diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 6f361ff867c35..b72a21f1aa0c6 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -402,6 +402,8 @@ def _ea_wrap_cython_operation(
 
             if self.how in self.cast_blocklist:
                 return res_values
+            elif self.how in ["first", "last", "min", "max"]:
+                res_values[result_mask == 1] = -1
             return values._from_backing_data(res_values)
 
         npvalues = self._ea_to_cython_values(values)
diff --git a/pandas/tests/groupby/test_min_max.py b/pandas/tests/groupby/test_min_max.py
index 8602f8bdb1aa1..37eb52be0b37b 100644
--- a/pandas/tests/groupby/test_min_max.py
+++ b/pandas/tests/groupby/test_min_max.py
@@ -247,3 +247,26 @@ def test_min_max_nullable_uint64_empty_group():
     res = gb.max()
     expected.iloc[0, 0] = 9
     tm.assert_frame_equal(res, expected)
+
+
+@pytest.mark.parametrize("func", ["first", "last", "min", "max"])
+def test_groupby_min_max_categorical(func):
+    # GH: 52151
+    df = DataFrame(
+        {
+            "col1": pd.Categorical(["A"], categories=list("AB"), ordered=True),
+            "col2": pd.Categorical([1], categories=[1, 2], ordered=True),
+            "value": 0.1,
+        }
+    )
+    result = getattr(df.groupby("col1", observed=False), func)()
+
+    idx = pd.CategoricalIndex(data=["A", "B"], name="col1", ordered=True)
+    expected = DataFrame(
+        {
+            "col2": pd.Categorical([1, None], categories=[1, 2], ordered=True),
+            "value": [0.1, None],
+        },
+        index=idx,
+    )
+    tm.assert_frame_equal(result, expected)