Challenges of Implementing Agentic AI in Big Data Environments
Introduction Agentic AI, characterized by its autonomy, adaptability, and goal-oriented behavior, holds immense potential for transforming industries by leveraging big data. These systems can independently analyze vast datasets, make decisions, and adapt to changing conditions, making them ideal for complex, data-rich environments. However, implementing agentic AI in big data ecosystems presents significant challenges, from technical hurdles to ethical considerations. These obstacles can hinder adoption, increase costs, and impact the effectiveness of AI-driven solutions. This chapter explores the primary challenges of implementing agentic AI in big data environments, including scalability, data privacy, integration with legacy systems, bias mitigation, and skill gaps. We will discuss each challenge in detail, supported by real-world examples, and provide practical strategies for overcoming them. By understanding these challenges, organizations can better prepare for successfu...