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Agentic AI is moving from experimentation toward enterprise orchestration. Early deployments emphasized efficiency. As systems scale, the more significant shift lies in how enterprises redesign value creation, capture, and long-term advantage.

IDC’s FutureScape 2026 predictions identifies this transition as one of four strategic imperatives shaping the agentic future. Unlocking innovation beyond productivity defines how organizations translate AI maturity into new business models, revenue streams, and sustained competitive position.

Innovation beyond productivity refers to the structural redesign of business models, industry boundaries, and economic logic enabled by agentic AI operating across enterprise portfolios and ecosystems. It reflects how organizations convert AI maturity into scalable growth, differentiated customer value, and durable competitive advantage.

This is the focus of Pillar 4 within FutureScape 2026.

The productivity plateau

The first wave of AI delivered measurable gains. Contact centers reduced handle times. Back-office operations automated repetitive tasks. Sales and marketing teams improved throughput. These gains were important because they made AI investment tangible.

However, efficiency advantages diffuse quickly. What creates competitive differentiation in one quarter becomes standard capability the next. Productivity improvements, when layered onto existing operating models, eventually reach saturation.

Productivity-first strategies constrain long-term impact in three ways:

  1. They reinforce functional silos. AI is deployed by department, and each team optimizes local objectives.
  2. They lock in current assumptions. Optimization strengthens workflows designed for earlier market conditions.
  3. They produce linear gains. Efficiency improvements reach saturation when underlying structures remain unchanged.

The constraint is not AI capability. The constraint is operating design. When AI is layered onto legacy structures without structural redesign, outcomes remain incremental.

Innovation as the structural payoff of agentic AI

Innovation occurs when AI reshapes enterprise structure rather than simply accelerating task execution. Agentic AI enables coordinated decision-making across marketing, supply chain, finance, service, and ecosystem partners. Systems move from isolated automation toward orchestration embedded in enterprise operating models.

Innovation beyond productivity highlights three requirements for structural innovation in the agentic era:

  • Redefined industry boundaries. Agentic AI facilitates collaboration between domains that previously operated independently, reshaping competitive landscapes.
  • New economic logic. When agents operate autonomously at scale, assumptions about capacity, cost, and output change. Business cases designed for linear improvement do not capture compounding value created through coordination.
  • Governance as infrastructure. Governance must support cross-domain orchestration while embedding accountability into operating design.

Where value models are being rebuilt

FutureScape research identifies structural pressure points where value creation is already evolving. These signals reflect changes in pricing structures, industry organization, and coordinated delivery models.

Pricing model evolution
Traditional pricing frameworks were built around human labor and seat-based licensing. As agent interactions increase, value shifts from access to measurable outcomes. Enterprises and providers are redesigning pricing logic to reflect agent-mediated execution and results. This indicates a change in value capture, not simply a change in delivery.

Life sciences reinvention
Agentic AI is transforming pharmaceutical research and development. By 2030, 80 percent of pharmaceutical companies are projected to partner with TechBios, leveraging agentic AI and quantum computing to reduce R&D costs and failure rates. This signals new industry architectures built on coordinated discovery and ecosystem collaboration.

Healthcare system coordination
Healthcare has traditionally operated through linear care pathways. Agentic AI enables continuous orchestration across diagnosis, treatment, monitoring, and escalation. By 2030, one in three top-tier hospitals is expected to deploy AI agents delivering real-time decision support and autonomous workflows with high levels of accuracy. Clinical value becomes embedded in system coordination rather than isolated interventions.

Consumer ecosystem realignment
Immersive digital environments and gaming platforms are evolving into coordinated ecosystems for engagement and commerce. By 2026, two-thirds of Gen Z and Gen Alpha are projected to spend more time gaming than on social media. This signals movement toward platforms designed for persistent interaction and orchestrated value creation.

Rethinking AI ROI

As AI becomes integral to enterprise operating logic, traditional ROI metrics require reassessment. Leaders must reconsider three assumptions:

  • Short-term cost savings do not define strategic value.
  • Pilot programs do not create durable advantage without integration.
  • Model accuracy does not guarantee enterprise impact if objectives remain unchanged.

Legacy metrics focus on time saved and expenses reduced. Structural innovation requires evaluation of adaptability, cross-functional coordination, and long-term growth potential.

This shift aligns AI outcomes with enterprise design and economic logic, not isolated task performance.

Innovation as portfolio and ecosystem strategy

Agentic AI generates the greatest impact when managed as a coordinated portfolio rather than discrete initiatives. Each deployment should strengthen enterprise adaptability, improve cross-functional coordination, and expand future strategic options.

Unified governance frameworks support this model by embedding oversight into operating systems and enabling autonomous action within defined boundaries.

As agents operate across organizational and ecosystem boundaries, value creation becomes interdependent. Competitive advantage becomes systemic and embedded within enterprise design.

Defining the next horizon

Productivity remains necessary. Structural innovation determines sustained advantage.

The transition highlights a pivotal transition within the agentic journey. Agentic AI is redefining economic models, industry boundaries, and enterprise architecture. Organizations that redesign for orchestration, portfolio coordination, and ecosystem alignment position themselves for long-term growth in the AI-fueled economy.

Explore innovation beyond productivity in depth

FutureScape 2026 includes detailed research, analyst perspectives, and events that expand on the innovation beyond productivity theme.

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Explore the full FutureScape 2026 predictions.

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International Data Corporation (IDC) is the premier global market intelligence, data, and events provider for the information technology, telecommunications, and consumer technology markets. With more than 1,300 analysts worldwide, IDC offers global, regional, and local expertise on technology and industry opportunities and trends in over 110 countries. IDC’s analysis and insight help IT professionals, business executives, and the investment community make fact-based technology decisions and achieve their key business objectives.

In the fourth quarter of 2025 (4Q25), the worldwide enterprise WLAN market reached $2.9B, growing 13.9% year over year. The primary driver was the rapid adoption of Wi-Fi 7, which accounted for 39.7% of dependent access point segment revenue, up from 10.25% a year earlier. For full-year 2025, the market totaled $10.5B, with 11.4% annual growth, reflecting ongoing demand for advanced wireless standards.

Why enterprise WLAN matters in the AI era

In the AI era, connectivity is no longer just infrastructure—it is a strategic foundation for digital business. Enterprise WLAN plays a critical role in delivering secure, reliable, and high-performance connectivity across enterprise campuses, branches, and edge environments. At the same time, AI-driven applications, video traffic, and the rapid growth of IoT devices are placing unprecedented demands on network capacity, latency, and efficiency, pushing organizations to rethink and modernize their wireless networks.

IDC’s 4Q25 WLAN Tracker highlights a clear inflection point: 60% of global enterprise WLAN spending is now directed toward Wi-Fi 6E and Wi-Fi 7. This shift reflects a move from early adoption to mainstream deployment, as enterprises invest in next-generation WLAN technologies to support higher performance requirements and enable emerging AI-driven and distributed business models.

“Enterprise WLAN is entering a new phase where it’s no longer just about connectivity—it’s about enabling AI-driven and digital business operations. The rapid adoption of Wi-Fi 6E and Wi-Fi 7, combined with expanded 6GHz spectrum and AI-driven network operations, is reshaping expectations for performance, automation, and scale. At the same time, organizations are prioritizing integrated, platform-based architectures that unify networking, security, and observability, making modern WLAN a strategic foundation for intelligent, high-performance, and secure digital experiences.” — Brandon Butler, Senior Research Manager, Network Infrastructure and Services

Market dynamics: WiFi 7 and AI drive upgrades

The enterprise WLAN market is being shaped by continued innovation, evolving architectures, and the growing influence of AI. The expansion of 6GHz spectrum with Wi-Fi 6E and the accelerating adoption of Wi-Fi 7 are driving a new wave of upgrades.

