^{Trained on infinite data of the internet, lacking domain specificity}

^{Lack of precision and consistency in LLM output; critical for enterprises}

^{Customization and fine-tuning of LLM is effort and cost-intensive}

^{Integrating LLM with existing apps and data can be challenging}

^{Model monitoring, maintenance, and retraining is expertise-intensive}

^{Optimization for speed and accuracy requires experimentation}

^{Sensitive data cannot be shared with cloud LLMs}

^{Compliance and regulatory objectives add complexity}

^{Need to manage bias, transparency, and accountability in training models}