diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 60179b69f56a4..ad5f878628931 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1697,6 +1697,10 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
                 # We get here in one case via .loc with a all-False mask
                 pass
 
+            elif self._is_scalar_access(indexer):
+                # We are setting nested data
+                self._setitem_single_column(indexer[1], value, pi)
+
             elif len(ilocs) == len(value):
                 # We are setting multiple columns in a single row.
                 for loc, v in zip(ilocs, value):
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index 79c0aad66229c..c4f6aff049ea3 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -44,7 +44,6 @@
 )
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
-    ABCPandasArray,
     ABCSeries,
 )
 from pandas.core.dtypes.inference import is_inferred_bool_dtype
@@ -85,6 +84,7 @@
 from pandas.core.internals.blocks import (
     ensure_block_shape,
     external_values,
+    extract_pandas_array,
     maybe_coerce_values,
     new_block,
     to_native_types,
@@ -399,6 +399,8 @@ def convert(
     ) -> T:
         def _convert(arr):
             if is_object_dtype(arr.dtype):
+                # extract PandasArray for tests that patch PandasArray._typ
+                arr = np.asarray(arr)
                 return soft_convert_objects(
                     arr,
                     datetime=datetime,
@@ -697,6 +699,7 @@ def __init__(
 
         if verify_integrity:
             self._axes = [ensure_index(ax) for ax in axes]
+            arrays = [extract_pandas_array(x, None, 1)[0] for x in arrays]
             self.arrays = [maybe_coerce_values(arr) for arr in arrays]
             self._verify_integrity()
 
@@ -1183,8 +1186,7 @@ def __init__(
             self._axes = [ensure_index(ax) for ax in self._axes]
             arr = arrays[0]
             arr = maybe_coerce_values(arr)
-            if isinstance(arr, ABCPandasArray):
-                arr = arr.to_numpy()
+            arr = extract_pandas_array(arr, None, 1)[0]
             self.arrays = [arr]
             self._verify_integrity()
 
diff --git a/pandas/tests/extension/test_numpy.py b/pandas/tests/extension/test_numpy.py
index ed26bf6481bd9..e963cfec71b5b 100644
--- a/pandas/tests/extension/test_numpy.py
+++ b/pandas/tests/extension/test_numpy.py
@@ -16,8 +16,6 @@
 import numpy as np
 import pytest
 
-import pandas.util._test_decorators as td
-
 from pandas.core.dtypes.cast import can_hold_element
 from pandas.core.dtypes.dtypes import (
     ExtensionDtype,
@@ -30,9 +28,6 @@
 from pandas.core.internals import blocks
 from pandas.tests.extension import base
 
-# TODO(ArrayManager) PandasArray
-pytestmark = td.skip_array_manager_not_yet_implemented
-
 
 def _can_hold_element_patched(obj, element) -> bool:
     if isinstance(element, PandasArray):
@@ -349,26 +344,6 @@ def test_setitem_sequence_broadcasts(self, data, box_in_series):
         # length than the value
         super().test_setitem_sequence_broadcasts(data, box_in_series)
 
-    @skip_nested
-    def test_setitem_loc_scalar_mixed(self, data):
-        # AssertionError
-        super().test_setitem_loc_scalar_mixed(data)
-
-    @skip_nested
-    def test_setitem_loc_scalar_multiple_homogoneous(self, data):
-        # AssertionError
-        super().test_setitem_loc_scalar_multiple_homogoneous(data)
-
-    @skip_nested
-    def test_setitem_iloc_scalar_mixed(self, data):
-        # AssertionError
-        super().test_setitem_iloc_scalar_mixed(data)
-
-    @skip_nested
-    def test_setitem_iloc_scalar_multiple_homogoneous(self, data):
-        # AssertionError
-        super().test_setitem_iloc_scalar_multiple_homogoneous(data)
-
     @skip_nested
     @pytest.mark.parametrize("setter", ["loc", None])
     def test_setitem_mask_broadcast(self, data, setter):