diff --git a/doc/source/whatsnew/v2.0.0.rst b/doc/source/whatsnew/v2.0.0.rst
index 0ecdde89d9013..54c7a8697e23f 100644
--- a/doc/source/whatsnew/v2.0.0.rst
+++ b/doc/source/whatsnew/v2.0.0.rst
@@ -562,6 +562,7 @@ Removal of prior version deprecations/changes
 - Changed behavior of :meth:`SparseArray.astype` when given a dtype that is not explicitly ``SparseDtype``, cast to the exact requested dtype rather than silently using a ``SparseDtype`` instead (:issue:`34457`)
 - Changed behavior of :meth:`Index.ravel` to return a view on the original :class:`Index` instead of a ``np.ndarray`` (:issue:`36900`)
 - Changed behavior of :meth:`Series.to_frame` and :meth:`Index.to_frame` with explicit ``name=None`` to use ``None`` for the column name instead of the index's name or default ``0`` (:issue:`45523`)
+- Changed behavior of :func:`concat` with one array of ``bool``-dtype and another of integer dtype, this now returns ``object`` dtype instead of integer dtype; explicitly cast the bool object to integer before concatenating to get the old behavior (:issue:`45101`)
 - Changed behavior of :class:`DataFrame` constructor given floating-point ``data`` and an integer ``dtype``, when the data cannot be cast losslessly, the floating point dtype is retained, matching :class:`Series` behavior (:issue:`41170`)
 - Changed behavior of :class:`Index` constructor when given a ``np.ndarray`` with object-dtype containing numeric entries; this now retains object dtype rather than inferring a numeric dtype, consistent with :class:`Series` behavior (:issue:`42870`)
 - Changed behavior of :meth:`Index.__and__`, :meth:`Index.__or__` and :meth:`Index.__xor__` to behave as logical operations (matching :class:`Series` behavior) instead of aliases for set operations (:issue:`37374`)
diff --git a/pandas/core/dtypes/concat.py b/pandas/core/dtypes/concat.py
index 03429fd9fee1d..80eaf13d9dd06 100644
--- a/pandas/core/dtypes/concat.py
+++ b/pandas/core/dtypes/concat.py
@@ -4,12 +4,10 @@
 from __future__ import annotations
 
 from typing import TYPE_CHECKING
-import warnings
 
 import numpy as np
 
 from pandas._typing import AxisInt
-from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.astype import astype_array
 from pandas.core.dtypes.cast import (
@@ -115,15 +113,8 @@ def is_nonempty(x) -> bool:
 
     result = np.concatenate(to_concat, axis=axis)
     if "b" in kinds and result.dtype.kind in ["i", "u", "f"]:
-        # GH#39817
-        warnings.warn(
-            "Behavior when concatenating bool-dtype and numeric-dtype arrays is "
-            "deprecated; in a future version these will cast to object dtype "
-            "(instead of coercing bools to numeric values). To retain the old "
-            "behavior, explicitly cast bool-dtype arrays to numeric dtype.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
+        # GH#39817 cast to object instead of casting bools to numeric
+        result = result.astype(object, copy=False)
     return result
 
 
diff --git a/pandas/tests/reshape/concat/test_empty.py b/pandas/tests/reshape/concat/test_empty.py
index 18c0645df1ceb..68220855b3d7a 100644
--- a/pandas/tests/reshape/concat/test_empty.py
+++ b/pandas/tests/reshape/concat/test_empty.py
@@ -96,7 +96,7 @@ def test_concat_empty_series_timelike(self, tz, values):
         "left,right,expected",
         [
             # booleans
-            (np.bool_, np.int32, np.int32),
+            (np.bool_, np.int32, np.object_),  # changed from int32 in 2.0 GH#39817
             (np.bool_, np.float32, np.object_),
             # datetime-like
             ("m8[ns]", np.bool_, np.object_),
@@ -109,12 +109,8 @@ def test_concat_empty_series_timelike(self, tz, values):
         ],
     )
     def test_concat_empty_series_dtypes(self, left, right, expected):
-        warn = None
-        if (left is np.bool_ or right is np.bool_) and expected is not np.object_:
-            warn = FutureWarning
-        with tm.assert_produces_warning(warn, match="concatenating bool-dtype"):
-            # GH#39817
-            result = concat([Series(dtype=left), Series(dtype=right)])
+        # GH#39817, GH#45101
+        result = concat([Series(dtype=left), Series(dtype=right)])
         assert result.dtype == expected
 
     @pytest.mark.parametrize(