At the same time, AI is improving how WLANs are designed and operated through greater automation and optimization, while enterprises adopt platform-based approaches that integrate WLAN with broader networking, security, and observability tools. Combined, these trends are driving strong growth in the enterprise WLAN market, both in 4Q25 and for full-year 2025.

From a geographic perspective, in 4Q25, the Americas saw a 13.9% year-over-year increase, while Europe, the Middle East & Africa experienced robust growth of 25.2% YoY. In contrast, the Asia Pacific region saw a slight revenue decline of 0.9% YoY, highlighting regional disparities in technology adoption and investment priorities.

Vendor performance: Cisco leads as growth accelerates

Cisco maintained its leadership in the enterprise WLAN market, with revenue rising 10.8% year over year to $1.0B and a market share of 34.6% in 4Q25. For the full year, Cisco’s revenue increased 4.9% to $3.9B, giving the company a market share of 37.2% at year-end.

HPE, now including Juniper following its July 2025 acquisition, grew 4.7% YoY to $552.8M, capturing 18.8% of the market in 4Q25. For the full year, HPE’s revenue increased 7.6% to $2.0B, giving the company a market share of 19.7% at year-end.

Ubiquiti saw the highest growth among major vendors, increasing 49.0% YoY to $344.5M and holding 11.7% market share in 4Q25. For the full year, the company’s revenue grew 53.1% to $1.2B, maintaining an 11.7% share in 2025.

Huawei posted strong growth, up 32.1% YoY to $409.8M, with a 14.0% share in 4Q25. For the full year, revenue rose 18.4% to $1.0B, giving the company a 9.6% share.

CommScope (Ruckus Networks) grew 13.4% YoY to $88.8M, representing 3.0% of the market in 4Q25. For the full year, revenue rose 26.0%, giving the company a 3.4% share.

Outlook: Wi-Fi 7 momentum and AI-driven networks

IDC expects continued momentum in enterprise WLAN upgrades as organizations pursue higher performance, greater automation, and tighter integration with AI-driven and distributed workloads. Wi-Fi 7 adoption is likely to accelerate further—alongside increased deployment of tri-band APs—particularly in regions with strong digital transformation initiatives.

Growth will also be supported by rising adoption of AI-driven network operations, platform-based networking approaches, and cloud-managed architectures, as enterprises seek more scalable and flexible environments. At the same time, evolving security requirements, including zero trust frameworks, will remain a key driver, while supply chain constraints or macroeconomic headwinds may temper growth in certain regions. Watch for continued innovation in AI capabilities, architectural models, and vendor strategies in the coming quarters.

For deeper analysis and IDC research on enterprise WLAN trends, visit IDC’s Worldwide Quarterly WLAN Tracker or contact IDC for the latest market insights.

Brandon Butler - Sr. Research Manager - IDC

Analyst Profile
Brandon Butler is a Senior Research Manager with IDC's Network Infrastructure group covering Enterprise Networks. His research focuses on market and technology trends, forecasts and competitive analysis in enterprise campus and branch networks. His coverage includes technologies used in local and wide area networking such as Ethernet switching, routing/SD-WAN, wireless LAN, and enterprise network management platforms. While contributing to ongoing forecast and market share updates, he also assists in end-user surveys, interviews and advisory services and contributes to custom projects for IDC's Consulting and Go-To-Market Services practices.

Petr Jirovsky - Senior Research Director, Network Infrastructure and Services - IDC

Analyst Profile LinkedIn
Petr Jirovsky is a Senior Research Director within IDC's Enterprise Infrastructure global research domain. He provides quantitative insights on network infrastructure for the datacenter, cloud, and campus/branch environments as part of the Network Infrastructure and Services subdomain. Petr serves as the global lead for IDC's Network Infrastructure Trackers, which track Ethernet switches, routers, wireless equipment, and application delivery appliances and services. He also contributes to numerous custom data projects and supports the publication of market share and forecast documents for the subdomain.

Diego Anesini - VP D&A, LatAm & Director Enterprise and Telecom - IDC

Analyst Profile LinkedIn
Diego Anesini serves as Research Vice-President, Data & Analytics for IDC Latin America, overseeing all the Information and Communications Technologies. Prior to this position, Diego held various roles in the company. The most recent was Enterprise Infrastructure and Telecom Director for Latin America. He has extensive experience in the Telecom and IT markets, due to his more than 25 years in the industry.

在刚刚落幕的英伟达GTC大会和阿里巴巴组织架构调整的双重催化下，“AI Token预算”已从科技圈的前沿话题，迅速演变为企业管理层案头的必答题。随着AI智能体（Agent）开始替代传统软件执行复杂任务，Token不再仅仅是技术计价单位，而是企业参与未来竞争的“数字石油”。

IDC最新研究显示，2025年中国AI相关IT支出预计将达到约380亿美元，并将在2027年前保持超过25%的年复合增长率，其中生成式AI推理相关支出占比快速提升，成为企业数字化投资中增长最快的子项之一。这一趋势表明，Token作为AI消费的核心计量单位，正在从“技术指标”转变为“财务指标”。

对于中国市场而言，凭借独特的成本优势与政策红利，为企业设立独立的Token预算科目，已不仅是财务精细化的需求，更是一场抢占“AI定价权”的战略博弈。

指数级消耗倒逼财务变革：Token是新型“生产力采购”

过去一年，全球日均Token消耗量增长近300倍，IDC中国追踪的企业级Token年度总消耗量过去一年也增长了近20倍，这一数字背后是AI从“辅助工具”向“生产力主体”的身份转变。

IDC调研进一步指出，已有超过60%的中国头部企业开始将生成式AI纳入核心业务流程（如研发、客服、营销自动化），其中超过30%的企业已经出现“AI调用成本不可控”的问题，这正是Token预算缺失的直接表现。

对企业而言，忽视Token预算的风险正在显现。一方面，若沿用传统的软件订阅制预算逻辑，企业将面临难以预测的“成本黑洞”——例如，一个重度使用的工程师，其年度AI推理支出可能突破10万美元，占其总人力成本的20%以上；另一方面，缺乏独立核算将导致投入产出比失真，无法精准衡量“每一美元Token究竟换来了多少业务价值”。

因此，将Token支出从“软件采购”剥离，升级为与人力、供应链同等重要的“核心生产资源”进行独立核算，已成为企业财务管理的必然选择。这标志着企业采购逻辑的转变：从购买“软件工具”转向购买“生产力服务”。

中国市场的“弯道超车”：性价比即竞争力

对于中国公司而言，制定Token预算具有特殊的地缘战略意义。当前，中国AI大模型市场正凭借极致的性价比在全球竞争中抢占先机。

IDC数据显示，中国大模型市场呈现出“高性价比+高调用量”的双重特征：2025年中国生成式AI模型调用量预计将占全球约35%以上，且增长速度显著高于北美市场。

得益于“东数西算”工程带来的绿电成本优势（西部数据中心电价仅为欧美的1/3至1/5），国产模型在Token单价上展现出碾压性优势。目前，中国主流大模型的Token单价仅为国外竞品（如Gemini）的1/6至1/10。

这种成本红利直接转化为市场数据：2026年初，中国大模型的周调用量已在全球主要API聚合平台上历史性地反超美国市场。

这意味着，中国公司若能充分利用本土模型的“价格洼地”，其Token预算的每一分钱都将具备更高的购买力。这不仅是降本增效的手段，更是中国企业在全球AI应用层竞争中实现“弯道超车”的关键窗口。

