The previous section provided a broad overview of quantum machine learning techniques. This section dives deeper into quantum enhancements for specific AI models like neural networks, transformers, and reinforcement learning agents. Early research shows that integrating quantum processing into classical AI algorithms can speed training, increase model capacity, and improve predictive accuracy. However, practical implementation remains challenging (Amin et al. in Phys Rev X 8, 2018 [1]).