diff --git a/doc/source/whatsnew/v1.5.0.rst b/doc/source/whatsnew/v1.5.0.rst
index 0c3ad0f7d8d21..706821afeb237 100644
--- a/doc/source/whatsnew/v1.5.0.rst
+++ b/doc/source/whatsnew/v1.5.0.rst
@@ -216,6 +216,7 @@ Indexing
 - Bug in :meth:`DataFrame.iloc` where indexing a single row on a :class:`DataFrame` with a single ExtensionDtype column gave a copy instead of a view on the underlying data (:issue:`45241`)
 - Bug in :meth:`Series.__setitem__` with a non-integer :class:`Index` when using an integer key to set a value that cannot be set inplace where a ``ValueError`` was raised insead of casting to a common dtype (:issue:`45070`)
 - Bug when setting a value too large for a :class:`Series` dtype failing to coerce to a common type (:issue:`26049`, :issue:`32878`)
+- Bug in :meth:`Series.__setitem__` when setting ``boolean`` dtype values containing ``NA`` incorrectly raising instead of casting to ``boolean`` dtype (:issue:`45462`)
 - Bug in :meth:`Series.__setitem__` where setting :attr:`NA` into a numeric-dtpye :class:`Series` would incorrectly upcast to object-dtype rather than treating the value as ``np.nan`` (:issue:`44199`)
 -
 
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index ac017146b153a..92f3cfdc589ff 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -1997,9 +1997,7 @@ def np_can_hold_element(dtype: np.dtype, element: Any) -> Any:
             elif not isinstance(tipo, np.dtype):
                 # i.e. nullable IntegerDtype; we can put this into an ndarray
                 #  losslessly iff it has no NAs
-                hasnas = element._mask.any()
-                # TODO: don't rely on implementation detail
-                if hasnas:
+                if element._hasna:
                     raise ValueError
                 return element
 
@@ -2016,9 +2014,7 @@ def np_can_hold_element(dtype: np.dtype, element: Any) -> Any:
             elif not isinstance(tipo, np.dtype):
                 # i.e. nullable IntegerDtype or FloatingDtype;
                 #  we can put this into an ndarray losslessly iff it has no NAs
-                hasnas = element._mask.any()
-                # TODO: don't rely on implementation detail
-                if hasnas:
+                if element._hasna:
                     raise ValueError
                 return element
             return element
@@ -2047,7 +2043,12 @@ def np_can_hold_element(dtype: np.dtype, element: Any) -> Any:
 
     elif dtype.kind == "b":
         if tipo is not None:
-            if tipo.kind == "b":  # FIXME: wrong with BooleanArray?
+            if tipo.kind == "b":
+                if not isinstance(tipo, np.dtype):
+                    # i.e. we have a BooleanArray
+                    if element._hasna:
+                        # i.e. there are pd.NA elements
+                        raise ValueError
                 return element
             raise ValueError
         if lib.is_bool(element):
diff --git a/pandas/tests/series/indexing/test_setitem.py b/pandas/tests/series/indexing/test_setitem.py
index e7261d75dfd30..8501c7146f371 100644
--- a/pandas/tests/series/indexing/test_setitem.py
+++ b/pandas/tests/series/indexing/test_setitem.py
@@ -21,6 +21,7 @@
     Series,
     Timedelta,
     Timestamp,
+    array,
     concat,
     date_range,
     period_range,
@@ -573,6 +574,19 @@ def test_setitem_non_bool_into_bool(self, val, indexer_sli, unique):
             expected = Series([val, val], dtype=object, index=[1, 1])
         tm.assert_series_equal(ser, expected)
 
+    def test_setitem_boolean_array_into_npbool(self):
+        # GH#45462
+        ser = Series([True, False, True])
+        values = ser._values
+        arr = array([True, False, None])
+
+        ser[:2] = arr[:2]  # no NAs -> can set inplace
+        assert ser._values is values
+
+        ser[1:] = arr[1:]  # has an NA -> cast to boolean dtype
+        expected = Series(arr)
+        tm.assert_series_equal(ser, expected)
+
 
 class SetitemCastingEquivalents:
     """