Benchmarking involves evaluating a system's performance by measuring it against established benchmarks or metrics. In the context of AI, this could involve testing a model's accuracy, speed, or efficiency compared to others. It helps identify best practices and areas for improvement. For example, machine learning models are commonly benchmarked using datasets like ImageNet to ensure they perform well on specific tasks, such as image recognition.