### Q1: What is one way AI enhances business intelligence through predictive analytics, and how can it impact decision-making in a retail context?  
### Q2: How does natural language processing (NLP) contribute to making data analysis more accessible for non-technical users in BI tools?  
### Q3: What are the key ethical considerations organizations should keep in mind when implementing AI in their business intelligence practices?  
### Q4: In what ways can a business utilize augmented analytics to streamline the data preparation process?  
### Q5: How can the integration of AI with Internet of Things (IoT) data provide real-time insights to a manufacturing company?  
### Q6: What are the potential risks associated with AI-driven BI that organizations must address to maintain trust with stakeholders?  
### Q7: How can you effectively communicate the benefits of AI in BI to a non-technical audience within your organization?  
### Q8: What strategies can be employed to encourage collaboration between technical teams and business units in leveraging AI for BI?  
### Q9: How can storytelling techniques be used to present AI-driven insights effectively to stakeholders, ensuring clarity and engagement?