The first challenge is ensuring the availability of high-quality data that is relevant, accurate, and representative of the problem at hand. Second, there is a shortage of skilled professionals who can effectively develop, deploy, and interpret AI models. Third, ethical considerations arise in terms of data privacy, fairness, and bias, requiring you to establish robust governance frameworks. Next, the interpretability of AI models remains a challenge as complex models like deep learning neural networks are often regarded as black boxes. Lastly, AI models need ongoing monitoring to detect and address concept drift and to ensure that they remain accurate and unbiased as new data becomes available.