diff --git a/sagemaker-core/src/sagemaker/core/telemetry/constants.py b/sagemaker-core/src/sagemaker/core/telemetry/constants.py
index 04231ef8a0..4b9b9d3e66 100644
--- a/sagemaker-core/src/sagemaker/core/telemetry/constants.py
+++ b/sagemaker-core/src/sagemaker/core/telemetry/constants.py
@@ -32,6 +32,7 @@ class Feature(Enum):
     PROCESSING = 18
     MODEL_CUSTOMIZATION_NOVA = 19
     MODEL_CUSTOMIZATION_OSS = 20
+    INFERENCE_RECOMMENDER = 21
 
     def __str__(self):  # pylint: disable=E0307
         """Return the feature name."""
diff --git a/sagemaker-core/src/sagemaker/core/telemetry/telemetry_logging.py b/sagemaker-core/src/sagemaker/core/telemetry/telemetry_logging.py
index 96196e1182..aa44bac0af 100644
--- a/sagemaker-core/src/sagemaker/core/telemetry/telemetry_logging.py
+++ b/sagemaker-core/src/sagemaker/core/telemetry/telemetry_logging.py
@@ -76,6 +76,7 @@
     str(Feature.PROCESSING): 18,
     str(Feature.MODEL_CUSTOMIZATION_NOVA): 19,
     str(Feature.MODEL_CUSTOMIZATION_OSS): 20,
+    str(Feature.INFERENCE_RECOMMENDER): 21,
 }
 
 STATUS_TO_CODE = {
diff --git a/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/_model_builder_methods.py b/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/_model_builder_methods.py
index c4ce3ba29f..5bbe4907e6 100644
--- a/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/_model_builder_methods.py
+++ b/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/_model_builder_methods.py
@@ -81,7 +81,7 @@ def _map_service_error(error: Exception) -> Exception:
 
 
 @_telemetry_emitter(
-    feature=Feature.MODEL_CUSTOMIZATION, func_name="ai_inference_recommender.start_benchmark"
+    feature=Feature.INFERENCE_RECOMMENDER, func_name="ai_inference_recommender.start_benchmark"
 )
 def start_benchmark(
     endpoint: Union[Endpoint, str],
diff --git a/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/jobs.py b/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/jobs.py
index 5b5c459128..ec06111740 100644
--- a/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/jobs.py
+++ b/sagemaker-serve/src/sagemaker/serve/ai_inference_recommender/jobs.py
@@ -34,7 +34,7 @@ class BenchmarkJob(AIBenchmarkJob):
     """
 
     @_telemetry_emitter(
-        feature=Feature.MODEL_CUSTOMIZATION, func_name="BenchmarkJob.show_result"
+        feature=Feature.INFERENCE_RECOMMENDER, func_name="BenchmarkJob.show_result"
     )
     def show_result(self):
         """Download the benchmark output from S3 and return a parsed result.
@@ -58,7 +58,7 @@ class RecommendationJob(AIRecommendationJob):
     """
 
     @_telemetry_emitter(
-        feature=Feature.MODEL_CUSTOMIZATION, func_name="RecommendationJob.show_result"
+        feature=Feature.INFERENCE_RECOMMENDER, func_name="RecommendationJob.show_result"
     )
     def show_result(self) -> "_RecommendationsView":
         """Return the ranked recommendations produced by the job.
diff --git a/sagemaker-serve/src/sagemaker/serve/model_builder.py b/sagemaker-serve/src/sagemaker/serve/model_builder.py
index 275b09707e..453b097b73 100644
--- a/sagemaker-serve/src/sagemaker/serve/model_builder.py
+++ b/sagemaker-serve/src/sagemaker/serve/model_builder.py
@@ -4427,12 +4427,12 @@ def _model_builder_optimize_wrapper(
         return self.built_model
 
     @_telemetry_emitter(
-        feature=Feature.MODEL_CUSTOMIZATION,
+        feature=Feature.INFERENCE_RECOMMENDER,
         func_name="ModelBuilder.generate_deployment_recommendations",
     )
     def generate_deployment_recommendations(
         self,
-        workload=None,
+        workload: Optional[Union["Workload", str]] = None,
         performance_target: Optional[Union[str, "PerformanceTarget"]] = None,
         *,
         output_path: Optional[str] = None,