No, not at all. There is a transformer obsession that is quite possibly not supported by the actual facts (CNNs can still do just as well: https://arxiv.org/abs/2310.16764), and CNNs definitely remain preferable for smaller and more specialized tasks (e.g. computer vision on medical data).
If you also get into more robust and/or specialized tasks (e.g. rotation invariant computer vision models, graph neural networks, models working on point-cloud data, etc) then transformers are also not obviously the right choice at all (or even usable in the first place). So plenty of other useful architectures out there.
If you also get into more robust and/or specialized tasks (e.g. rotation invariant computer vision models, graph neural networks, models working on point-cloud data, etc) then transformers are also not obviously the right choice at all (or even usable in the first place). So plenty of other useful architectures out there.