Despite significant advances in medical interventions, fatal traumatic hemorrhage remains a leading cause of death worldwide. This persistent challenge has driven extensive research and development efforts aimed at creating more effective hemostatic agents to control bleeding. While most existing hemostatic agents are organic in nature, recent studies have highlighted the promising potential of mineral and synthetic inorganic materials for hemorrhage control. These materials demonstrate remarkable properties, such as rapid water adsorption from blood via their porous structures, which leads to the local concentration of proteins and cellular elements crucial for clot formation. Additionally, their negatively charged surfaces create a favorable environment for the activation of the intrinsic coagulation cascade. Although a variety of minerals and synthetic inorganic materials are currently employed as topical hemostatic agents, a vast array of emerging classes of inorganic materials remains underexplored. Many of these materials possess untapped hemostatic potential, but their properties and mechanisms for controlling bleeding are poorly understood. Moreover, synthesizing these materials with the precise characteristics required for effective hemostasis presents significant challenges. Recent advances in artificial intelligence (AI) offer a promising avenue to address these hurdles. By leveraging the growing availability of large datasets and sophisticated algorithms, AI can identify complex relationships within multidimensional systems, such as the synthesis of advanced inorganic materials. This capability is particularly critical for materials lacking well-characterized mechanisms or those with implications for hemostasis disorders, such as severe bleeding or thrombosis. AI-driven approaches could enable the design of innovative topical hemostatic agents capable of rapidly diagnosing and efficiently intervening in life-threatening situations, revolutionizing the field of hemorrhage control.