diff --git a/haystack/dataclasses/chat_message.py b/haystack/dataclasses/chat_message.py
index a7e2d318d..4bfbe5582 100644
--- a/haystack/dataclasses/chat_message.py
+++ b/haystack/dataclasses/chat_message.py
@@ -5,7 +5,6 @@
 from dataclasses import asdict, dataclass, field
 from enum import Enum
 from typing import Any, Dict, Optional
-from warnings import warn
 
 
 class ChatRole(str, Enum):
@@ -33,25 +32,6 @@ class ChatMessage:
     name: Optional[str]
     meta: Dict[str, Any] = field(default_factory=dict, hash=False)
 
-    def to_openai_format(self) -> Dict[str, Any]:
-        """
-        Convert the message to the format expected by OpenAI's Chat API.
-
-        See the [API reference](https://platform.openai.com/docs/api-reference/chat/create) for details.
-
-        :returns: A dictionary with the following key:
-            - `role`
-            - `content`
-            - `name` (optional)
-        """
-        warn("The `to_openai_format` method is deprecated and will be removed in Haystack 2.5.0.", DeprecationWarning)
-
-        msg = {"role": self.role.value, "content": self.content}
-        if self.name:
-            msg["name"] = self.name
-
-        return msg
-
     def is_from(self, role: ChatRole) -> bool:
         """
         Check if the message is from a specific role.
diff --git a/releasenotes/notes/deprecate-chatmessage-toopenaiformat-9b1b2987a568d3d7.yaml b/releasenotes/notes/deprecate-chatmessage-toopenaiformat-9b1b2987a568d3d7.yaml
new file mode 100644
index 000000000..8b861068a
--- /dev/null
+++ b/releasenotes/notes/deprecate-chatmessage-toopenaiformat-9b1b2987a568d3d7.yaml
@@ -0,0 +1,4 @@
+---
+upgrade:
+  - |
+    Remove `ChatMessage.to_openai_format` method. Use `haystack.components.generators.openai_utils._convert_message_to_openai_format` instead.
diff --git a/test/dataclasses/test_chat_message.py b/test/dataclasses/test_chat_message.py
index ab4606d7b..642ff4d55 100644
--- a/test/dataclasses/test_chat_message.py
+++ b/test/dataclasses/test_chat_message.py
@@ -5,6 +5,7 @@ import pytest
 from transformers import AutoTokenizer
 
 from haystack.dataclasses import ChatMessage, ChatRole
+from haystack.components.generators.openai_utils import _convert_message_to_openai_format
 
 
 def test_from_assistant_with_valid_content():
@@ -42,20 +43,24 @@ def test_from_function_with_empty_name():
 
 def test_to_openai_format():
     message = ChatMessage.from_system("You are good assistant")
-    assert message.to_openai_format() == {"role": "system", "content": "You are good assistant"}
+    assert _convert_message_to_openai_format(message) == {"role": "system", "content": "You are good assistant"}
 
     message = ChatMessage.from_user("I have a question")
-    assert message.to_openai_format() == {"role": "user", "content": "I have a question"}
+    assert _convert_message_to_openai_format(message) == {"role": "user", "content": "I have a question"}
 
     message = ChatMessage.from_function("Function call", "function_name")
-    assert message.to_openai_format() == {"role": "function", "content": "Function call", "name": "function_name"}
+    assert _convert_message_to_openai_format(message) == {
+        "role": "function",
+        "content": "Function call",
+        "name": "function_name",
+    }
 
 
 @pytest.mark.integration
 def test_apply_chat_templating_on_chat_message():
     messages = [ChatMessage.from_system("You are good assistant"), ChatMessage.from_user("I have a question")]
     tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
-    formatted_messages = [m.to_openai_format() for m in messages]
+    formatted_messages = [_convert_message_to_openai_format(m) for m in messages]
     tokenized_messages = tokenizer.apply_chat_template(formatted_messages, tokenize=False)
     assert tokenized_messages == "<|system|>\nYou are good assistant</s>\n<|user|>\nI have a question</s>\n"
 
@@ -76,7 +81,7 @@ def test_apply_custom_chat_templating_on_chat_message():
     messages = [ChatMessage.from_system("You are good assistant"), ChatMessage.from_user("I have a question")]
     # could be any tokenizer, let's use the one we already likely have in cache
     tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/zephyr-7b-beta")
-    formatted_messages = [m.to_openai_format() for m in messages]
+    formatted_messages = [_convert_message_to_openai_format(m) for m in messages]
     tokenized_messages = tokenizer.apply_chat_template(
         formatted_messages, chat_template=anthropic_template, tokenize=False
     )