diff --git a/pytorch_lightning/utilities/cli.py b/pytorch_lightning/utilities/cli.py
index d97ef9ccddebb..7b064aa4fbbca 100644
--- a/pytorch_lightning/utilities/cli.py
+++ b/pytorch_lightning/utilities/cli.py
@@ -662,12 +662,6 @@ def get_automatic(
                 "#optimizers-and-learning-rate-schedulers"
             )
 
-        if is_overridden("configure_optimizers", self.model):
-            warnings._warn(
-                f"`{self.model.__class__.__name__}.configure_optimizers` will be overridden by "
-                f"`{self.__class__.__name__}.add_configure_optimizers_method_to_model`."
-            )
-
         optimizer_class = parser._optimizers[optimizers[0]][0]
         optimizer_init = self._get(self.config_init, optimizers[0])
         if not isinstance(optimizer_class, tuple):
@@ -675,6 +669,7 @@ def get_automatic(
         if not optimizer_init:
             # optimizers were registered automatically but not passed by the user
             return
+
         lr_scheduler_init = None
         if lr_schedulers:
             lr_scheduler_class = parser._lr_schedulers[lr_schedulers[0]][0]
@@ -691,6 +686,11 @@ def configure_optimizers(
             lr_scheduler = instantiate_class(optimizer, lr_scheduler_init)
             return [optimizer], [lr_scheduler]
 
+        if is_overridden("configure_optimizers", self.model):
+            warnings._warn(
+                f"`{self.model.__class__.__name__}.configure_optimizers` will be overridden by "
+                f"`{self.__class__.__name__}.add_configure_optimizers_method_to_model`."
+            )
         self.model.configure_optimizers = MethodType(configure_optimizers, self.model)
 
     def _get(self, config: Dict[str, Any], key: str, default: Optional[Any] = None) -> Any:
diff --git a/tests/utilities/test_cli.py b/tests/utilities/test_cli.py
index bff5d7e9111e4..8c5d441c0925c 100644
--- a/tests/utilities/test_cli.py
+++ b/tests/utilities/test_cli.py
@@ -46,6 +46,7 @@
 from pytorch_lightning.utilities.imports import _TORCHVISION_AVAILABLE
 from tests.helpers import BoringDataModule, BoringModel
 from tests.helpers.runif import RunIf
+from tests.helpers.utils import no_warning_call
 
 torchvision_version = version.parse("0")
 if _TORCHVISION_AVAILABLE:
@@ -1265,3 +1266,11 @@ class TestCallback(Callback):
     )
     # the existing config is not updated
     assert cli.config_init["trainer"]["max_epochs"] is None
+
+
+def test_cli_configure_optimizers_warning(tmpdir):
+    match = "configure_optimizers` will be overridden by `LightningCLI"
+    with mock.patch("sys.argv", ["any.py"]), no_warning_call(UserWarning, match=match):
+        LightningCLI(BoringModel, run=False)
+    with mock.patch("sys.argv", ["any.py", "--optimizer=Adam"]), pytest.warns(UserWarning, match=match):
+        LightningCLI(BoringModel, run=False)