diff --git a/pandas/_typing.py b/pandas/_typing.py
index a9177106535fc..2244be1b61fc6 100644
--- a/pandas/_typing.py
+++ b/pandas/_typing.py
@@ -109,12 +109,14 @@
 
 # types of `func` kwarg for DataFrame.aggregate and Series.aggregate
 AggFuncTypeBase = Union[Callable, str]
+AggFuncTypeDict = Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]]
 AggFuncType = Union[
     AggFuncTypeBase,
     List[AggFuncTypeBase],
-    Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]],
+    AggFuncTypeDict,
 ]
 
+
 # for arbitrary kwargs passed during reading/writing files
 StorageOptions = Optional[Dict[str, Any]]
 
diff --git a/pandas/core/aggregation.py b/pandas/core/aggregation.py
index 639b5f31835d1..ffc3283152687 100644
--- a/pandas/core/aggregation.py
+++ b/pandas/core/aggregation.py
@@ -23,6 +23,7 @@
 from pandas._typing import (
     AggFuncType,
     AggFuncTypeBase,
+    AggFuncTypeDict,
     Axis,
     FrameOrSeries,
     FrameOrSeriesUnion,
@@ -442,7 +443,7 @@ def transform(
             func = {col: func for col in obj}
 
     if is_dict_like(func):
-        func = cast(Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]], func)
+        func = cast(AggFuncTypeDict, func)
         return transform_dict_like(obj, func, *args, **kwargs)
 
     # func is either str or callable
@@ -466,7 +467,7 @@ def transform(
 
 def transform_dict_like(
     obj: FrameOrSeries,
-    func: Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]],
+    func: AggFuncTypeDict,
     *args,
     **kwargs,
 ):
@@ -560,7 +561,7 @@ def aggregate(
     if isinstance(arg, str):
         return obj._try_aggregate_string_function(arg, *args, **kwargs), None
     elif is_dict_like(arg):
-        arg = cast(Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]], arg)
+        arg = cast(AggFuncTypeDict, arg)
         return agg_dict_like(obj, arg, _axis), True
     elif is_list_like(arg):
         # we require a list, but not an 'str'
@@ -672,7 +673,7 @@ def agg_list_like(
 
 def agg_dict_like(
     obj,
-    arg: Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]],
+    arg: AggFuncTypeDict,
     _axis: int,
 ) -> FrameOrSeriesUnion:
     """
@@ -701,7 +702,7 @@ def agg_dict_like(
     # eg. {'A' : ['mean']}, normalize all to
     # be list-likes
     if any(is_aggregator(x) for x in arg.values()):
-        new_arg: Dict[Label, Union[AggFuncTypeBase, List[AggFuncTypeBase]]] = {}
+        new_arg: AggFuncTypeDict = {}
         for k, v in arg.items():
             if not isinstance(v, (tuple, list, dict)):
                 new_arg[k] = [v]