As interactions between humans and robots become increasingly common, robots are being entrusted with greater autonomy in decision-making, particularly in resource allocation-related tasks. Building on past work from our research group, we aimed to better understand the impact of robot form and intelligence on participants’ responses in decision-making tasks related to resource allocation. To achieve this goal, we conducted an online study in which participants played the Ultimatum Game with a random number generator, a series of humans, and three different embodied robots (i.e., table-like, single-armed, and dual-armed), each with two different purported intelligence levels (i.e., non-AI-enabled and AI-enabled). We found that participants tend to treat AI-enabled robots more like humans when receiving unfair Ultimatum Game offers from these systems. Taken together, the results of this work can help to explain human decision making around everyday robots, providing helpful insights for those who wish to design better and more successful robotic systems.