diff --git a/python/pyarrow/array.pxi b/python/pyarrow/array.pxi
index dca99af81204..6e9dc46a9a3d 100644
--- a/python/pyarrow/array.pxi
+++ b/python/pyarrow/array.pxi
@@ -290,27 +290,34 @@ def array(object obj, type=None, mask=None, size=None, from_pandas=None,
 
             indices = _codes_to_indices(
                 values.codes, mask, index_type, memory_pool)
-            try:
-                dictionary = array(
-                    values.categories.values, type=value_type,
-                    memory_pool=memory_pool)
-            except TypeError:
-                # TODO when removing the deprecation warning, this whole
-                # try/except can be removed (to bubble the TypeError of
-                # the first array(..) call)
-                if value_type is not None:
-                    warnings.warn(
-                        "The dtype of the 'categories' of the passed "
-                        "categorical values ({0}) does not match the "
-                        "specified type ({1}). For now ignoring the specified "
-                        "type, but in the future this mismatch will raise a "
-                        "TypeError".format(
-                            values.categories.dtype, value_type),
-                        FutureWarning, stacklevel=2)
+
+            if hasattr(values.categories.values, '__arrow_array__'):
+                dictionary = _handle_arrow_array_protocol(
+                    values.categories.values, type, mask, size)
+                if isinstance(dictionary, ChunkedArray):
+                    dictionary = dictionary.combine_chunks()
+            else:
+                try:
                     dictionary = array(
-                        values.categories.values, memory_pool=memory_pool)
-                else:
-                    raise
+                        values.categories.values, type=value_type,
+                        memory_pool=memory_pool)
+                except TypeError:
+                    # TODO when removing the deprecation warning, this whole
+                    # try/except can be removed (to bubble the TypeError of
+                    # the first array(..) call)
+                    if value_type is not None:
+                        warnings.warn(
+                            "The dtype of the 'categories' of the passed "
+                            "categorical values ({0}) does not match the "
+                            "specified type ({1}). For now ignoring the specified "
+                            "type, but in the future this mismatch will raise a "
+                            "TypeError".format(
+                                values.categories.dtype, value_type),
+                            FutureWarning, stacklevel=2)
+                        dictionary = array(
+                            values.categories.values, memory_pool=memory_pool)
+                    else:
+                        raise
 
             return DictionaryArray.from_arrays(
                 indices, dictionary, ordered=values.ordered, safe=safe)
diff --git a/python/pyarrow/tests/test_pandas.py b/python/pyarrow/tests/test_pandas.py
index 4d0ddf875474..e3d3d044f242 100644
--- a/python/pyarrow/tests/test_pandas.py
+++ b/python/pyarrow/tests/test_pandas.py
@@ -1728,6 +1728,25 @@ def test_table_str_to_categorical_with_na(self):
             table.to_pandas(strings_to_categorical=True,
                             zero_copy_only=True)
 
+    def test_categorical_with_arrow_backed_ea_to_array(self):
+        if Version(pd.__version__) < Version("1.5.0"):
+            pytest.skip("ArrowDtype missing")
+
+        ser = pd.Series([1, 2, 1], dtype=pd.ArrowDtype(pa.int64())).astype("category")
+        result = pa.array(ser)
+        expected = pa.DictionaryArray.from_arrays(
+            pa.array([0, 1, 0], type=pa.int8()), pa.array([1, 2]))
+        assert result.equals(expected)
+
+        ser = pd.Series(
+            ["a", "b", "a"],
+            dtype=pd.ArrowDtype(pa.string()),
+        ).astype("category")
+        result = pa.array(ser)
+        expected = pa.DictionaryArray.from_arrays(
+            pa.array([0, 1, 0], type=pa.int8()), pa.array(["a", "b"]))
+        assert result.equals(expected)
+
     # Regression test for ARROW-2101
     def test_array_of_bytes_to_strings(self):
         converted = pa.array(np.array([b'x'], dtype=object), pa.string())