Published: 02 February 2024
生成式人工智能（GenAI）将对IT基础设施和运营（I&O）产生越来越深远的影响。为了做好准备，I&O领导者不仅需要评估其收益，还要衡量未来需持续面临的挑战，以确保能以安全可控的方式实施GenAI战略。
GenAI帮助资浅团队成员的学习曲线大大提速，使资深团队成员具备高级洞察和自动化能力，但关键的一点认知是：不能将GenAI视为人类专业知识的替代品。
多数网络团队通常厌恶风险，最初并不信任人工智能（AI）工具推荐的行动。
IT服务管理（ITSM）平台中的虚拟支持代理和其他AI生成的顾问功能，需要结合企业内部知识和文档来提供重要的价值。
鉴于围绕GenAI的炒作过多，使得用户对自动化开发改进的范围和规模产生了不切实际的期望，其热度将因负面体验而逐渐降低。
虽然目前基于助手的GenAI方法可以增加价值，但从长远来看，I&O产品中的GenAI价值将取决于其如何改变I&O工作。
积极选择和实施基于AI的数字办公场所管理工具，改善数字员工体验，提高运营效率；优先选择软件即服务（SaaS）工具，而不是本地工具，因为供应商能够快速实施功能。
从小规模入手，通过概念验证（POC）测试功能，在进入生产阶段之前对功能进行验证，对GenAI解决方案进行迭代。进入生产环境后，充分利用AI网络的建议和预测，并随着效率和信任度的提高，逐渐升级到无人值守的自动化阶段。
采用知识管理文档政策和格式标准（例如知识中心服务[KCS]），确保AI解决方案能够通过元数据利用信息情境。
自动化开发人员应采用“安全失败”的方法来实施开发实践，确保自动化故障以可控的方式发生。
对专注于I&O的供应商的GenAI能力和长期产品路线图进行评估。
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Analysts:
Cameron Haight, Chris Matchett, Jonathan Forest, Andrew Lerner, Tom Cipolla, Chris Saunderson, Colin Fletcher, Pankaj Prasad
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