未来竞争的关键，不只是“谁用AI”，而是“谁用更低成本的Token创造更高密度的业务价值”。

如何编制你的Token预算？分层配置与动态调整

面对Token经济的浪潮，企业应如何着手准备预算？结合行业实践，建议从以下三个维度入手：

1. 分层设置消耗配额：

  • 基础层：保障高频、轻量级应用（如内部知识库、客服机器人），预算编制可参考历史消耗量，并叠加行业年均降价预期（预计年降本约30%）。
  • 战略层：预留高价值场景预算（如视频生成、AI自主编程、智能体编排），并将预算额度与具体的业务增长目标挂钩，确保高投入带来高回报。

2. 响应国家“算力通胀”治理：

国家数据局已将“降低社会算力总成本”列为重点任务。

IDC预计，到2027年，中国数据中心算力规模将增长超过2倍，其中AI算力占比将超过40%。在此背景下，Token成本管理将成为企业参与“算力资源配置”的关键能力。

企业设立独立的Token预算科目，不仅便于合规申报深圳等地推出的“算力券”补贴，也有助于满足ESG（环境、社会和公司治理）披露要求，如追踪单位Token的碳足迹。

3. 配置弹性对冲机制：

鉴于Token成本受地缘政治（如算力出口限制）和电力波动影响显著，建议企业在总预算中配置约20%的弹性空间，以应对不确定性。

IDC建议

IDC中国研究总监卢言霞表示，正如工业时代的企业必须预算电力成本，AI时代的企业必须学会预算Token成本。阿里巴巴成立“Token Hub”事业群、英伟达高呼“推理拐点已至”，这将提醒所有企业：Token不仅是成本，更是未来企业竞争力的量化指标。

IDC认为，未来3年内，是否具备“Token精细化管理能力”，将成为企业AI成熟度的重要分水岭。领先企业将呈现出三大特征：

  1. 将Token纳入核心财务指标体系
  2. 建立跨部门的AI成本治理机制（财务+IT+业务）
  3. 实现Token消耗与业务价值的实时映射

每个公司都应该现在就开始思考：你的年度预算表里，准备好“Token”这一项了吗？

关于Token预算、AI投入或相关实践，如果您有更多思考或问题，欢迎与我们交流。IDC也将持续分享最新研究与市场洞察，与您一起探索AI时代的增长机会。

如需进一步了解与研究相关内容或咨询 IDC其他相关研究，请点击此处与我们联系。

生成式AI和智能体的快速普及，正在改变网络安全的攻防模式。企业不仅要利用AI提升安全能力，也必须应对AI带来的新型风险。

近期，中国类OpenClaw应用快速发展，市场上出现了许多不同的龙虾智能体，如火山引擎的的ArkClaw、腾讯的QClaw等。阿里巴巴近日也发布了企业级Agent平台 “悟空” 。大模型、智能体的快速发展为千行百业带来众多机遇，网络安全产业也不例外。

一方面，AI正在赋能安全检测、漏洞分析和自动化修复，大幅提升安全运营效率；另一方面，AI应用本身也正在成为新的攻击入口。IDC在《IDC Link：中国网络安全技术前瞻，2026Q1》中指出，当前网络安全技术的发展正呈现出明显的 “All in AI”趋势。

以下是IDC观察到的七个关键技术趋势。

趋势一：安全智能体有望替代部分传统安全产品，成为安全团队“协作者”和“运营者”

2026年2月，Anthropic发布 Claude Code Security。这款安全智能体能够通过语义理解分析代码逻辑，并在真实环境中发现 500多个此前未被识别的高危漏洞。事实上，Google和OpenAI早在2025年就推出了类似的安全研究智能体，并将其应用于漏洞识别、代码审计和漏洞验证等场景。

与传统SAST、DAST或SCA工具相比，代码安全智能体在以下方面具有明显优势：

  • 更强的上下文理解能力
  • 更复杂的场景识别能力
  • 自动化修复能力

IDC认为，在任务重复度较高、难度较低的安全场景，智能体会快速落地，并替代掉部分安全工具和产品。但短期来看，AI并不会取代安全专家。当前主流安全智能体仍然保留 人工审批机制（Human in loop），因为在风险决策、责任归属和异常处理方面，人类仍然是关键环节。

趋势二：AI智能体应用正在成为新的攻击入口

OpenClaw龙虾爆火全球，其具备长期记忆能力，在本地运行，可以主动通过用户偏好的现有消息应用向用户发送消息并在后台持续运行，受到了全球用户的广泛关注并引发安装潮。但这类能力与高度自主性息息相关，意味着助手在实现目标时可能表现出异常强大的资源整合能力，这既带来了益处，也会大幅扩大威胁暴露面，“裸奔”的小龙虾会造成巨大的安全风险，给个人、企业带来难以挽回的巨大损失。

具体来说，OpenClaw存在如公网暴露+弱认证、Skill供应链风险、Agent权限失控风险、提示注入风险、敏感信息明文存储风险等。国家信息安全漏洞库（CNNVD）发布通报，2026年1月到3月9日，共采集到82个OpenClaw漏洞，存在极大的安全隐患。

为此 IDC 建议：禁用公网直接暴露，改用 127.0.0.1 并加密远程访问；最小化权限，关闭高危命令并启用二次确认；加密敏感数据，杜绝明文存密；仅安装官方可信插件；定期自查安全配置，及时整改风险。IDC《全球CIO议程2026年预测——中国启示》报告预测，到2030年，中国500强企业中15%的组织将因对AI智能体的管控与治理不足，引发高关注度的运营中断，进而面临诉讼、高额罚款及CIO被解雇的情况。企业管理者亟需构建一套智能体安全和治理体系来帮助企业安全地用好智能体，规避安全风险。

趋势三：非人类身份管理将成为现代身份管理体系的核心

在AI和自动化环境中，企业身份体系正在发生变化。除了员工身份外，越来越多 非人类身份 正在出现，如AI智能体、API密钥、服务账号等，这些身份推动企业自动化运行，但同时也扩大了攻击面。

IDC观察到，非人类身份管理平台（NHIM） 正成为企业安全架构的重要组成部分，非人类身份管理平台（NHIM）可为多云和代码环境中的机器身份提供基于AI驱动的自动化生命周期管理，具体能力如下：

  • 非人类身份的自动发现和分类
  • 最小权限管理
  • 动态密钥轮换
  • 身份归属管理
  • 态势监控与管理

IDC认为，通过整合这些功能，NHIM平台可实现一致的治理和安全性，使身份管理实践与零信任框架保持一致。未来，非人类身份管理将弥补IAM体系中的关键缺口，通过主动安全控制措施增强企业机器身份管理能力，降低机器身份相关事件发生的概率。

趋势四：AI-ready data成为AI安全的关键基础设施

在推进AI项目时，企业往往面临一个核心挑战：如何在推动AI应用落地的同时保护敏感数据。

IDC提出 AI-ready data 概念，即经过整理、清洗、脱敏和合规化处理的数据。

构建AI-ready data通常需要：

  • 用于AI训练推理的数据识别和分级分类治理
  • 跨场景统一安全策略
  • 细粒度访问控制

IDC认为，AI-ready数据既能保障数据安全与数据质量，消除 AI 项目推进的关键障碍，又能通过分层安全机制降低数据泄露与合规风险，为企业安全、高效、规模化落地 AI 应用提供稳定可靠的数据基础。

趋势五：PCC技术将推动企业数字化架构向更高的安全性、灵活性和智能化演进

当前许多企业在落地大模型应用时面临一个典型困境，即自建大模型成本过高，但使用公有云模型又担心数据隐私。PCC（Private Cloud Compute）私密云计算 正成为解决这一问题的重要技术路径。

PCC通过 端到端加密和硬件级安全隔离 构建 “数据可访问但不可见” 的运行环境，使企业能够在云端运行AI模型的同时保护核心数据。其既保留了云计算能力对复杂大模型任务的支持能力，又避免了传统公有云数据流的泄漏风险。

