AI Agents and Autonomous Systems: Architecture, Applications, and Enterprise Evaluation

Kanishka Singhal; Dr. Yatu Rani

AI Agents and Autonomous Systems: Architecture, Applications, and Enterprise Evaluation

Author(s)	Ms. Kanishka Singhal, Dr. Yatu Rani
Country	India
Abstract	The emergence of large language models (LLMs) has catalysed a shift from reactive machine-learning pipelines to proactive, multi-step autonomous systems commonly called AI agents. While industry adoption is growing rapidly, practitioners face a fragmented landscape of competing frameworks with little guidance on enterprise suitability. This paper addresses that gap through a systematic literature review of 20 works published between 2022 and 2025, combined with a six-dimension quantitative evaluation of four widely-adopted frameworks—LangChain, CrewAI, AutoGPT, and MetaGPT—scored on multi-agent support, memory management, tool integration, enterprise readiness, ease of setup, and scalability. The evaluation yields three principal findings: (1) no single framework satisfies all enterprise deployment requirements simultaneously, with the best-performing framework (LangChain) achieving only 73% of the ideal score; (2) persistent cross-session memory manage-ment remains an unsolved problem across all evaluated frame-works, averaging 2.5 out of 5; and (3) enterprise readiness—encompassing role-based access control, audit logging, and regu-latory compliance—is critically low, with all frameworks scoring at most 3 out of 5. Agent decision-making is formalised using reinforcement learning, including Q-learning and Bellman opti-mality equations, providing a theoretically grounded basis for the evaluation criteria. A concrete research roadmap spanning 2025–2030 is proposed to guide the community toward production-grade enterprise AI agent systems. The limitations of this study, including the subjective nature of the scoring rubric and the absence of live benchmarking, are discussed explicitly.
Keywords	AI agents, agentic AI, large language models, LangChain, CrewAI, AutoGPT, MetaGPT, multi-agent systems, reinforcement learning, enterprise AI, autonomous systems
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-11

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AI Agents and Autonomous Systems: Architecture, Applications, and Enterprise Evaluation

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