diff --git a/src/spatialdata/models/models.py b/src/spatialdata/models/models.py
index 6a126b02..e148a986 100644
--- a/src/spatialdata/models/models.py
+++ b/src/spatialdata/models/models.py
@@ -1047,25 +1047,39 @@ def _validate_table_annotation_metadata(self, data: AnnData) -> None:
             raise ValueError(f"`{attr[self.REGION_KEY_KEY]}` not found in `adata.obs`. Please create the column.")
         if attr[self.INSTANCE_KEY] not in data.obs:
             raise ValueError(f"`{attr[self.INSTANCE_KEY]}` not found in `adata.obs`. Please create the column.")
-        if (
-            (dtype := data.obs[attr[self.INSTANCE_KEY]].dtype)
-            not in [
-                int,
-                np.int16,
-                np.uint16,
-                np.int32,
-                np.uint32,
-                np.int64,
-                np.uint64,
-                "O",
-            ]
-            and not pd.api.types.is_string_dtype(data.obs[attr[self.INSTANCE_KEY]])
-            or (dtype == "O" and (val_dtype := type(data.obs[attr[self.INSTANCE_KEY]].iloc[0])) is not str)
+        dtype = data.obs[attr[self.INSTANCE_KEY]].dtype
+
+        # Check if dtype is valid for instance_key column
+        is_valid_dtype = False
+
+        # Check for integer types
+        if dtype in [int, np.int16, np.uint16, np.int32, np.uint32, np.int64, np.uint64] or isinstance(
+            dtype, pd.StringDtype
         ):
-            dtype = dtype if dtype != "O" else val_dtype
+            is_valid_dtype = True
+        # Check for CategoricalDtype with string categories
+        elif isinstance(dtype, pd.CategoricalDtype):
+            if pd.api.types.is_string_dtype(dtype.categories.dtype) or isinstance(
+                dtype.categories.dtype, pd.StringDtype
+            ):
+                is_valid_dtype = True
+        # Check for object dtype with string values
+        elif dtype == "O":
+            if len(data.obs[attr[self.INSTANCE_KEY]]) > 0:
+                val_dtype = type(data.obs[attr[self.INSTANCE_KEY]].iloc[0])
+                if val_dtype is str:
+                    is_valid_dtype = True
+            else:
+                # Empty column with object dtype is acceptable
+                is_valid_dtype = True
+        # Fallback check using pandas is_string_dtype
+        elif pd.api.types.is_string_dtype(dtype):
+            is_valid_dtype = True
+
+        if not is_valid_dtype:
             raise TypeError(
-                f"Only int, np.int16, np.int32, np.int64, uint equivalents or string allowed as dtype for "
-                f"instance_key column in obs. Dtype found to be {dtype}"
+                f"Only int, np.int16, np.int32, np.int64, uint equivalents, pandas StringDtype, or string "
+                f"allowed as dtype for instance_key column in obs. Dtype found to be {dtype}"
             )
         expected_regions = attr[self.REGION_KEY] if isinstance(attr[self.REGION_KEY], list) else [attr[self.REGION_KEY]]
         found_regions = data.obs[attr[self.REGION_KEY_KEY]].unique().tolist()