Modern supply chains are increasingly exposed to disruptions from geopolitical events, demand shocks, trade restrictions, to natural disasters. While many of these disruptions originate deep in the supply network, most companies still lack visibility beyond Tier-1 suppliers, leaving upstream vulnerabilities undetected until the impact cascades downstream. To overcome this blind-spot and move from reactive recovery to proactive resilience, we introduce a minimally supervised agentic AI framework that autonomously monitors, analyses, and responds to disruptions across extended supply networks. The architecture comprises seven specialised agents powered by large language models and deterministic tools that jointly detect disruption signals from unstructured news, map them to multi-tier supplier networks, evaluate exposure based on network structure, and recommend mitigations such as alternative sourcing options. \rev{We evaluate the framework across 30 synthesised scenarios covering three automotive manufacturers and five disruption classes. The system achieves high accuracy across core tasks, with F1 scores between 0.962 and 0.991, and performs full end-to-end analyses in a mean of 3.83 minutes at a cost of \$0.0836 per disruption. Relative to industry benchmarks of multi-day, analyst-driven assessments, this represents a reduction of more than three orders of magnitude in response time. A real-world case study of the 2022 Russia-Ukraine conflict further demonstrates operational applicability. This work establishes a foundational step toward building resilient, proactive, and autonomous supply chains capable of managing disruptions across deep-tier networks.

翻译：现代供应链日益暴露于地缘政治事件、需求冲击、贸易限制乃至自然灾害等多种中断风险。尽管许多中断源于供应链网络深层，但多数企业仍缺乏对一级供应商以外的可视性，导致上游脆弱性直至影响向下游级联时才被发现。为克服这一盲点，实现从被动恢复到主动韧性的转变，我们提出一种最小监督的智能体人工智能框架，能够自主监控、分析并响应扩展供应链网络中的中断事件。该架构包含七个由大语言模型和确定性工具驱动的专用智能体，它们协同工作以从非结构化新闻中检测中断信号，将其映射至多层级供应商网络，基于网络结构评估风险暴露程度，并推荐缓解措施（如替代采购方案）。\rev{我们在涵盖三家汽车制造商和五类中断事件的30个合成场景中评估该框架。系统在核心任务中均实现高精度，F1分数介于0.962至0.991之间，并以平均3.83分钟完成端到端分析，单次中断处理成本为0.0836美元。相较于行业基准中需数日人工分析的传统评估方式，本系统将响应时间缩短超过三个数量级。针对2022年俄乌冲突的真实案例研究进一步验证了其实际应用价值。本工作为构建具备韧性、主动性和自主性，能够管理深层网络中断的供应链奠定了重要基础。}