Example Concept: AI-driven assessments can face challenges in diverse educational settings due to potential biases in algorithms, which may not account for cultural and linguistic differences among students. Additionally, disparities in access to technology can hinder the equitable implementation of AI tools, requiring schools to address infrastructure gaps and provide adequate training for educators to effectively use these systems.