Agentic AI for Intent-Based Industrial Automation: Enabling Smart Decision-Making and Self-Optimizing Manufacturing Systems

Abstract

ABSTRACT

The advancement of artificial intelligence (AI) has significantly transformed industrial automation, enabling systems to perform complex tasks with increased efficiency and precision. Traditional automation relies heavily on predefined instructions and rigid control systems, limiting adaptability in dynamic industrial environments. Agentic AI, which embodies autonomous, goal-directed behavior, provides a promising approach for intent-based industrial automation. This paradigm allows machines to interpret high-level human intentions, make real-time decisions, and optimize processes without constant human intervention. This paper explores the integration of agentic AI in industrial automation, highlighting its architecture, capabilities, applications, challenges, and future scope. It emphasizes how agentic AI can enhance productivity, reduce operational costs, improve safety, and foster adaptive manufacturing systems.

KEYWORDS: Agentic AI, Intent-Based Automation, Industrial Systems, Smart Manufacturing, Autonomous Agents, Decision-Making, Predictive Control