diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 8d0c8e5f29413..32439af6db238 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4298,8 +4298,14 @@ def insert(self, loc, column, value, allow_duplicates: bool = False) -> None:
                 "Cannot specify 'allow_duplicates=True' when "
                 "'self.flags.allows_duplicate_labels' is False."
             )
+        if not allow_duplicates and column in self.columns:
+            # Should this be a different kind of error??
+            raise ValueError(f"cannot insert {column}, already exists")
+        if not isinstance(loc, int):
+            raise TypeError("loc must be int")
+
         value = self._sanitize_column(value)
-        self._mgr.insert(loc, column, value, allow_duplicates=allow_duplicates)
+        self._mgr.insert(loc, column, value)
 
     def assign(self, **kwargs) -> DataFrame:
         r"""
diff --git a/pandas/core/internals/array_manager.py b/pandas/core/internals/array_manager.py
index 99a1706c671b1..950d229c45f9e 100644
--- a/pandas/core/internals/array_manager.py
+++ b/pandas/core/internals/array_manager.py
@@ -904,7 +904,7 @@ def iset(self, loc: Union[int, slice, np.ndarray], value):
             self.arrays[mgr_idx] = value_arr
         return
 
-    def insert(self, loc: int, item: Hashable, value, allow_duplicates: bool = False):
+    def insert(self, loc: int, item: Hashable, value: ArrayLike) -> None:
         """
         Insert item at selected position.
 
@@ -912,25 +912,18 @@ def insert(self, loc: int, item: Hashable, value, allow_duplicates: bool = False
         ----------
         loc : int
         item : hashable
-        value : array_like
-        allow_duplicates: bool
-            If False, trying to insert non-unique item will raise
-
+        value : np.ndarray or ExtensionArray
         """
-        if not allow_duplicates and item in self.items:
-            # Should this be a different kind of error??
-            raise ValueError(f"cannot insert {item}, already exists")
-
-        if not isinstance(loc, int):
-            raise TypeError("loc must be int")
-
         # insert to the axis; this could possibly raise a TypeError
         new_axis = self.items.insert(loc, item)
 
         value = extract_array(value, extract_numpy=True)
         if value.ndim == 2:
             if value.shape[0] == 1:
-                value = value[0, :]
+                # error: Invalid index type "Tuple[int, slice]" for
+                # "Union[Any, ExtensionArray, ndarray]"; expected type
+                # "Union[int, slice, ndarray]"
+                value = value[0, :]  # type: ignore[index]
             else:
                 raise ValueError(
                     f"Expected a 1D array, got an array with shape {value.shape}"
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index e4cce731b7b56..14fa994631623 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -1208,9 +1208,7 @@ def value_getitem(placement):
             # Newly created block's dtype may already be present.
             self._known_consolidated = False
 
-    def insert(
-        self, loc: int, item: Hashable, value: ArrayLike, allow_duplicates: bool = False
-    ):
+    def insert(self, loc: int, item: Hashable, value: ArrayLike) -> None:
         """
         Insert item at selected position.
 
@@ -1219,17 +1217,7 @@ def insert(
         loc : int
         item : hashable
         value : np.ndarray or ExtensionArray
-        allow_duplicates: bool
-            If False, trying to insert non-unique item will raise
-
         """
-        if not allow_duplicates and item in self.items:
-            # Should this be a different kind of error??
-            raise ValueError(f"cannot insert {item}, already exists")
-
-        if not isinstance(loc, int):
-            raise TypeError("loc must be int")
-
         # insert to the axis; this could possibly raise a TypeError
         new_axis = self.items.insert(loc, item)