AI training and deployment is a multi-faceted task. AI Data Modeling is a key component, as AI models are built from existing data and the model's performance is largely determined by the quality of that data. To ensure AI models are optimized for predictive accuracy, it is critical to deploy AI that includes effective strategies such as AI hyper-parameter tuning and model selection to select the best AI model. Additionally, AI architectures must be properly chosen with consideration given to both system memory and processing power. AI models can be computationally expensive and are heavily dependent on the hardware/data processing technology used. AI also requires frequent monitoring, as AI models can become out of date or quickly break when unforeseen changes occur in underlying datasets. With proper careful implementation of AI training and deployment, Artificial Intelligence can provide solutions to challenging business problems.