diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index b551e7ded0178..9cb5a3e17f527 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -157,3 +157,5 @@ jobs:
       run: |
         source activate pandas-dev
         pytest pandas/tests/frame/methods --array-manager
+        pytest pandas/tests/frame/indexing/test_indexing.py::TestDataFrameIndexing::test_setitem_boolean --array-manager
+        pytest pandas/tests/frame/indexing/test_where.py --array-manager
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 3621539a3f0c3..50579d8ca0787 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -621,6 +621,10 @@ def _as_manager(self, typ: str) -> DataFrame:
         # fastpath of passing a manager doesn't check the option/manager class
         return DataFrame(new_mgr)
 
+    @property
+    def _has_array_manager(self):
+        return isinstance(self._mgr, ArrayManager)
+
     # ----------------------------------------------------------------------
 
     @property
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index e1271cfec2bde..1a163035d8f01 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -8801,6 +8801,13 @@ def _where(
         if axis is not None:
             axis = self._get_axis_number(axis)
 
+        cond_orig = cond
+
+        # Needed for DataFrames with ArrayManager, see below for details
+        all_bool_columns = False
+        if isinstance(cond, ABCDataFrame) and cond._has_array_manager:
+            all_bool_columns = all(is_bool_dtype(dt) for dt in cond.dtypes)
+
         # align the cond to same shape as myself
         cond = com.apply_if_callable(cond, self)
         if isinstance(cond, NDFrame):
@@ -8812,9 +8819,32 @@ def _where(
                 raise ValueError("Array conditional must be same shape as self")
             cond = self._constructor(cond, **self._construct_axes_dict())
 
+        # Needed for DataFrames with ArrayManager, see below for details
+        if (
+            isinstance(cond, ABCDataFrame)
+            and cond._has_array_manager
+            and isinstance(cond_orig, ABCSeries)
+        ):
+            all_bool_columns = is_bool_dtype(cond_orig.dtype)
+
         # make sure we are boolean
         fill_value = bool(inplace)
-        cond = cond.fillna(fill_value)
+        try:
+            cond = cond.fillna(fill_value)
+        except TypeError:
+            # With ArrayManager, fillna can raise an error if `cond` is not
+            # of boolean dtype
+            raise ValueError("Boolean array expected for the condition")
+
+        # With ArrayManager, `fillna` does not automatically change object dtype
+        # back to bools (if the alignment made it object by introducing NaNs).
+        # So in this case we cast back to bool manually *if* the original columns
+        # before aligning were bool
+        # TODO this workaround can be removed once we have nullable boolean dtype
+        # as default
+        if isinstance(cond, ABCDataFrame) and cond._has_array_manager:
+            if not all(is_bool_dtype(dt) for dt in cond.dtypes) and all_bool_columns:
+                cond = cond.astype(bool)
 
         msg = "Boolean array expected for the condition, not {dtype}"
 
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index 0f677ff3180be..40ce563f86162 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -454,7 +454,7 @@ def is_mixed_type(self) -> bool:
 
     @property
     def is_numeric_mixed_type(self) -> bool:
-        return False
+        return all(is_numeric_dtype(t) for t in self.get_dtypes())
 
     @property
     def any_extension_types(self) -> bool:
diff --git a/pandas/tests/frame/indexing/test_where.py b/pandas/tests/frame/indexing/test_where.py
index 2f098426efaf9..e4b161f9240ff 100644
--- a/pandas/tests/frame/indexing/test_where.py
+++ b/pandas/tests/frame/indexing/test_where.py
@@ -159,7 +159,7 @@ def test_where_set(self, where_frame, float_string_frame):
 
         def _check_set(df, cond, check_dtypes=True):
             dfi = df.copy()
-            econd = cond.reindex_like(df).fillna(True)
+            econd = cond.reindex_like(df).fillna(True).astype(bool)
             expected = dfi.mask(~econd)
 
             return_value = dfi.where(cond, np.nan, inplace=True)
@@ -499,6 +499,7 @@ def test_where_axis(self):
         assert return_value is None
         tm.assert_frame_equal(result, expected)
 
+    def test_where_axis_multiple_dtypes(self):
         # Multiple dtypes (=> multiple Blocks)
         df = pd.concat(
             [
diff --git a/pandas/tests/frame/methods/test_fillna.py b/pandas/tests/frame/methods/test_fillna.py
index 58016be82c405..035f31a29c599 100644
--- a/pandas/tests/frame/methods/test_fillna.py
+++ b/pandas/tests/frame/methods/test_fillna.py
@@ -544,3 +544,14 @@ def test_fillna_nonconsolidated_frame():
     df_nonconsol = df.pivot("i1", "i2")
     result = df_nonconsol.fillna(0)
     assert result.isna().sum().sum() == 0
+
+
+def test_fillna_infer_bool_dtype(using_array_manager):
+    # With ArrayManager, fillna doesn't change/infer dtypes
+    df = DataFrame([[True, False], [np.nan, True], [False, None]], dtype=object)
+    result = df.fillna(True)
+    if using_array_manager:
+        expected = DataFrame([[True, False], [True, True], [False, True]], dtype=object)
+    else:
+        expected = DataFrame([[True, False], [True, True], [False, True]], dtype=bool)
+    tm.assert_frame_equal(result, expected)