Example Concept: AI-driven assessments can streamline grading by automating repetitive tasks, such as multiple-choice scoring or pattern recognition in student responses. However, challenges include ensuring that AI algorithms align with subjective grading criteria, maintaining transparency in AI decision-making processes, and addressing potential biases in AI models. Effective integration requires educators to validate AI outputs and provide oversight to ensure fair and accurate assessments.