diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index 9b9239cc042..9b15df63e1a 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -320,8 +320,16 @@ def convert_non_numpy_type(data):
         else:
             data = np.asarray(data)
 
-    if not isinstance(data, np.ndarray) and (
-        hasattr(data, "__array_function__") or hasattr(data, "__array_namespace__")
+    if (
+        not isinstance(data, np.ndarray)
+        and (
+            hasattr(data, "__array_function__") or hasattr(data, "__array_namespace__")
+        )
+        # Not exactly sure why this is a special case but
+        # https://github.com/pydata/xarray/issues/9535
+        # (possibly numpy strings can be
+        # indexed but it's indexing the string rather than as an array?)
+        and not isinstance(data, np.str_)
     ):
         return cast("T_DuckArray", data)
 
diff --git a/xarray/tests/test_variable.py b/xarray/tests/test_variable.py
index 0a55b42f228..53a61c455c7 100644
--- a/xarray/tests/test_variable.py
+++ b/xarray/tests/test_variable.py
@@ -3068,3 +3068,12 @@ def test_pandas_indexing_adapter_non_nanosecond_conversion(index, dtype) -> None
     with pytest.warns(UserWarning, match="non-nanosecond precision"):
         var = Variable(["time"], data)
     assert var.dtype == np.dtype(f"{dtype}[ns]")
+
+
+def test_numpy_strings():
+    # https://github.com/pydata/xarray/issues/9535
+    data = np.full((5,), fill_value="nothing")
+    da = DataArray(data)
+    values = np.asarray(["foo", "bar"])
+    da[1:2] = values[0]
+    assert da.sel(dim_0=1).item() == "foo"