diff --git a/pandas/core/arrays/numeric.py b/pandas/core/arrays/numeric.py
index 80fbbf99a5494..3d157495c0c1f 100644
--- a/pandas/core/arrays/numeric.py
+++ b/pandas/core/arrays/numeric.py
@@ -24,6 +24,7 @@
     pandas_dtype,
 )
 
+import pandas as pd
 from pandas.core.arrays.masked import (
     BaseMaskedArray,
     BaseMaskedDtype,
@@ -231,16 +232,17 @@ def _coerce_to_data_and_mask(
             values = np.ones(values.shape, dtype=dtype)
         else:
             idx = np.nanargmax(values)
-            if int(values[idx]) != original[idx]:
-                # We have ints that lost precision during the cast.
-                inferred_type = lib.infer_dtype(original, skipna=True)
-                if (
-                    inferred_type not in ["floating", "mixed-integer-float"]
-                    and not mask.any()
-                ):
-                    values = np.asarray(original, dtype=dtype)
-                else:
-                    values = np.asarray(original, dtype="object")
+            if not (pd.isna(values[idx]) or pd.isna(original[idx])):
+                if int(values[idx]) != original[idx]:
+                    # We have ints that lost precision during the cast.
+                    inferred_type = lib.infer_dtype(original, skipna=True)
+                    if (
+                        inferred_type not in ["floating", "mixed-integer-float"]
+                        and not mask.any()
+                    ):
+                        values = np.asarray(original, dtype=dtype)
+                    else:
+                        values = np.asarray(original, dtype="object")
 
     # we copy as need to coerce here
     if mask.any():
diff --git a/pandas/tests/indexing/test_iloc.py b/pandas/tests/indexing/test_iloc.py
index ddb58ecbfa6f3..88856418cb531 100644
--- a/pandas/tests/indexing/test_iloc.py
+++ b/pandas/tests/indexing/test_iloc.py
@@ -1090,6 +1090,25 @@ def test_iloc_setitem_pure_position_based(self, indexer, has_ref):
         expected = DataFrame({"a": [1, 2, 3], "b": [11, 12, 13], "c": [7, 8, 9]})
         tm.assert_frame_equal(df2, expected)
 
+    def test_iloc_assignment_nullable_int_with_na(self):
+        # GH#62473
+        ser = Series(
+            [4, 6, 9, None, 10, 13, 15], index=[6, 1, 5, 0, 3, 2, 4], dtype="Int64"
+        )
+        indices = Series(
+            [6, 1, 5, 0, 3, 2, 4], index=[6, 1, 5, 0, 3, 2, 4], dtype="int64"
+        )
+        values = Series(
+            [4, 6, 9, None, 10, 13, 15], index=[4, 1, 2, 6, 0, 5, 3], dtype="Int64"
+        )
+
+        ser.iloc[indices] = values
+
+        expected = Series(
+            [NA, 6, 13, 10, 15, 9, 4], index=[6, 1, 5, 0, 3, 2, 4], dtype="Int64"
+        )
+        tm.assert_series_equal(ser, expected)
+
     @pytest.mark.parametrize("has_ref", [True, False])
     def test_iloc_setitem_dictionary_value(self, has_ref):
         # GH#37728