diff --git a/doc/source/whatsnew/v1.0.0.rst b/doc/source/whatsnew/v1.0.0.rst
index d01a5fb4f8b43..ca950fbe047d9 100644
--- a/doc/source/whatsnew/v1.0.0.rst
+++ b/doc/source/whatsnew/v1.0.0.rst
@@ -402,6 +402,7 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 **Other removals**
 
 - Floordiv of integer-dtyped array by :class:`Timedelta` now raises ``TypeError`` (:issue:`21036`)
+- :func:`pandas.api.types.infer_dtype` argument ``skipna`` defaults to ``True`` instead of ``False`` (:issue:`24050`)
 - Removed the previously deprecated :meth:`Index.summary` (:issue:`18217`)
 - Removed the previously deprecated "fastpath" keyword from the :class:`Index` constructor (:issue:`23110`)
 - Removed the previously deprecated :meth:`Series.get_value`, :meth:`Series.set_value`, :meth:`DataFrame.get_value`, :meth:`DataFrame.set_value` (:issue:`17739`)
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index aaf6456df8f8e..780f93291cee8 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -4,7 +4,6 @@ from fractions import Fraction
 from numbers import Number
 
 import sys
-import warnings
 
 import cython
 from cython import Py_ssize_t
@@ -615,7 +614,7 @@ def clean_index_list(obj: list):
 
     # don't force numpy coerce with nan's
     inferred = infer_dtype(obj, skipna=False)
-    if inferred in ['string', 'bytes', 'unicode', 'mixed', 'mixed-integer']:
+    if inferred in ['string', 'bytes', 'mixed', 'mixed-integer']:
         return np.asarray(obj, dtype=object), 0
     elif inferred in ['integer']:
         # TODO: we infer an integer but it *could* be a uint64
@@ -1094,7 +1093,7 @@ cdef _try_infer_map(v):
     return None
 
 
-def infer_dtype(value: object, skipna: object=None) -> str:
+def infer_dtype(value: object, skipna: bool = True) -> str:
     """
     Efficiently infer the type of a passed val, or list-like
     array of values. Return a string describing the type.
@@ -1102,7 +1101,7 @@ def infer_dtype(value: object, skipna: object=None) -> str:
     Parameters
     ----------
     value : scalar, list, ndarray, or pandas type
-    skipna : bool, default False
+    skipna : bool, default True
         Ignore NaN values when inferring the type.
 
         .. versionadded:: 0.21.0
@@ -1113,7 +1112,6 @@ def infer_dtype(value: object, skipna: object=None) -> str:
     Results can include:
 
     - string
-    - unicode
     - bytes
     - floating
     - integer
@@ -1200,12 +1198,6 @@ def infer_dtype(value: object, skipna: object=None) -> str:
         bint seen_pdnat = False
         bint seen_val = False
 
-    if skipna is None:
-        msg = ('A future version of pandas will default to `skipna=True`. To '
-               'silence this warning, pass `skipna=True|False` explicitly.')
-        warnings.warn(msg, FutureWarning, stacklevel=2)
-        skipna = False
-
     if util.is_array(value):
         values = value
     elif hasattr(value, 'dtype'):
diff --git a/pandas/tests/dtypes/test_inference.py b/pandas/tests/dtypes/test_inference.py
index 743b844917edf..53e979d12a56d 100644
--- a/pandas/tests/dtypes/test_inference.py
+++ b/pandas/tests/dtypes/test_inference.py
@@ -628,13 +628,13 @@ def test_integer_na(self, arr, skipna):
         expected = "integer" if skipna else "integer-na"
         assert result == expected
 
-    def test_deprecation(self):
-        # GH 24050
-        arr = np.array([1, 2, 3], dtype=object)
+    def test_infer_dtype_skipna_default(self):
+        # infer_dtype `skipna` default deprecated in GH#24050,
+        #  changed to True in GH#29876
+        arr = np.array([1, 2, 3, np.nan], dtype=object)
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            result = lib.infer_dtype(arr)  # default: skipna=None -> warn
-            assert result == "integer"
+        result = lib.infer_dtype(arr)
+        assert result == "integer"
 
     def test_bools(self):
         arr = np.array([True, False, True, True, True], dtype="O")