Modelling AI agents for business data optimization

In an era where data-driven decision making is paramount, businesses face the challenge of efficiently managing and optimizing vast amounts of data. This doctoral dissertation presents the development of an artificial intelligent (AI) agent designed to enhance business data optimization through advanced modeling techniques. Utilizing an Object-Oriented Analysis and Design Methodology (OOADM), this research provides a structured framework for the systematic design and implementation of the AI agent. The proposed model leverages python as the primary programming language offering robust libraries and tools for machine learning and data analysis. The Ai agent integrates various algorithms such as neural network and SVM, identify patterns and generate actionable insights that aid in strategic decision-making processes. The AI agent is evaluated demonstrating significant improvements in data handling and decision-making speed. This study contributes to the field of business intelligence by providing scalable and adaptable solution for organizations seeking to harness the power of AI in optimizing their data driven strategies.