IDC认为，PCC可让企业在安全使用云端大模型能力的同时保护自身数据隐私，加速 AI 从试点探索走向规模化落地，并推动数据治理从静态合规评估转向动态隐私保护，实现大模型全生命周期安全管控。同时，PCC 能够拓展 AI 应用场景、提升用户信任，助力企业以轻资产模式快速部署合规的云 AI 服务。

趋势六：Deepfake防护需求快速增长

生成式AI正在让身份欺诈变得更加复杂。攻击者可以利用AI生成：深度伪造视频、合成身份以及自动化攻击脚本，这些攻击可能导致账户接管、财务损失和声誉风险。

为应对这一挑战，基于 AI 的生物识别和活体检测的多层身份验证技术正在成为关键防护手段，其主要功能包括：

  • AI生物识别
  • 活体检测
  • 分层身份认证

这些技术可以通过SDK或API集成到业务系统中，在提升安全性的同时保持用户体验。

IDC认为，多层身份验证技术可以帮助企业获得针对高级身份欺诈的认证保护，降低财务与声誉风险，满足全球合规标准，同时以快速无密码验证的方式提升用户体验与转化率，通过自动化降低运营成本，构建安全、合规且无摩擦的身份生态系统，为企业抵御不断演变的威胁提供未来保障。

趋势七：智能防偷拍技术补充了传统数据防泄漏技术在应对手机偷拍场景下的防护不足问题

传统DLP系统在防止文件外泄方面效果明显，但在手机偷拍场景中存在明显不足。例如2025年台积电数据泄露事件中，攻击者通过手机拍摄终端屏幕获取核心技术信息，并将相关信息外泄给竞争对手，造成了巨大损失。

智能防偷拍技术结合端侧AI能力和业务场景化设计，能够识别并阻断各类偷拍风险，通过终端侧AI模型，这类技术在不依赖特定手机型号的背景下可以：

  • 识别偷拍摄像头
  • 检测偷拍行为
  • 实时报警和阻断

IDC认为，随着AI技术的发展以及手机算力性能的不断提升，智能防偷拍技术将不断演进，在准确性、性能上不断提升，并进一步得到广泛应用。

IDC建议：以AI应对AI，构建面向未来的安全能力


IDC建议，企业应充分认识到AI正在重塑网络安全产业，并据此调整安全策略与技术路径。
一方面，随着众多安全智能体的出现，企业应逐步引入并应用安全智能体能力，对传统安全工具和产品进行AI化升级，在提升检测与防护能力的同时，优化安全软件体系与产品组合。


另一方面，随着OpenClaw等AI智能体应用的快速发展，AI自身的安全防护正成为全新的网络安全攻防战场。企业在延续传统网络安全手段的基础上，应重点关注AI应用带来的新型风险，并加强相关安全防护能力建设。


在此背景下，IDC建议企业逐步构建“以模治模”的安全防护体系，利用AI技术对抗AI驱动的攻击，通过AI赋能安全检测与防护能力，形成适应AI时代的网络安全产品与技术体系，从而更有效地保护用户在AI环境下的网络安全。

IDC更多相关研究

IDC已于2026年启动AI安全技术系列研究，围绕AI原生安全架构、安全智能体成熟度评估、AI驱动DevSecOps实践路径及企业级AI治理框架展开深入分析。

如需进一步了解与研究相关内容或咨询 IDC其他相关研究，请点击此处与我们联系。

Sophia Wang - Research Manager - IDC

Sophia Wang is a Research Manager in IDC China. She is responsible for the analysis and research of China's cybersecurity market. Her primary focus is on China's cybersecurity appliance and services market and operational technology (OT) security market. Additionally, she provides related research and consulting services for regional and global IT customers and supports their business development. Prior to joining IDC, Sophia worked in several consulting companies. She was independently responsible for consulting projects in fast-moving consumer goods (FMCG), internet, and other industries. Through market analysis and benchmarking analysis, she helped many clients solve problems in the different stages of their development. Sophia graduated from the University of Southern California with a master's degree in econometrics. She also majored in human resource management and journalism for her bachelor's degree.

随着生成式AI、大模型及Agent能力持续演进，围绕“AI是否会取代SaaS”的讨论正在快速升温。基于当前企业采用进度、软件支出变化、AI规模化落地情况以及企业工作方式转型趋势的综合观察，IDC的判断是：AI不会在中短期内取代SaaS，但将推动SaaS进入新一轮结构性重构周期。 企业软件市场未来的主要变化，不是SaaS的消失，而是SaaS从“功能交付工具”向“智能执行平台”演进。

当前，AI与SaaS之间并非替代关系，而更接近于“能力叠加”与“价值重定义”关系。随着企业客户从模型试点走向业务落地，从当前市场需求变化看，企业对软件平台的要求，正在从基础数字化和AI集成能力，进一步延伸至以AI Agent为代表的智能能力，包括任务执行、流程协同、系统连接、治理承接及业务结果支撑。

在明确 AI 与 SaaS 并非替代、而是能力叠加的核心关系后，我们可以从企业预算与市场结构的维度，进一步拆解这一演进趋势的现实表现 ——AI 技术的渗透并未削弱软件市场的基本盘，反而在重构企业对软件价值的判断标准与采购逻辑。

观点一：AI预算快速增长，但软件支出并未被替代

IDC数据显示，2025年全球生成式AI支出将达到 1843亿美元，同比增长151.6%。与此同时， 2025年全球IT总支出将达到 6.8万亿美元，其中软件支出将达到1.3万亿美元，同比增长 14.2%。这表明，AI投资扩张并未系统性挤压企业软件预算，反而正在推动企业重新定义软件的能力边界。

从市场结构看，企业并没有因为AI出现而停止采购软件，而是在加速采购“具备AI能力的软件”。这意味着，SaaS的需求基础并未减弱，但产品标准正在提升。未来，缺乏智能能力、缺乏AI与业务流程融合能力以及缺乏数据壁垒的传统SaaS产品，竞争压力将加大；而能够承接AI任务并支撑流程执行的平台型软件，战略重要性将持续提升。

观点二：AI采用率提升很快，但规模化价值兑现仍处于早期阶段

IDC的数据显示，2025年，亚太地区企业平均每年开展17.9个生成式AI概念验证（PoC）项目，PoC转入生产环境的比例为34.5%，也就是说，每10个PoC项目中约有3至4个最终进入生产阶段。在KPI达成率方面，亚太地区平均为36.8%，意味着进入生产环境的GenAI服务中，约37%能够实现预期业务目标。这些最新数据表明，企业对AI试点的热情依然高涨，但从PoC走向规模化生产的转化率，以及业务成效的实际达成率，仍有较大提升空间。

这表明，AI要从“具备生成与回答能力”进一步走向“具备执行能力、可审计性、可复制性和规模化应用能力”，仍需经过持续的场景验证与业务实践。仅依靠AI模型本身，尚不足以形成完整的企业级价值闭环，企业仍需要由业务系统与平台能力持续提供数据访问、权限控制、复杂流程编排、主数据管理及合规治理等关键支撑能力。也正因为如此，SaaS在AI时代并不会被削弱，反而将在任务执行、流程承接与治理支撑等方面承担更加重要的角色。

观点三：AI正在改变企业应用软件的交互方式与价值交付逻辑

传统SaaS的核心价值，在于以模块化、标准化的方式承载企业流程，并通过菜单、表单、权限和审批机制推动业务数字化落地。但随着生成式AI和AI Agent能力不断渗透，企业软件的交互逻辑正在发生明显变化：从过去的 “用户操作功能” ， 逐步转向 “用户提出需求、系统理解意图并执行任务” 。在这一变化过程中，软件价值的衡量标准也在同步改变。企业关注的重点，正在从功能是否齐全，转向任务完成效率、流程自动化水平，以及对实际业务结果的支撑能力。

