1. Defining Objectives and Use Cases:
Goal Setting:
Clearly define what you want to achieve with AI and how it aligns with your overall business strategy. 
 
Use Case Identification:
Identify specific areas where AI can provide value, such as customer service, data analysis, or process automation. 
 
Example:
A retail company might use AI to personalize customer recommendations or optimize inventory management. 
 
2. Data Acquisition and Preparation:
Data Importance: High-quality data is crucial for training effective AI models. 
 
Data Collection: Gather relevant data from various sources and ensure it is clean, accurate, and well-structured. 
 
Data Storage: Store data securely and in a way that is easily accessible for AI models. 
 
Example: A financial institution might use historical transaction data and customer information to build a fraud detection system.