diff --git a/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py b/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py
index 206cb0b9a..f7bb0ba23 100644
--- a/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py
+++ b/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py
@@ -1,7 +1,6 @@
 import json
 import logging
 import re
-import warnings
 from typing import Any, Callable, ClassVar, Dict, List, Optional, Type
 
 from botocore.exceptions import ClientError
@@ -150,12 +149,6 @@ def resolve_secret(secret: Optional[Secret]) -> Optional[str]:
         self.stop_words = stop_words or []
         self.streaming_callback = streaming_callback
 
-        warnings.warn(
-            "The `meta` output of the AmazonBedrockChatGenerator will change in the next release to be inline with "
-            "OpenAI `meta`output keys.",
-            stacklevel=2,
-        )
-
     @component.output_types(replies=List[ChatMessage])
     def run(
         self,
@@ -210,6 +203,12 @@ def run(
             msg = f"Could not inference Amazon Bedrock model {self.model} due: {exception}"
             raise AmazonBedrockInferenceError(msg) from exception
 
+        # rename the meta key to be inline with OpenAI meta output keys
+        for response in replies:
+            if response.meta is not None and "usage" in response.meta:
+                response.meta["usage"]["prompt_tokens"] = response.meta["usage"].pop("input_tokens")
+                response.meta["usage"]["completion_tokens"] = response.meta["usage"].pop("output_tokens")
+
         return {"replies": replies}
 
     @classmethod
diff --git a/integrations/anthropic/src/haystack_integrations/components/generators/anthropic/chat/chat_generator.py b/integrations/anthropic/src/haystack_integrations/components/generators/anthropic/chat/chat_generator.py
index 06b3dc353..9954f08c5 100644
--- a/integrations/anthropic/src/haystack_integrations/components/generators/anthropic/chat/chat_generator.py
+++ b/integrations/anthropic/src/haystack_integrations/components/generators/anthropic/chat/chat_generator.py
@@ -1,6 +1,5 @@
 import dataclasses
 import json
-import warnings
 from typing import Any, Callable, ClassVar, Dict, List, Optional, Union
 
 from haystack import component, default_from_dict, default_to_dict, logging
@@ -115,12 +114,6 @@ def __init__(
         self.client = Anthropic(api_key=self.api_key.resolve_value())
         self.ignore_tools_thinking_messages = ignore_tools_thinking_messages
 
-        warnings.warn(
-            "The `meta` output of the AnthropicChatGenerator will change in the next release to be inline with "
-            "OpenAI `meta`output keys.",
-            stacklevel=2,
-        )
-
     def _get_telemetry_data(self) -> Dict[str, Any]:
         """
         Data that is sent to Posthog for usage analytics.
@@ -220,6 +213,7 @@ def run(self, messages: List[ChatMessage], generation_kwargs: Optional[Dict[str,
                     # capture stop reason and stop sequence
                     delta = stream_event
             completions = [self._connect_chunks(chunks, start_event, delta)]
+
         # if streaming is disabled, the response is an Anthropic Message
         elif isinstance(response, Message):
             has_tools_msgs = any(isinstance(content_block, ToolUseBlock) for content_block in response.content)
@@ -227,6 +221,12 @@ def run(self, messages: List[ChatMessage], generation_kwargs: Optional[Dict[str,
                 response.content = [block for block in response.content if isinstance(block, ToolUseBlock)]
             completions = [self._build_message(content_block, response) for content_block in response.content]
 
+        # rename the meta key to be inline with OpenAI meta output keys
+        for response in completions:
+            if response.meta is not None and "usage" in response.meta:
+                response.meta["usage"]["prompt_tokens"] = response.meta["usage"].pop("input_tokens")
+                response.meta["usage"]["completion_tokens"] = response.meta["usage"].pop("output_tokens")
+
         return {"replies": completions}
 
     def _build_message(self, content_block: Union[TextBlock, ToolUseBlock], message: Message) -> ChatMessage: