Graph Attention Networks (GATs) enhance the representation of graph-structured data by dynamically assigning different levels of importance to nodes in a graph through attention mechanisms. This approach allows for more flexible and context-aware aggregation of node features, leading to improved performance in tasks like node classification and link prediction.