diff --git a/pandas/_testing.py b/pandas/_testing.py
index 73b1dcf31979f..964c8d4d3d61a 100644
--- a/pandas/_testing.py
+++ b/pandas/_testing.py
@@ -834,7 +834,9 @@ def _get_ilevel_values(index, level):
     # skip exact index checking when `check_categorical` is False
     if check_exact and check_categorical:
         if not left.equals(right):
-            diff = np.sum((left.values != right.values).astype(int)) * 100.0 / len(left)
+            diff = (
+                np.sum((left._values != right._values).astype(int)) * 100.0 / len(left)
+            )
             msg = f"{obj} values are different ({np.round(diff, 5)} %)"
             raise_assert_detail(obj, msg, left, right)
     else:
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 2101893d39dc9..70696a0991c90 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -27,7 +27,7 @@
 from pandas._libs.lib import is_datetime_array, no_default
 from pandas._libs.tslibs import IncompatibleFrequency, OutOfBoundsDatetime, Timestamp
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import AnyArrayLike, Dtype, DtypeObj, Label, Shape, final
+from pandas._typing import AnyArrayLike, ArrayLike, Dtype, DtypeObj, Label, Shape, final
 from pandas.compat.numpy import function as nv
 from pandas.errors import DuplicateLabelError, InvalidIndexError
 from pandas.util._decorators import Appender, cache_readonly, doc
@@ -1164,7 +1164,7 @@ def to_series(self, index=None, name=None):
         if name is None:
             name = self.name
 
-        return Series(self.values.copy(), index=index, name=name)
+        return Series(self._values.copy(), index=index, name=name)
 
     def to_frame(self, index: bool = True, name=None):
         """
@@ -4036,7 +4036,7 @@ def _wrap_joined_index(
     # Uncategorized Methods
 
     @property
-    def values(self) -> np.ndarray:
+    def values(self) -> ArrayLike:
         """
         Return an array representing the data in the Index.
 
@@ -4055,7 +4055,7 @@ def values(self) -> np.ndarray:
         Index.array : Reference to the underlying data.
         Index.to_numpy : A NumPy array representing the underlying data.
         """
-        return self._data.view(np.ndarray)
+        return self._data
 
     @cache_readonly
     @doc(IndexOpsMixin.array)
@@ -5322,7 +5322,7 @@ def _maybe_cast_slice_bound(self, label, side: str_t, kind):
         # wish to have special treatment for floats/ints, e.g. Float64Index and
         # datetimelike Indexes
         # reject them, if index does not contain label
-        if (is_float(label) or is_integer(label)) and label not in self.values:
+        if (is_float(label) or is_integer(label)) and label not in self._values:
             raise self._invalid_indexer("slice", label)
 
         return label
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index e2a7752cf3f0d..bf4047ddf29b1 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -357,11 +357,6 @@ def _format_with_header(self, header: List[str], na_rep: str = "NaN") -> List[st
     def inferred_type(self) -> str:
         return "categorical"
 
-    @property
-    def values(self):
-        """ return the underlying data, which is a Categorical """
-        return self._data
-
     @doc(Index.__contains__)
     def __contains__(self, key: Any) -> bool:
         # if key is a NaN, check if any NaN is in self.
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 23363e2c6e32a..1416f3afd60b3 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -348,13 +348,6 @@ def __contains__(self, key: Any) -> bool:
     def _multiindex(self) -> MultiIndex:
         return MultiIndex.from_arrays([self.left, self.right], names=["left", "right"])
 
-    @cache_readonly
-    def values(self) -> IntervalArray:
-        """
-        Return the IntervalIndex's data as an IntervalArray.
-        """
-        return self._data
-
     def __array_wrap__(self, result, context=None):
         # we don't want the superclass implementation
         return result