IDC预测，到2027年，约有50%的企业将在核心业务流程中引入AI agents，重塑人与机器之间的协作方式。这一趋势表明，AI agents正在从辅助工具逐步演变为企业工作体系的重要组成部分，而不再只是单点能力的补充。这也意味着，未来的软件平台，无论是SaaS还是企业级PaaS，都不再只是承担数据录入和流程流转的基础角色，而将进一步承担任务编排、系统集成、过程留痕和治理支撑等职责，成为AI执行任务时所依赖的业务底座。

与此同时，AI也正在重塑企业软件的交付方式与商业模式。基于用量的定价、智能体驱动的交互界面，以及基于结果的价值衡量，正在对传统的按席位订阅模式形成冲击。这种变化并不只停留在概念层面，而是已经在市场中逐步发生。

观点四：将被替代的更可能是低壁垒、浅流程的SaaS产品

从竞争格局变化看，AI对SaaS市场的影响并非均匀分布。预计首先受到冲击的，将是那些功能相对单一、流程嵌入程度有限、差异化不足，且主要依赖界面交互提供价值的轻量型SaaS产品。随着AI Agent逐步具备任务理解、流程拆解与自动执行能力，这类产品的独立价值空间可能被进一步压缩。

相比之下，深度嵌入企业核心流程、掌握关键业务数据、具备权限控制与合规支撑能力，并拥有行业知识积累的平台型软件，在AI时代更可能提升其战略重要性。这类平台不仅更有条件承接AI Agent的任务执行与流程协同，也更有可能在未来企业软件架构与采购体系中占据核心位置。

IDC中国企业级应用软件市场高级研究经理徐文婷认为，未来2-3年，企业将不会简单以AI替代现有软件系统，而是要求软件平台具备AI原生能力，并能够支撑AI Agent在业务场景中的应用。预计市场竞争焦点将逐步从功能覆盖转向任务执行、流程自动化和业务结果支撑能力。对SaaS厂商而言，关键不在于是否面对AI技术本身，而在于能否将AI有效嵌入企业级数据、业务流程和治理框架。从当前市场发展看，AI正在重塑SaaS的产品定义，但尚未改变企业对系统平台的根本需求。随着AI Agent从试点走向生产环境，SaaS将进一步向平台化和智能化演进，并承担更多任务执行与治理支撑职能。

为了更好的帮助用户了解企业级软件AI的发展动态和未来趋势，IDC正式启动《中国AI-Enable ERP市场份额研究，2026》报告、《中国企业资源管理（ERM）市场AI Agent技术厂商评估报告，2026》报告研究，欢迎大家与我们保持沟通交流，与IDC共同开展更多前瞻性与实践性研究。

IDC相关研究报告：

Worldwide AI and Generative AI Spending Guide 2025

Worldwide Black Book 2025

Automation, AI, and Agentic AI for FoW: Worldwide Tech Buyer Perspective Doc#：EUR154249426

IDC Survey: Enterprise AI Trends – the Latest Survey Insights Doc#：AP53632426

IDC 2026年软件和服务领域研究计划：

如需进一步了解与研究相关内容或咨询 IDC其他相关研究，请点击此处与我们联系。

2026年中国家电及消费电子博览会（AWE2026）于3月12日至15日在上海双区同步举行，以“AI科技，慧享未来”为主题，首次采用“一展双区”模式，全面呈现AI原生产品的加速落地。主展区聚焦AI+生态，涵盖智能家电、健康个护、家庭机器人等核心品类；新设的“消费电子先进科技展区”则集中展示消费电子产业的前沿技术突破，成为全球科技首发的关键平台。本届AWE无疑是历届以来AI含量最高、场景融合最深的一届。

据《IDC中国智能家居市场跟踪报告预测数据，2025年第四季度》预测，2026年中国智能家居设备市场预计出货达3亿台，同比增长8.8%。其中智能扫地机器人及智能照明设备市场引领增长。

四大关键词：AI重塑家庭场景的核心逻辑

  • 主动感知：从“被动响应”走向“主动服务”

全屋智能系统突破传统语音指令局限，搭载主动感知、智能预判能力，实现多设备无缝联动协同，让家居智能从 “被动响应” 迈向 “主动服务”。

  • 适老升级：居家康养成智能设备新刚需

紧扣老龄化社会刚需，居家康养成为家庭设备升级核心方向。智能看护设备、家庭服务机器人纷纷聚焦适老化场景，成为品牌技术与服务能力的重要展示窗口。

  • 跨界融合：打通“人、车、家”多元生活场景

AWE 持续以场景化体验为核心，打通人、车、家多元生活场景，各品类家电互为生态链接枢纽，重构未来品质生活图景，打造一体化智慧生活新愿景。

AI原生落地：从技术概念到生活实景

创新科技展区成为 AI 技术家庭落地的实践窗口，头部品牌将大模型、深度学习、感知交互等核心技术深度融入产品，AI 原生手机、AI 眼镜、AI 会议耳机等前沿终端悉数亮相，推动 AI 原生时代全面到来。AI Agent能力成为决胜厂商竞争力的关键。

五大市场洞察：从功能叠加到系统智能的跃迁

  1. 未来厨房加速演进，数据能力成厂商新护城河

未来厨房概念在本届AWE吸引关注。当前新设备整合油烟、燃气、温湿度、视觉、用户行为、菜谱等多类型数据，形成统一场景决策，同时需要基于烹饪习惯、设备使用数据，提供精准菜谱、场景模式与主动服务。从网络接入看，需采用本地边缘计算与云端协同架构，支持 Wi‑Fi 6/7、Thread 等多模连接，满足低时延、高可靠与多设备并发需求。数据层面，传感器、控制及多媒体数据爆发式增长，要求边缘实时处理、本地存储与云端分析结合，兼顾数据安全与隐私合规。厂商从卖单品转向打造厨房全链路智能方案，并有机会围绕适老等热点以安全便捷为核心推出新的细分赛道爆品。

  • 情感化AI崛起，陪伴式服务成差异化突破口

海尔、TCL、珞博智能、灵童机器人、宇树科技、魔法原子等集中展出陪伴式服务产品，涵盖情感陪伴机器人、家庭服务机器人等。智能家电需从指令执行转向主动关怀，聚焦适老、育儿、独居等更符合当前中国家庭的真实场景。当前，厂商可通过融合语音、表情、肢体、语气等多模态交互弱化机械感，同时依托经典 IP 或打造原生机器人 IP，构建更具辨识度、难以替代的陪伴体验。

  • 细分场景迈向品质化，清洁设备更具“人性”

用户对细分场景的需求，已不再满足于基础功能的实现，而是全面迈向品质化、精细化、个性化的高阶体验。随着居家场景不断细分与多元，消费者诉求也愈发具体、私密与专属。无论是健康护理、居家清洁、智慧厨房还是睡眠起居等垂直领域，参展企业均以高端材质、人性化设计、原生 AI 主动服务及系统化解决方案，提升场景体验的舒适度、专业性与高级感，充分彰显家居消费升级下品质优先的核心趋势。作为家居生活的核心场景之一，本届 AWE 清洁类新品更具温度与人性，从被动执行转向主动理解、贴心适配。依托 AI 大模型实现环境感知、行为预判与个性化清洁方案，搭配高温蒸汽除菌、仿生机械臂贴边、轮足跨层越障等前沿技术，让家庭清洁场景的迭代始终围绕人的真实需求展开，真正做到科技为人服务、清洁以人为本。

  • AI智能体时代：竞争从“单点”走向“系统”

