NLP enables machines to understand and interpret human language. It can be used for automated text analysis, sentiment analysis, language translation, and chatbot interactions. Businesses can automate processes like customer support, document analysis, and information retrieval by using NLP algorithms to extract meaning and insights from textual data. ML algorithms enable machines to learn from data without explicit programming. They can identify patterns, make predictions, and continuously improve their performance over time. ML algorithms, such as decision trees and random forests (multiple decision trees) have been employed for business automation for years and are still used. Each node in a decision tree represents a decision based on a feature. For instance, decision trees can be used to segment customers based on their attributes, such as age, income, or purchase history, for targeted marketing campaigns. It is also used to identify patterns and anomalies in transaction data to detect fraudulent activities.