soon take construction in entirely new directions. The use of composite structures is increasing in the construction industry due to their higher load-bearing capacity, better structural fire performance, and more significant potential to provide optimized structural solutions, effectively creating synergies between structural materials. Regarding composite structures, the new trends are innovative solutions combining different structural materials, such as steel or HSS and concrete (conventional and UHPC), among others, applicable to buildings, bridges, infrastructure, and connectors at the interface of the most efficient materials. Additionally, steel-concrete composite structures are prone to fire accidents, which is why fireproof systems are installed in residential and industrial buildings. New technologies and new fireproof materials can increase the longevity and strength of these structures, making them highly resistant to fire. Investigations into this type of structure are essential for a better understanding of their behavior, which enables the development of regulations for project development and encourages their application in civil construction. In this context, the development of refined numerical models used to analyze steel-concrete composite structural elements currently stands out. Using numerical modeling, it is possible to investigate these elements under different conditions: dynamic analyses, static analyses, buckling analyses, and fire situation analyses, among others. Furthermore, with refined numerical modeling, it becomes possible to extrapolate the expensive results of experimental tests, therefore enabling the parameterization of several variables that influence the behavior of steel-concrete composite structures. Finally, we highlight machine learning (ML), which has become the most successful branch of artificial intelligence (AI). It offers a unique opportunity to make structural engineering more predictable due to its ability to deal with complex nonlinear structural systems.