I think it's a reasonable claim that all graph convolutional networks (GCN) are graph neural networks (GNN), since they operate on graphs, and are NNs. However, there are graph neural networks that don't use graph convolutions.
For example, GRN is a generative neural network for graphs where an RNN is given all the previous nodes and edges, and decides whether or not to add a new node/edges to the existing graph, or to terminate the generation process.
Shicheng-Guo
commented
1 year ago 
I think it's a reasonable claim that all graph convolutional networks (GCN) are graph neural networks (GNN), since they operate on graphs, and are NNs. However, there are graph neural networks that don't use graph convolutions. For example, GRN is a generative neural network for graphs where an RNN is given all the previous nodes and edges, and decides whether or not to add a new node/edges to the existing graph, or to terminate the generation process.
https://theaisummer.com/gnn-architectures/