### Q1: What is one easy way in which natural language processing (NLP) can be utilized in customer service applications?  
### Q2: How can understanding the structure of neural networks help sales leaders make more informed decisions regarding customer engagement strategies?  
### Q3: What are some difficult challenges related to data quality and compliance that a financial services company must address when implementing AI solutions?  
### Q4: How can a low-code approach to AI development streamline customer service processes in a financial services context?  
### Q5: In what ways can low-code tools enhance the implementation of neural networks for better prediction of customer behavior?  
### Q6: What are some complex scenarios where a low-code approach may not be sufficient for training AI models effectively?  
### Q7: How important is clear communication when explaining the concepts of Generative AI to non-technical stakeholders?  
### Q8: What strategies can be employed to effectively communicate the benefits of machine learning to your sales team?  
### Q9: How can you ensure that your communication regarding data management practices aligns with compliance regulations such as SOX?