diff --git a/python/pyarrow/array.pxi b/python/pyarrow/array.pxi
index b704da73606d6..0e4732a3bf175 100644
--- a/python/pyarrow/array.pxi
+++ b/python/pyarrow/array.pxi
@@ -1689,8 +1689,11 @@ cdef _array_like_to_pandas(obj, options, types_mapper):
         arr = dtype.__from_arrow__(obj)
         return pandas_api.series(arr, name=name, copy=False)
 
-    # ARROW-3789(wesm): Convert date/timestamp types to datetime64[ns]
-    c_options.coerce_temporal_nanoseconds = True
+    # ARROW-33321 reenables support for date/timestamp conversion in pandas >= 2.0
+    from pyarrow.vendored.version import Version
+    if pandas_api.loose_version < Version('2.0.0'):
+        # ARROW-3789(wesm): Convert date/timestamp types to datetime64[ns]
+        c_options.coerce_temporal_nanoseconds = True
 
     if isinstance(obj, Array):
         with nogil:
diff --git a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
index 2cd6f5c26de0a..12cfbfbdc85de 100644
--- a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
+++ b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
@@ -86,6 +86,8 @@ PandasOptions MakeInnerOptions(PandasOptions options) {
   // datetime.datetime does not support nanoseconds).
   // We force the object conversion to preserve the value of the timezone.
   // Nanoseconds are returned as integers.
+  // In ARROW-33321, we no longer need to coerce for pandas versions >= 2.0,
+  // which now support all temporal types.
   options.coerce_temporal_nanoseconds = false;
 
   return options;
@@ -2061,9 +2063,18 @@ static Status GetPandasWriterType(const ChunkedArray& data, const PandasOptions&
     case Type::DATE64:
       if (options.date_as_object) {
         *output_type = PandasWriter::OBJECT;
+      } else if (options.coerce_temporal_nanoseconds) {
+        *output_type = PandasWriter::DATETIME_NANO;
       } else {
-        *output_type = options.coerce_temporal_nanoseconds ? PandasWriter::DATETIME_NANO
-                                                           : PandasWriter::DATETIME_DAY;
+        const auto& dt_type = checked_cast<const DateType&>(*data.type());
+        switch (dt_type.unit()) {
+          case DateUnit::DAY:
+            *output_type = PandasWriter::DATETIME_DAY;
+            break;
+          case DateUnit::MILLI:
+            *output_type = PandasWriter::DATETIME_MILLI;
+            break;
+        }
       }
       break;
     case Type::TIMESTAMP: {
diff --git a/python/pyarrow/table.pxi b/python/pyarrow/table.pxi
index fd5ba263d249e..f8bcd7d676321 100644
--- a/python/pyarrow/table.pxi
+++ b/python/pyarrow/table.pxi
@@ -2981,8 +2981,11 @@ def table_to_blocks(options, Table table, categories, extension_columns):
         c_options.extension_columns = {tobytes(col)
                                        for col in extension_columns}
 
-    # ARROW-3789(wesm); Convert date/timestamp types to datetime64[ns]
-    c_options.coerce_temporal_nanoseconds = True
+    # ARROW-33321 reenables support for date/timestamp conversion in pandas >= 2.0
+    from pyarrow.vendored.version import Version
+    if pandas_api.loose_version < Version('2.0.0'):
+        # ARROW-3789(wesm); Convert date/timestamp types to datetime64[ns]
+        c_options.coerce_temporal_nanoseconds = True
 
     if c_options.self_destruct:
         # Move the shared_ptr, table is now unsafe to use further