在家庭场景中，智能产品的竞争维度正加速拓宽。竞争焦点已从单一的性能参数，延伸至多智能体协同、具身智能落地、垂直场景深度适配、全链路数据与隐私保护等综合能力层面。同时，硬件自研、系统级调度与开放生态建设也成为关键竞争力。展会现场的实际案例进一步表明，行业已从早期的“单点智能”竞争，演进为以“系统智能”为核心的价值创造阶段。竞争格局日趋立体，呈现“功能叠加”向“体验整合”跃迁的明显趋势。

  • 中国厂商领跑新品类，从参与者变定义者

本届AWE有一百多家企业首次参展。全新的机器人、拍摄眼镜、感知戒指、电动滑板车、老人AI敲击呼叫器等等新品类层出不穷，国内企业已从市场参与者，升级为技术、产品与场景的定义者和引领者。在核心技术自研、产品形态创新、场景深度适配、生态协同构建等方面实现系统突破。凭借快速工程化能力、本地化场景理解与全产业链协同优势，中国品牌正不断拓展产业边界，成为全球家电与消费电子领域新质生产力的关键载体，在新品类的竞争格局中日益占据主导地位。

IDC中国高级分析师赵思泉认为，本届AWE以家电为主要切入口，实际上是消费电子企业展示AI能力的集中亮相，更是在家庭框架下对未来生活方式的一轮预演。以家电 AI 化 为核心，通过深度语义理解、用户行为自主学习及长期记忆能力，新一代智能家居系统能够持续沉淀用户操作、场景偏好与使用习惯数据，并不断迭代形成专属用户模型。在此基础上，家庭设备可突破单一指令响应模式，实现跨场景、多设备的智能协同与需求预判，提供更贴合生活节奏的个性化自动化服务，推动家电从被动执行工具升级为具备理解、学习与适配能力的智慧家庭中枢。

延伸阅读与沟通：

如需了解更多IDC相关研究或进一步与我们沟通，欢迎识别二维码与 IDC 联系，我们将安排专人与您对接，为您提供定制化的市场洞察与咨询服务。


如需了解IDC在智能终端领域的最新研究报告、数据产品及行业分析，请扫描二维码，在线获取完整研究目录与内容简介，助您精准把握市场脉动。

Claire Zhao - Senior Market Analyst - IDC

Claire Zhao is senior market analyst for Client System Research of IDC China. She is responsible for conducting research on the augmented reality (AR)/virtual reality (VR) market, and vertical analysis for the PC market. She started working for IDC China as a summer intern in 2019 as part of the Telecommunication group. Prior to joining IDC, Claire did some internships in the banking and insurance industries, and had some research experiences related to risk management, financial market, and data analytics. Claire graduated from Rensselaer Polytechnic Institute with a master’s degree in Financial Mathematics.

2026 年 3 月，“算电协同” 首次被写入《政府工作报告》，标志着算力与电力系统的深度融合正式上升至国家战略层面。当前全球 AI 产业竞争正从技术赛点转向成本赛点，这一战略落地不仅能化解算力快速增长与能源供给之间的结构性矛盾，更可依托 AI Token 跨境服务输出带动电力资源数字化出口，推动我国算力竞争迈入电力系统调度与协调能力比拼的全新阶段，为数字经济出口打造新增长极。

战略落地：政策沉淀与能源转型的必然结果

算电协同升级为国家战略，是长期政策铺垫与内需驱动的必然结果。早在 2023 年 12 月，“算电协同” 概念首次出现在《关于深入实施 “东数西算” 工程加快构建全国一体化算力网的实施意见》中；2024 年，国家发改委、能源局等部门在《加快构建新型电力系统行动方案（2024—2027 年）》中，为算电协同配套项目制定了具体实施纲领，其推进节奏与我国新型电力系统建设、能源转型的时间线高度契合。

从能源供给端来看，2025 年底我国风电光伏装机占比达 47.3%，首次超过煤电；非化石能源发电量占比升至 42.9%，风光新增发电量占全社会新增用电量的 97.1%，新能源已成为用电增量的核心供给主体。但现阶段能源与算力布局仍存在明显矛盾：一方面存在结构性、时段性供电紧张的时间错配问题，另一方面是东部算力需求旺盛但绿电资源稀缺，西部绿电富集但算力需求不足的空间错配问题。算电协同不仅是解决时空错配的抓手，更承担着推动区域协调发展、保障国家算力安全、完善新型电力系统、落地 “双碳” 目标的多重使命，其核心是将我国电力系统的产业优势转化为数字经济的竞争优势。

全球竞争：算力竞争的终局是电力系统综合实力的较量

全球 AI 产业规模化落地，推动算力需求呈指数级增长，算力消耗与电力供给的强绑定成为行业发展的核心特征。IDC 数据显示，2023-2028 年全球智能算力五年复合增长率达 46.2%，2025 年我国智算规模达 1037.3EFLOPS，同比增长 43%，这背后是 AI 大模型训练与推理规模化落地带来的算力需求爆发。算力需求的快速攀升直接推高电力消耗，2025 年我国 AI 数据中心 IT 能耗预计达 77.7 太瓦时，2027 年将增至 146.2 太瓦时，五年实现 6 倍增长，电力供给端的压力持续加大。

全球 AI 产业竞争已出现阶段变化，上半场竞争聚焦芯片等核心技术突破，下半场则转向电力系统综合实力的较量，成本竞争趋势显现：低成本、稳定且绿色的电力供给是核心竞争力。

模式创新：AI Token 开创电力出口新模式

算电协同将继续推动我国电力出口模式转型。通过 “电力转化为算力、算力生成 Token”，实现电力资源的数字化跨境服务输出。与 2000 年后我国电子家电、智能手机、新能源汽车等实体商品出口不同，AI Token 属于数字服务贸易范畴，依托 API 电子传输实现跨境交付，且受 WTO 电子传输关税豁免规则保护，形成了数字经济领域的 “免税高速公路”，降低了跨境服务输出的成本与壁垒。

当前全球 AI Token 产业竞争呈现明显的层级特征，表层是 AI 模型技术的比拼，中层是算力服务能力的竞争，而底层则是电力体系综合实力的较量。在全球 AI Token 竞争中中国拥有四大核心优势：

1. 电力规模优势：2025 年全国用电量突破 10 万亿千瓦时，电力供给能力稳居全球前列；

2. 成本优势：中西部地区拥有丰富的低成本绿电资源；

3. 布局优势：“东数西算” 与 “算电协同” 双战略加持下，我国算力布局与能源布局的协同性提升；

4. 技术优势：我国 AI 模型性价比高、开源生态强大，为算力服务与 AI Token 产业提供有力支撑。

未来方向：电力和算力的双螺旋演进

未来，算电协同发展将聚焦三大核心方向——推动实现电力服务算力、算力反哺电力的双向赋能、提升能源与算力资源的配置效率。

1. 持续推进 “算力跟着电走”，推动算力设施向绿电资源集中区域集聚，最大化利用低成本绿电；2. 推动算力错峰用电落地，将非实时性算力任务合理安排在电力低谷时段；

3. 推动算力成为电网可调节资源，助力电网实现削峰填谷，提升电网运行的稳定性。

产业机遇：算电协同背景下，IT 供应商迎市场新空间

算电协同战略落地为 IT 技术供应商打开了新市场空间，IDC认为有四个机会窗口：

1. 算力电力协同调度系统开发需求爆发，全国一体化算力监测调度、源网荷储一体化管控等场景，亟需能实现算力负荷与电力供应动态匹配的智能调度平台；

2. 绿色算力基础设施技术升级需求凸显，液冷温控、高密度供电、低 PUE 数据中心改造等技术成为算力设施建设标配，绿电直连配套的数字化适配技术也迎来蓝海市场；

3. 跨域融合技术服务空间广阔，算力枢纽与新能源基地协同布局背景下，数字孪生、AI 能效优化、跨境算力服务 API 搭建等技术服务需求快速增长；

4. 中西部算力基建配套市场持续扩容，“算力跟着电走” 的布局思路下，中西部新能源富集区的算力集群建设，将带来服务器部署、算力网络搭建、边缘计算节点建设等大量项目机会。

