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This perspective article focuses on the exploration and advocacy of approaches to be considered in designing equitable learning experiences for students’ use of artificial intelligence, machine learning, and technology through the Universal Design for Learning Framework (UDL) exemplifying chemistry examples that can be applied to any course in STEM. The use of artificial intelligence (AI) and machine learning are causing disruptions within learning in higher education and is also casting a spotlight on systemic inequities particularly affecting minoritized groups broadly and in STEM fields. Particularly, the emergence of AI has focused on inequities toward minoritized students in academic and professional ethics. As the U.S. education system grapples with a nuanced mix of acceptance and hesitation towards AI, the necessity for inclusive and equitable education, impactful learning practices, and innovative strategies has become more pronounced. Promoting equitable approaches for the use of artificial intelligence and technology in STEM learning will be an important milestone in addressing STEM disparities toward minoritized groups and equitable accessibility to evolving technology.