In recent years, Large Language Model(LLM)-based AI (GenAI) assistants have begun to transform the computer programming process. Researchers in computing education are studying these tools by assessing their capabilities, analyzing associated risks and opportunities, and developing guidelines for their effective use. One concern that has received little attention thus far is the potentially disparate impacts of GenAI tools on computing students with unequal resources and opportunities in different regions across the globe. Is GenAI technology creating a digital divide among computing students from different regions? This research presents a comparative study between undergraduate computing students from the United States and Bangladesh with respect to their access to GenAI assistants, usage behavior, and concerns about these tools. We collected study data through a questionnaire distributed to undergraduate computing education students from multiple universities in both countries (n = 534). The study results reveal significant differences (p < .05) between the access, use, and attitudes of students from the two countries, suggesting the need to develop strategies for bridging the gap between the regions. This research aims to inform computing education researchers about GenAI disparities among computing students from different regions and to promote research to address this challenge.