IDC 认为，未来全球算力竞争不再局限于规模比拼，而是转向算力、电网、储能、调度的系统能力综合较量。算电协同作为我国新型基建的重要组成部分，其深度推进不仅能推动新能源高效消纳、降低数据中心运营成本、提升我国 AI 产业全球竞争力，更能优化电网资源配置、稳定居民用电成本、推动绿色 AI 服务普惠化。而以 AI Token 为纽带的电力数字化出口，也将成为我国数字经济出口的全新增长极。对于 IT 技术供应商而言，当前正处于算电协同领域的市场窗口期，企业需紧密关注国家及地方政策导向，积极融入行业生态，与电力运营商、发电集团、电力设备商、综合能源服务商等主体深化合作，才能把握产业发展机遇。

IDC相关研究报告：《IDC Perspective 电力算力协同发展趋势预测与市场研判，2025》（Doc#CHC52926825）

算电协同正在成为数字基础设施与能源体系深度融合的重要方向，也将重塑全球算力产业的竞争格局。围绕这一趋势，IDC已在算力基础设施、数据中心能源管理、电力数字化以及绿色算力发展等领域持续开展研究。未来，IDC将持续发布相关研究成果与产业洞察，深入解读算电协同的发展趋势与市场机遇，欢迎持续关注IDC在数字能源与算力产业领域的最新研究与观点。

如需进一步了解与研究相关内容或咨询 IDC其他相关研究，请点击此处与我们联系。

当类OpenClaw的应用迈向规模化部署阶段，安全不再是可选附加，而是支撑其全域落地与长效运行的先决条件。

OpenClaw龙虾爆火全球，区别于以往的AI助手、聊天机器人或智能体，OpenClaw具备长期记忆能力，在本地运行，可以主动通过用户偏好的现有消息应用向用户发送消息并在后台持续运行，受到了全球用户的广泛关注并引发安装潮。对于企业来说，OpenClaw的潜力更大。理论上，OpenClaw可以查看用户的日历、阅读会议记录，并持续关注正在进行的项目。与传统需要用户主动提问或提示的方式不同，OpenClaw会主动通过消息应用如Microsoft Teams、微信、飞书、钉钉等联系用户，它还可以执行诸如浏览网页、撰写和发送邮件、编写代码、创建新agent以实现目标等操作。用户可以通过包括手机和笔记本电脑在内的多种设备与其交互。这类持续在后台运行、能够检测趋势、异常和机会的环境型agent，对知识型员工来说极具价值。它代表了一种新层次智能助手理念——不再需要人类先设想可能性并指示助手执行，而是助手能够主动确定下一步行动并识别新机会。这类能力与高度自主性息息相关，意味着助手在实现目标时可能表现出异常强大的资源整合能力，这既带来了益处，也会大幅扩大威胁暴露面，“裸奔”的小龙虾会造成巨大的安全风险，给个人、企业带来难以挽回的巨大损失。

具体来说，OpenClaw可以执行Shell/Python、访问本地文件、调用API、安装社区Skills等，这些能力会带来巨大的安全风险，IDC总结了其存在的一些安全：

  • 公网暴露+弱认证风险：OpenClaw默认端口（18789/19890）常被设为 0.0.0.0 全网监听，全球超23万个实力裸奔，攻击者不需要密码、不需要权限、不需要确认即可连接OpenClaw服务，获得权限，进行未授权访问和远程代码执行，对主机进行完全控制，是超高危风险。
  • Skill供应链风险：ClawGuard发现36.8%的ClawHub Skills存在安全问题，至少76个Skills含恶意代码，攻击者可以一次发布多个恶意Skills，用户在安装Skills时面临重大安全风险。2026年2月，ClawHacvoc大规模恶意Skills投毒，一旦用户执行恶意安装步骤，攻击者便可获取 SSH 密钥、浏览器密码、加密货币钱包私钥、云服务 API 密钥等敏感数据，或在用户设备上植入远程控制程序（RAT），实现完全系统接管。
  • Agent权限失控风险：OpenClaw 可以做Shell执行、文件访问等高权限动作，可以读写全盘、执行任意命令。当Agent做出如删文件、格式化的高危动作时，无二次确认将带来不可挽回的损失。2026 年 2 月，Meta 安全专家在测试OpenClaw 时，因 AI 处理大量邮件时遗忘 “未经确认不得操作” 的安全约束，批量删除其 200 多封工作邮件，专家只能通过强制关机物理止损。
  • 提示注入风险：攻击者可以在skills、网页、邮件、工具中嵌入恶意指令，诱导Agent执行高危操作。
  • 敏感信息明文存储：OpenClaw 将 API Key、账号凭证及会话数据明文保存在本地目录，已被主流窃密木马列为重点窃取目标，存在高风险的数据泄露隐患。
  • 高危漏洞频发：OpenClaw持续暴露高危安全漏洞，攻击者可利用这些漏洞实现远程控制或系统接管，严重威胁运行环境安全。国家信息安全漏洞库（CNNVD）发布通报，2026年1月到3月9日，共采集到82个OpenClaw漏洞，存在极大的安全隐患。

无论是个人还是企业部署类似OpenClaw的工具时，需要采取严格的安全和治理措施，IDC建议组织可以从以下几点入手进行检测和防护：

  • 网络隔离：网关绑定 127.0.0.1 ，关闭默认端口，禁止公网暴露；远程用SSH隧道/VPN/零信任，配IP白名单+强密码+MFA；防火墙阻断外部入站，仅内网/堡垒机访问。
  • 最小化权限：用普通用户启动，禁用root/管理员权限；仅开放必要文件路径，禁用删除/格式化等高危命令；关键操作强制二次确认等。
  • Skills供应链安全管控：Skills供应链扫描、安装前代码审计等。
  • 数据与凭证安全：开启数据加密，禁止明文存密钥/密码；定期更换API密钥，用密钥管理服务/环境变量注入；清理本地缓存与日志，避免敏感信息残留等；
  • 漏洞与监控：开启自动更新；开启操作日志，异常实时告警；定期用官方工具自查绑定地址、认证状态。

目前，中国众多大模型厂商陆续推出了免费版类OpenClaw智能体，积极抢占新的用户端入口。伴随类OpenClaw智能体部署节奏的加快，AI云厂、网络安全厂商以及AI安全创新型企业快速推出了OpenClaw安全风险分析与防护解决方案和 “安全小龙虾” ，帮助用户安全地使用OpenClaw。为了更好地帮助用户了解大模型安全、智能体安全的市场格局并帮助其做技术选型，IDC正式发布《IDC MarketGlance：中国大模型安全，2026Q1》（Doc#CHC53617026），市场格局详见下图：

与此同时，大模型、智能体的安全检测与防护也少不了AI的赋能即安全智能体的加持。当前众多技术服务提供商已经将安全智能体和智能体集群的能力集成到其安全解决方案中，帮助用户提质增效，用AI对抗AI、AI防护AI将成为未来大模型安全、智能体安全防护的一个重要思路与能力。IDC同期发布《IDC MarketGlance：中国安全智能体，2026Q1》（Doc#CHC53597826），希望通过IDC对于中国市场中安全智能体产品的调研来帮助用户充分地了解安全智能体相关技术的发展和市场格局，详见下图：

