diff --git a/airflow/decorators/base.py b/airflow/decorators/base.py
index 7da74e5514e42..89f06b6aab591 100644
--- a/airflow/decorators/base.py
+++ b/airflow/decorators/base.py
@@ -300,6 +300,10 @@ def _infer_multiple_outputs(self):
         except TypeError:  # Can't evaluate return type.
             return False
         ttype = getattr(return_type, "__origin__", return_type)
+        if ttype == dict or ttype == Dict:
+            raise AttributeError(
+                "multiple_outputs was not set and will not implicitly unroll dict for return values"
+            )
         return ttype == dict or ttype == Dict
 
     def __attrs_post_init__(self):
diff --git a/docs/apache-airflow/tutorial/taskflow.rst b/docs/apache-airflow/tutorial/taskflow.rst
index 9db581200effe..497509102c5d7 100644
--- a/docs/apache-airflow/tutorial/taskflow.rst
+++ b/docs/apache-airflow/tutorial/taskflow.rst
@@ -377,19 +377,21 @@ section "Having sensors return XOM values" of :doc:`apache-airflow-providers:how
 
 Multiple outputs inference
 --------------------------
-Tasks can also infer multiple outputs by using dict Python typing.
+In case a task has multiple return values, Airflow can unroll these in separate values if using
+Python dict typing. The values then become available as separate arguments to downstream tasks.
 
 .. code-block:: python
 
-   @task
+   @task(multiple_outputs=True)
    def identity_dict(x: int, y: int) -> dict[str, int]:
        return {"x": x, "y": y}
 
 By using the typing ``Dict`` for the function return type, the ``multiple_outputs`` parameter
 is automatically set to true.
 
-Note, If you manually set the ``multiple_outputs`` parameter the inference is disabled and
-the parameter value is used.
+Note, before Airflow 2.5, Airflow would automatically unroll ``dict`` return values and you would need to set
+``multiple_outputs=False` explicitly. This was deemed confusing and now always defaults to ``False``.
+
 
 Adding dependencies between decorated and traditional tasks
 -----------------------------------------------------------
diff --git a/newsfragments/27819.significant.rst b/newsfragments/27819.significant.rst
new file mode 100644
index 0000000000000..ad0fc169467f0
--- /dev/null
+++ b/newsfragments/27819.significant.rst
@@ -0,0 +1,2 @@
+Airflow no longer automatically unrolls dict values into separate arguments requiring an explicit
+``multiple_outputs=True`` if unrolling is required.
diff --git a/tests/decorators/test_python.py b/tests/decorators/test_python.py
index 3ded6c80fa337..0e95494b3b517 100644
--- a/tests/decorators/test_python.py
+++ b/tests/decorators/test_python.py
@@ -94,19 +94,14 @@ def test_python_operator_python_callable_is_callable(self):
             "Dict[str, int]",
         ],
     )
-    def test_infer_multiple_outputs_using_dict_typing(self, resolve, annotation):
-        @task_decorator
-        def identity_dict(x: int, y: int) -> resolve(annotation):
-            return {"x": x, "y": y}
-
-        assert identity_dict(5, 5).operator.multiple_outputs is True
+    def test_infer_multiple_outputs_using_dict_typing_raises(self, resolve, annotation):
+        with pytest.raises(AttributeError) as e:
 
-        # Check invoking ``@task_decorator.__call__()`` yields the correct inference.
-        @task_decorator()
-        def identity_dict_with_decorator_call(x: int, y: int) -> resolve(annotation):
-            return {"x": x, "y": y}
+            @task_decorator()
+            def identity_dict(x: int, y: int) -> resolve(annotation):
+                return {"x": x, "y": y}
 
-        assert identity_dict_with_decorator_call(5, 5).operator.multiple_outputs is True
+        assert "not implicitly unroll" in str(e.value)
 
     def test_infer_multiple_outputs_using_other_typing(self):
         @task_decorator