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Agentic ERP uses LLM agents for autonomous business workflow execution

Researchers have introduced Agentic ERP, a novel architecture designed to enable autonomous decision-making within Enterprise Resource Planning (ERP) systems. This system utilizes role-aligned large language model (LLM) agents, orchestrated through a graph-based Planner--Executor--Reflector--Responder framework, to manage complex business workflows. Evaluations demonstrated that Agentic ERP significantly outperformed traditional rule-based automation and no-intervention baselines, maintaining operational efficiency over a simulated year without stockouts. AI

IMPACT This research could enable ERP systems to move from passive data recording to active operational decision-making, potentially improving business efficiency.

RANK_REASON The cluster contains an academic paper detailing a new architecture and evaluation protocol for autonomous enterprise resource planning using LLM agents.

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Agentic ERP uses LLM agents for autonomous business workflow execution

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Zhihao Liu, Tianyu Wang, Xi Vincent Wang, Lihui Wang ·

    Agentic ERP: Multi-Agent Large Language Model Architecture for Autonomous Enterprise Resource Planning

    arXiv:2607.17331v1 Announce Type: new Abstract: Enterprise Resource Planning (ERP) systems record transactions reliably but still delegate almost all operational decision-making to human specialists, because classical rule-based automation cannot reason about exceptions and monol…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Lihui Wang ·

    Agentic ERP: Multi-Agent Large Language Model Architecture for Autonomous Enterprise Resource Planning

    Enterprise Resource Planning (ERP) systems record transactions reliably but still delegate almost all operational decision-making to human specialists, because classical rule-based automation cannot reason about exceptions and monolithic AI assistants degrade when asked to coordi…