技术与软件

行业概述:科技与软件

全球科技与软件行业正经历一场堪比从本地部署向云计算转型规模的平台变革——智能体AI能力、主权云基础设施需求,以及由AI时代威胁驱动而根本重塑的企业安全模型,共同重新定义着软件的构建、部署和保护方式。

智能体AI:新的应用层

如商业服务类别所讨论,智能体AI——能够利用外部工具和API自主规划并执行多步骤任务的AI系统——代表着多年来企业软件领域最重大的转变之一,智能体AI与自动化市场以32.6%的复合年增长率增长,到2031年将达到2278亿美元。对科技与软件行业而言,这一转变对软件架构和竞争格局具有深远影响:传统SaaS应用历来围绕浏览界面的人类用户设计,现正被重新构想,纳入代理可访问的API以及与传统UX并重的"代理体验"(AX)设计考量。基础模型提供商(OpenAI、Anthropic、谷歌)正将其代理框架和API定位为其他软件公司构建其上的新平台层,类似于云基础设施提供商成为上一代软件的基础层——这既创造了机遇(对于将有效智能体能力构建到产品中的软件公司而言),也带来了竞争威胁(对于其核心价值主张可能被在其现有界面上运行的、足够强大的通用代理所复制的软件公司而言)。

主权AI云:新兴基础设施类别

面向电信和企业应用的全球主权AI云基础设施市场反映出一种日益增长的需求,尤其是政府和受监管行业,需要在本国境内、受本国司法管辖的AI基础设施(计算、数据存储以及日益增多的AI模型本身)——这一需求由数据主权法规、对AI能力依赖外国提供商的国家安全考量,以及在某些情况下发展本国AI基础设施能力的明确产业政策目标共同驱动。这为电信公司(已运营大量数据中心基础设施并拥有现有政府和企业关系)扩展至AI基础设施提供创造了机遇,通常与全球云提供商或AI模型提供商合作,在满足数据主权要求的同时利用外部技术专长。海湾国家、印度和多个欧洲国家在发展主权AI基础设施举措方面尤为活跃,反映出AI能力日益受到的战略重视,以及对依赖美国或中国AI基础设施提供商的担忧。

零信任安全:应对AI时代威胁

网络安全架构持续向零信任模型转变——该模型不基于网络位置赋予隐含信任,而要求对每次访问请求进行持续验证——这一转变既受到绕过传统边界安全的复杂攻击持续盛行的驱动,也日益受到AI特有安全考量的驱动。面向电信行业的全球零信任网络架构市场反映了这一转变,该行业运营着尤为敏感的基础设施;更广泛而言,企业零信任的采用持续受到远程/混合办公永久常态化(消除了边界安全模型所依赖的传统"受信任内部网络"假设)以及AI代理本身作为一种新型"身份"出现(需要访问管理)的驱动——随着企业部署可访问内部系统和数据的AI代理,管理这些代理可访问的内容、授权范围以及审计追踪,已成为企业安全架构中日益重要的新维度,有时称为"非人类身份管理"。

云基础设施:AI驱动的产能动态

如能源与公用事业及建筑与房地产类别广泛讨论,AI工作负载已根本重塑云基础设施经济模式和产能规划,主要超大规模云提供商(AWS、微软Azure、谷歌云)报告的数据中心和AI基础设施资本支出水平均代表着相对历史模式的阶跃式变化。这加剧了围绕AI专属云服务——托管AI模型托管、微调基础设施,以及日益增多的智能体AI编排平台——作为企业云支出关键战场的竞争动态,即便核心基础设施即服务类别(计算、存储、网络)的增长率仍较其上层叠加的AI专属服务类别更为温和。

开源AI与模型生态系统

AI模型生态系统持续呈现专有前沿模型(来自OpenAI、Anthropic、谷歌等)与日益强大的开放权重模型生态系统(包括Meta、Mistral以及多家中国AI实验室如DeepSeek和阿里巴巴Qwen系列的模型)并存的格局,开放权重模型在许多企业用例中与专有模型的竞争力日益增强,尤其在数据驻留要求倾向于自托管部署的场景。这一动态对企业AI战略具有重大影响,企业需在API访问专有前沿模型的运营简便性与自托管开放权重模型的数据控制、定制灵活性及潜在成本优势之间权衡——这一决策矩阵与上文讨论的主权AI基础设施趋势直接相关。

区域动态

美国仍是大多数前沿AI模型开发和最大云基础设施提供商的所在地,尽管中国的AI生态系统已展现出尽管面临先进AI训练硬件出口管制限制,仍具有日益竞争力的开放权重模型开发能力,这持续引发关于基于硬件的限制对AI能力发展长期有效性的问题。印度科技行业持续作为全球AI生态系统的重要参与者,既是AI基础设施和服务的主要市场,也日益成为AI人才来源以及服务于国内和全球市场的AI应用开发地。

企业买家关注的研究重点

科技与软件领域的市场研究买家通常需要:智能体AI平台竞争格局与企业采用跟踪;按地区和提供商划分的主权AI云基础设施市场规模;零信任与非人类身份管理供应商分析;与AI需求相关的云基础设施产能与资本支出预测;以及按企业用例划分的开放权重与专有AI模型采用分析。

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