Strategic Design with AI Agents, Predefined Workflows and Agentic AI - Chandrababu C Nallapareddy (International Journal of Intelligent Systems and Applications in Engineering, 2025)
Artificial Intelligence (AI) agents are transforming application development by enabling adaptive decision-making and dynamic interactions in complex environments. These agents can learn from data, respond to real-time inputs, and operate autonomously, making them powerful for scenarios requiring flexibility and contextual intelligence. However, AI agents are not always the optimal choice. In many cases, predefined workflows structured, rule-based processes deliver greater predictability, cost-efficiency, and maintainability. Recent advances have introduced Agentic AI, a paradigm that blends the adaptability of AI agents with long-term planning, persistent memory, and tool integration. This paper compares AI agents, predefined workflows, and Agentic AI, analyzing their respective strengths, trade-offs, and ideal use cases. It also explores hybrid architectures that combine these approaches, providing practical guidance for selecting the most effective solution based on context, complexity, and operational goals.