Agentic AI Pipelines for Autonomous Data Orchestration and Decision-Making

Abstract

As the computational storages continue increasing in size, there is an increasing trend toward creating autonomous systems that can successfully juggle complex data flows, making decisions on the go without any interventions from human beings. Existing data processing frameworks face problems of scalability, reliability, and flexibility, mainly owing to slow and inflexible human-driven validation and configuration paradigms. This writing establishes the concept of agentic forms of artificial intelligence designed for managing and validating data movement in complex settings and for autonomous decision-making in decision contexts. In complex settings, agentic forms of artificial intelligence aim at utilizing forms of multi-agent reasoning and collaboration in speeding up forms of data processing and decision-making through the introduction of autonomous decision nodes and XML-based agentic governance models for determining how forms of data processing and decision execution take place. Data handling and decision-making autonomy is considered the cornerstone of emerging forms of autonomous intelligent systems.