Detecting AI-generated reviews is crucial for maintaining the authenticity of online feedback in low-resource languages like Tamil and Malayalam. We propose a transfer learning-based approach using embeddings from XLM-RoBERTa, IndicBERT, mT5, and Sentence-BERT, validated with five-fold cross-validation via XGBoost. These embeddings are used to train deep neural networks (DNNs), refined through a weighted ensemble model. Our method achieves 90% F1-score for Malayalam and 73% for Tamil, demonstrating the effectiveness of transfer learning and ensembling for review detection. The source code is publicly available to support further research and improve online review systems in multilingual settings.