diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index da80969b613cd..703c270132a02 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -379,6 +379,12 @@ def _call_cython_op(
         if values.dtype == "float16":
             values = values.astype(np.float32)
 
+        values = values.T
+        if mask is not None:
+            mask = mask.T
+            if result_mask is not None:
+                result_mask = result_mask.T
+
         if self.how in ["any", "all"]:
             if mask is None:
                 mask = isna(values)
@@ -392,12 +398,6 @@ def _call_cython_op(
             values = values.astype(bool, copy=False).view(np.int8)
             is_numeric = True
 
-        values = values.T
-        if mask is not None:
-            mask = mask.T
-            if result_mask is not None:
-                result_mask = result_mask.T
-
         out_shape = self._get_output_shape(ngroups, values)
         func = self._get_cython_function(self.kind, self.how, values.dtype, is_numeric)
         values = self._get_cython_vals(values)
diff --git a/pandas/tests/groupby/test_grouping.py b/pandas/tests/groupby/test_grouping.py
index fc2a8a970010a..b1d84f8ac4657 100644
--- a/pandas/tests/groupby/test_grouping.py
+++ b/pandas/tests/groupby/test_grouping.py
@@ -1180,3 +1180,15 @@ def test_grouping_by_key_is_in_axis():
     result = gb.sum()
     expected = DataFrame({"a": [1, 2], "b": [1, 2], "c": [7, 5]})
     tm.assert_frame_equal(result, expected)
+
+def test_groupby_any_timedelta_with_all_nulls():
+    # Create a DataFrame with timedelta values, including NaT (null timedelta)
+    df = pd.DataFrame({
+        'timedelta': [pd.Timedelta(days=1), pd.NaT],
+        'group': [0, 1]
+    })
+    result = df.groupby('group')['timedelta'].any()
+
+    # Expected behavior: group 1 should return False because it has all null values
+    expected = pd.Series([True, False], index=[0, 1])
+    pd.testing.assert_series_equal(result, expected)