diff --git a/pandas/tests/frame/methods/test_astype.py b/pandas/tests/frame/methods/test_astype.py
index eb1ee4e7b2970..ea9c33c31bdcf 100644
--- a/pandas/tests/frame/methods/test_astype.py
+++ b/pandas/tests/frame/methods/test_astype.py
@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
 import pandas.util._test_decorators as td
 
 import pandas as pd
@@ -745,9 +743,11 @@ def test_astype_tz_object_conversion(self, tz):
         result = result.astype({"tz": "datetime64[ns, Europe/London]"})
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.xfail(using_string_dtype(), reason="TODO(infer_string) GH#60639")
     def test_astype_dt64_to_string(
-        self, frame_or_series, tz_naive_fixture, using_infer_string
+        self,
+        frame_or_series,
+        tz_naive_fixture,
+        string_dtype_no_object,
     ):
         # GH#41409
         tz = tz_naive_fixture
@@ -757,23 +757,17 @@ def test_astype_dt64_to_string(
         dta[0] = NaT
 
         obj = frame_or_series(dta)
-        result = obj.astype("string")
+        result = obj.astype(string_dtype_no_object)
 
         # Check that Series/DataFrame.astype matches DatetimeArray.astype
-        expected = frame_or_series(dta.astype("string"))
+        expected = frame_or_series(dta.astype(string_dtype_no_object))
         tm.assert_equal(result, expected)
 
         item = result.iloc[0]
         if frame_or_series is DataFrame:
             item = item.iloc[0]
-        if using_infer_string:
-            assert item is np.nan
-        else:
-            assert item is pd.NA
 
-        # For non-NA values, we should match what we get for non-EA str
-        alt = obj.astype(str)
-        assert np.all(alt.iloc[1:] == result.iloc[1:])
+        assert item is string_dtype_no_object.na_value
 
     def test_astype_td64_to_string(self, frame_or_series):
         # GH#41409