diff --git a/airflow-core/src/airflow/example_dags/example_task_state_store_mapped.py b/airflow-core/src/airflow/example_dags/example_task_state_store_mapped.py
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+++ b/airflow-core/src/airflow/example_dags/example_task_state_store_mapped.py
@@ -0,0 +1,59 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""Example DAG with mapped tasks to demonstrate task state store isolation per map_index."""
+
+from __future__ import annotations
+
+import random
+from datetime import datetime, timezone
+
+from airflow.sdk import DAG, task
+
+TABLES = ["orders", "customers", "products"]
+
+with DAG(
+    dag_id="example_task_state_store_mapped",
+    schedule=None,
+    start_date=datetime(2026, 1, 1),
+    catchup=False,
+    tags=["example", "task-state-store"],
+    doc_md=__doc__,
+) as dag:
+
+    @task
+    def get_tables() -> list[str]:
+        """Return the list of tables to process."""
+        return TABLES
+
+    @task
+    def process_table(table: str, task_state_store=None, ti=None) -> dict:
+        """Process one table — each mapped instance gets its own task state."""
+        row_count = random.randint(100, 10000)
+        result = {
+            "table": table,
+            "map_index": ti.map_index,
+            "row_count": row_count,
+            "processed_at": datetime.now(tz=timezone.utc).isoformat(timespec="seconds"),
+        }
+        task_state_store.set("status", "complete")
+        task_state_store.set("result", result)
+
+        print(f"[map_index={ti.map_index}] Processed {table}: {row_count} rows")
+        return result
+
+    tables = get_tables()
+    process_table.expand(table=tables)