标题： 由代理控制：代理AI在未来计算环境中的作用综述 显示英文标题

标题： Governed By Agents: A Survey On The Role Of Agentic AI In Future Computing Environments

摘要： 代理人工智能（AI）的出现，能够自主运行、表现出目标导向行为并适应性学习，表明了当今计算基础设施的重大变化已经开始。 本研究探讨了代理AI模型的多种特性可能如何影响计算环境运作的架构、治理和操作。 由于资源效率，特别是处理和/或存储方面，代理AI有可能减少对极大型（公共）云环境的依赖。 上述特性为我们提供了一个机会，可以调查计算基础设施战略迁移的可能性，从大规模公共云服务转向更加本地化的分布式架构：边缘计算和本地计算基础设施。 其中许多可能的迁移将由本地处理需求、数据消耗足迹的减少以及成本节约等因素推动。 本研究考察了实现AI自主性的解决方案可能导致系统重新架构，并模拟从当今的治理模型中脱离，以帮助我们管理这些日益自主的代理，以及在涵盖通过云、边缘和本地计算解决方案整合的多样化计算系统环境中对流程进行运营上的全面改革。 为了使我们能够探索这些相互交织的决策，理解如何最好地定位代理AI，并导航计算基础设施的未来状态将是根本重要的。 显示英文摘要

摘要： The emergence of agentic Artificial Intelligence (AI), which can operate autonomously, demonstrate goal-directed behavior, and adaptively learn, indicates the onset of a massive change in today's computing infrastructure. This study investigates how agentic AI models' multiple characteristics may impact the architecture, governance, and operation under which computing environments function. Agentic AI has the potential to reduce reliance on extremely large (public) cloud environments due to resource efficiency, especially with processing and/or storage. The aforementioned characteristics provide us with an opportunity to canvas the likelihood of strategic migration in computing infrastructures away from massive public cloud services, towards more locally distributed architectures: edge computing and on-premises computing infrastructures. Many of these likely migrations will be spurred by factors like on-premises processing needs, diminished data consumption footprints, and cost savings. This study examines how a solution for implementing AI's autonomy could result in a re-architecture of the systems and model a departure from today's governance models to help us manage these increasingly autonomous agents, and an operational overhaul of processes over a very diverse computing systems landscape that bring together computing via cloud, edge, and on-premises computing solutions. To enable us to explore these intertwined decisions, it will be fundamentally important to understand how to best position agentic AI, and to navigate the future state of computing infrastructures.