The increasing complexity and scale of modern telecommunications networks demand intelligent automation to enhance efficiency, adaptability, and resilience. Agentic AI has emerged as a key paradigm for intelligent communications and networking, enabling AI-driven agents to perceive, reason, decide, and act within dynamic networking environments. However, effective decision-making in telecom applications, such as network planning, management, and resource allocation, requires integrating retrieval mechanisms that support multi-hop reasoning, historical cross-referencing, and compliance with evolving 3GPP standards. This article presents a forward-looking perspective on generative information retrieval-inspired intelligent communications and networking, emphasizing the role of knowledge acquisition, processing, and retrieval in agentic AI for telecom systems. We first provide a comprehensive review of generative information retrieval strategies, including traditional retrieval, hybrid retrieval, semantic retrieval, knowledge-based retrieval, and agentic contextual retrieval. We then analyze their advantages, limitations, and suitability for various networking scenarios. Next, we present a survey about their applications in communications and networking. Additionally, we introduce an agentic contextual retrieval framework to enhance telecom-specific planning by integrating multi-source retrieval, structured reasoning, and self-reflective validation. Experimental results demonstrate that our framework significantly improves answer accuracy, explanation consistency, and retrieval efficiency compared to traditional and semantic retrieval methods. Finally, we outline future research directions.

翻译：现代电信网络日益增长的复杂性和规模要求智能自动化以提升效率、适应性和韧性。代理式人工智能已成为智能通信与网络的关键范式，使人工智能驱动的代理能够在动态网络环境中感知、推理、决策和行动。然而，在电信应用（如网络规划、管理和资源分配）中实现有效决策，需要整合支持多跳推理、历史交叉引用以及符合不断演进的3GPP标准的检索机制。本文提出了一个关于生成式信息检索启发的智能通信与网络的前瞻性视角，强调了知识获取、处理和检索在电信系统代理式人工智能中的作用。我们首先全面回顾了生成式信息检索策略，包括传统检索、混合检索、语义检索、基于知识的检索以及代理式上下文检索。接着，我们分析了它们的优势、局限性及在不同网络场景中的适用性。随后，我们综述了这些策略在通信与网络中的应用。此外，我们引入了一个代理式上下文检索框架，通过整合多源检索、结构化推理和自反思验证，以增强电信特定规划。实验结果表明，与传统和语义检索方法相比，我们的框架显著提高了答案准确性、解释一致性和检索效率。最后，我们展望了未来的研究方向。