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As businesses enter the era of artificial intelligence (AI), enterprise organizations are reaching a tipping point with data storage. Increased regulatory pressure, emphasis on security, and cost concerns have all led to an increase in the on-premises storage of data, and the role of on-premises infrastructure is even more important in data-intensive initiatives such as artificial intelligence. |
随着企业进入人工智能（AI）时代，企业组织在数据存储方面正处于临界点。监管压力的增加、对安全的关注以及成本问题都导致了本地数据存储的增加，而本地基础设施在人工智能等数据密集型计划中的作用更为重要。 |
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According to Enterprise Strategy Group research:1 |
根据企业战略组的研究：1 |
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84% of organizations agreed that the growth of AI (including generative AI) has led to them reevaluating their application deployment strategy. |
84% 的组织认为，人工智能（包括生成式人工智能）的增长促使他们重新评估其应用程序部署策略。 |
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78% of organizations agreed that they prefer to run AI applications on premises. |
78% 的组织表示他们更愿意在本地运行 AI 应用程序。 |
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76% of organizations agreed that they view on-premises application deployments more favorably today than they did five years ago. |
76% 的组织认为，与五年前相比，他们今天对本地应用程序部署的看法更为乐观。 |
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As businesses scale business critical and data-intensive workloads, including AI, on premises, demand for cost-effective, scalable storage has reached all-time highs. The inherent flexibility of software-defined storage technology delivers exactly the cost-effective scale that businesses require, but historically, those benefits have been tempered by the complexity of hardware integration, deployment, and maintenance. In the contemporary enterprise, the pressures of staying cyber-resilient and architecting new initiatives—like AI—steal cycles from IT infrastructure operations, storage included. For example, 80% of storage administrators have taken on new responsibilities to support their organizations’ digital transformation initiatives or are under pressure to do so.2 |
随着企业在本地扩展包括人工智能在内的关键业务和数据密集型工作负载，对经济实惠、可扩展存储的需求已达到历史新高。软件定义存储技术固有的灵活性恰好提供了企业所需要的经济实惠的规模，但从历史上看，这些优势一直受到硬件集成、部署和维护的复杂性的抑制。在当代企业中，保持网络弹性和设计新举措（例如人工智能）所面临的压力使IT基础架构运营（包括存储）失去了周期。例如，80% 的存储管理员承担了支持组织数字化转型计划的新职责，或者面临着这样做的压力。2 |
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The result is that businesses must radically simplify on-premises infrastructure. The level of scale required for the AI era is not sustainable given traditional systems-based or even software-based approaches to data storage. Increased pressures on internal personnel have already led to recent growth in the adoption of on-premises infrastructure options that can be procured via a consumption-based model or as-a-service, and the pressures of AI will likely accelerate this trend. |
结果是，企业必须从根本上简化本地基础设施。鉴于传统的基于系统甚至基于软件的数据存储方法，人工智能时代所需的规模水平是不可持续的。内部人员压力的增加已经导致最近采用本地基础设施选项的人数增加，这些选项可以通过基于消费的模式或即服务采购，而人工智能的压力可能会加速这一趋势。 |
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The top benefits of as-a-service infrastructure options often manifest in the radical simplification that businesses now demand (see Figure 1). Specifically, the ability to accelerate initiatives via freeing up personnel (cited by 52%) and achieving increased budget flexibility (46%) combined with benefits tied to IT personnel experience/retention (46%) and operational costs (38%) highlight the already significant benefits being experienced. |
即服务基础架构选项的最大优势通常体现在企业现在要求的根本简化上（参见图 1）。具体而言，通过腾出人员（52％的人提出）和提高预算灵活性（46％）来加快举措的能力，加上与IT人员经验/留用率（46％）和运营成本（38％）相关的好处，凸显了已经获得的巨大好处。 |
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1. Source: Enterprise Strategy Group Complete Survey Results, Understanding Workload, App, and Data Deployment and Migration Decision-making, July 2024. |
1。来源：企业战略小组完整调查结果，了解工作负载、应用程序以及数据部署和迁移决策，2024 年 7 月。 |
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2. Source: Enterprise Strategy Group Complete Survey Results, Navigating the Cloud and AI Revolution: The State of Enterprise Storage and HCI, February 2024. All data in this brief is from this study, unless otherwise noted. |
2。来源：企业战略组完整调查结果，《驾驭云和人工智能革命：企业存储和超融合基础架构现状》，2024年2月。除非另有说明，否则本简报中的所有数据均来自本研究。 |