diff --git a/python/pyspark/pandas/series.py b/python/pyspark/pandas/series.py
index f7f8c89ab2783..7cb9ade3d8d99 100644
--- a/python/pyspark/pandas/series.py
+++ b/python/pyspark/pandas/series.py
@@ -104,6 +104,7 @@
 from pyspark.pandas.plot import PandasOnSparkPlotAccessor
 from pyspark.pandas.utils import (
     combine_frames,
+    is_ansi_mode_enabled,
     is_name_like_tuple,
     is_name_like_value,
     name_like_string,
@@ -5081,33 +5082,68 @@ def replace(
                     )
                 )
             to_replace = {k: v for k, v in zip(to_replace, value)}
+
+        spark_session = self._internal.spark_frame.sparkSession
+        ansi_mode = is_ansi_mode_enabled(spark_session)
+        col_type = self.spark.data_type
+
         if isinstance(to_replace, dict):
             is_start = True
             if len(to_replace) == 0:
                 current = self.spark.column
             else:
                 for to_replace_, value in to_replace.items():
-                    cond = (
-                        (F.isnan(self.spark.column) | self.spark.column.isNull())
-                        if pd.isna(to_replace_)
-                        else (self.spark.column == F.lit(to_replace_))
-                    )
+                    if pd.isna(to_replace_):
+                        if ansi_mode and isinstance(col_type, NumericType):
+                            cond = F.isnan(self.spark.column) | self.spark.column.isNull()
+                        else:
+                            cond = self.spark.column.isNull()
+                    else:
+                        lit = (
+                            F.lit(to_replace_).try_cast(col_type)
+                            if ansi_mode
+                            else F.lit(to_replace_)
+                        )
+                        cond = self.spark.column == lit
+                    value_expr = F.lit(value).try_cast(col_type) if ansi_mode else F.lit(value)
                     if is_start:
-                        current = F.when(cond, value)
+                        current = F.when(cond, value_expr)
                         is_start = False
                     else:
-                        current = current.when(cond, value)
+                        current = current.when(cond, value_expr)
                 current = current.otherwise(self.spark.column)
         else:
             if regex:
                 # to_replace must be a string
                 cond = self.spark.column.rlike(cast(str, to_replace))
             else:
-                cond = self.spark.column.isin(to_replace)
+                if ansi_mode:
+                    to_replace_values = (
+                        [to_replace]
+                        if not is_list_like(to_replace) or isinstance(to_replace, str)
+                        else to_replace
+                    )
+                    to_replace_values = cast(List[Any], to_replace_values)
+                    literals = [F.lit(v).try_cast(col_type) for v in to_replace_values]
+                    cond = self.spark.column.isin(literals)
+                else:
+                    cond = self.spark.column.isin(to_replace)
                 # to_replace may be a scalar
                 if np.array(pd.isna(to_replace)).any():
-                    cond = cond | F.isnan(self.spark.column) | self.spark.column.isNull()
-            current = F.when(cond, value).otherwise(self.spark.column)
+                    if ansi_mode:
+                        if isinstance(col_type, NumericType):
+                            cond = cond | F.isnan(self.spark.column) | self.spark.column.isNull()
+                        else:
+                            cond = cond | self.spark.column.isNull()
+                    else:
+                        cond = cond | F.isnan(self.spark.column) | self.spark.column.isNull()
+
+            if ansi_mode:
+                value_expr = F.lit(value).try_cast(col_type)
+                current = F.when(cond, value_expr).otherwise(self.spark.column.try_cast(col_type))
+
+            else:
+                current = F.when(cond, value).otherwise(self.spark.column)
 
         return self._with_new_scol(current)  # TODO: dtype?
 
diff --git a/python/pyspark/pandas/tests/computation/test_missing_data.py b/python/pyspark/pandas/tests/computation/test_missing_data.py
index dfecaf4be20b0..8489ce64b68ff 100644
--- a/python/pyspark/pandas/tests/computation/test_missing_data.py
+++ b/python/pyspark/pandas/tests/computation/test_missing_data.py
@@ -274,7 +274,6 @@ def test_fillna(self):
             pdf.fillna({("x", "a"): -1, ("x", "b"): -2, ("y", "c"): -5}),
         )
 
-    @unittest.skipIf(is_ansi_mode_test, ansi_mode_not_supported_message)
     def test_replace(self):
         pdf = pd.DataFrame(
             {