IDC《全球CIO议程2026年预测——中国启示》报告预测，到2030年，中国500强企业中15%的组织将因对AI智能体的管控与治理不足，引发高关注度的运营中断，进而面临诉讼、高额罚款及CIO被解雇的情况。企业管理者亟需构建一套智能体安全和治理体系来帮助企业安全地用好智能体，规避安全风险。

为了更好地帮助用户了解智能体安全检测和防护如何入手，IDC正式启动《IDC Perspective：OpenClaw安全防护解决方案市场洞察，2026》报告、《IDC Perspective：中国智能体身份与访问控制解决方案市场洞察，2026》报告研究，欢迎大家与我们保持沟通交流，与IDC共同开展更多前瞻性与实践性研究。

IDC更多相关研究

IDC已于2026年启动AI安全技术系列研究，围绕AI原生安全架构、安全智能体成熟度评估、AI驱动DevSecOps实践路径及企业级AI治理框架展开深入分析。

如需进一步了解与研究相关内容或咨询 IDC其他相关研究，请点击此处与我们联系。

Sophia Wang - Research Manager - IDC

Sophia Wang is a Research Manager in IDC China. She is responsible for the analysis and research of China's cybersecurity market. Her primary focus is on China's cybersecurity appliance and services market and operational technology (OT) security market. Additionally, she provides related research and consulting services for regional and global IT customers and supports their business development. Prior to joining IDC, Sophia worked in several consulting companies. She was independently responsible for consulting projects in fast-moving consumer goods (FMCG), internet, and other industries. Through market analysis and benchmarking analysis, she helped many clients solve problems in the different stages of their development. Sophia graduated from the University of Southern California with a master's degree in econometrics. She also majored in human resource management and journalism for her bachelor's degree.

AI-driven infrastructure demand is accelerating investment in datacenter networking, reshaping the Ethernet switch market.

The datacenter portion of the Ethernet switch market continued its strong growth in the fourth quarter of 2025 (4Q25), rising 63.0% year over year (YoY) to reach $9.9 billion, driven by the build-out of datacenter network infrastructure to support AI workloads.

The total Ethernet switch market, inclusive of both datacenter and non-datacenter segments, grew 35.1% YoY to reach $16.2B in 4Q25. For the full year, revenue totaled $55.1 billion, up 31.5% YoY.

Ethernet switch market highlights

  • Datacenter segment: The datacenter portion of the Ethernet switch market saw exceptional growth in 2025, with full-year growth of 53.5% YoY to reach $32.5B. High-speed datacenter switches (800G) accounted for 25.8% of 4Q25 revenues and 16.4% of full-year revenues, while 200Gb/400Gb speeds represented 43.9% of yearly revenue—reflecting rapid adoption of higher-speed networking to support AI workloads.
  • Non-datacenter segment: Ethernet switches used in enterprise campus and branch networks grew 6.4% YoY in 4Q25 and 9.1% for the full year, reflecting steady investment in enterprise infrastructure.
  • Regional performance: Ethernet switch revenues grew in all regions of the world in both 4Q25 and the full year. The Americas led with 45.4% YoY growth in 4Q25 and 40.2% for the year. EMEA posted 28.3% growth in 4Q25 and 23.1% for the year, while Asia Pacific saw 23.3% growth in 4Q25 and 23.5% for the year.

Router market highlights

The total router market, inclusive of both service provider and enterprise segments, rose 11.5% YoY in 4Q25 and increased 11.2% for the full year 2025 to reach $15.0B.

  • Service provider segment: The service provider segment (including communications and cloud SPs) made up 74.4% of total router market revenues in 4Q25 and increased 12.8% YoY.
  • Enterprise segment: The enterprise router market makes up the balance of revenues and grew 7.5% YoY in 4Q25, reflecting ongoing investment in enterprise wide area networking (WAN) connectivity.
  • Regional performance: In 4Q25, the Americas router market rose 15.9% YoY, EMEA increased 16.2%, and APJ grew 3.8%.

Vendor highlights

Vendor performance reflects the shift toward AI-driven datacenter demand.

  • Cisco: Cisco’s total Ethernet switch revenues increased 13.5% YoY in 4Q25 to $4.5 billion, capturing 27.6% market share. Non-datacenter segment revenues (63.9% of Cisco’s total) grew 7.5% YoY, while datacenter segment revenues rose 26.0% YoY. Cisco’s total router revenue increased 22.5% YoY, giving the company a 30.6% market share.
  • Arista Networks: With 92.6% of its Ethernet switch revenues in the datacenter segment, Arista’s revenues grew 31.4% YoY in 4Q25 to $2.0 billion. Arista holds a 12.6% share of the total Ethernet switch market and 19% in the datacenter segment.
  • Huawei: Huawei’s total Ethernet switch revenue increased 14.0% YoY in 4Q25 to $1.7 billion, giving the company a market share of 10.6%. Huawei’s router revenue increased 6.5% in 4Q25, giving the company a 30.2% market share.
  • NVIDIA: NVIDIA’s Ethernet switch revenues, entirely from the datacenter segment, surged 192.6% YoY to $1.5 billion in 4Q25, giving it a 15.2% share of the datacenter segment.
  • HPE: HPE’s total Ethernet switch revenue (66.8% from non-datacenter) increased 11.7% YoY in 4Q25, reaching a 6.7% market share. Following the July 2025 acquisition, HPE revenues now also include Juniper.

Market dynamics

  • Demand for speed and low latency: Organizations are investing in higher-speed switches to support AI-driven and other demanding workloads, fueling growth in datacenter and high-speed segments.
  • AI workloads: The proliferation of AI applications is pushing enterprises to upgrade their networks for both bandwidth and latency improvements.
  • Global uncertainty (constraint): While macroeconomic and geopolitical uncertainty persists, it has not significantly dampened investment in critical network infrastructure.

“The 4Q25 results highlight the scale of the AI-driven boom in datacenter networking. Hyperscalers, cloud providers, and increasingly enterprises are turning the datacenter network into critical infrastructure, driving strong demand for high-speed Ethernet switching.” — Brandon Butler, Senior Research Manager, Network Infrastructure and Services, IDC

Why it maters

  • Who should care? CIOs, network architects, IT buyers, and technology vendors should note this acceleration, as it signals a renewed investment cycle in network infrastructure.
  • Business impact: Upgrading to more reliable and faster networks enables more responsive applications, enhances employee and customer experiences, and supports faster decision-making platforms.
  • Ecosystem signal: The market’s robust growth highlights the strategic importance of network modernization, especially as organizations deploy AI and data-intensive applications.

What’s next for the Ethernet switch market

IDC expects continued momentum in the Ethernet switch market as enterprises prioritize network modernization to support AI, cloud, and real-time applications. Growth could accelerate further as AI investments increase, particularly in datacenter AI factories and as more inferencing use cases emerge. However, new supply chain concerns around memory and persistent global uncertainty are headwinds. Watch for ongoing investments in datacenter upgrades and higher-speed switch deployments in the coming quarters.

For deeper analysis, see the IDC Quarterly Ethernet Switch Tracker and IDC Quarterly Router Tracker.

Brandon Butler - Sr. Research Manager - IDC

Analyst Profile
Brandon Butler is a Senior Research Manager with IDC's Network Infrastructure group covering Enterprise Networks. His research focuses on market and technology trends, forecasts and competitive analysis in enterprise campus and branch networks. His coverage includes technologies used in local and wide area networking such as Ethernet switching, routing/SD-WAN, wireless LAN, and enterprise network management platforms. While contributing to ongoing forecast and market share updates, he also assists in end-user surveys, interviews and advisory services and contributes to custom projects for IDC's Consulting and Go-To-Market Services practices.

Petr Jirovsky - Senior Research Director, Network Infrastructure and Services - IDC

Analyst Profile LinkedIn
Petr Jirovsky is a Senior Research Director within IDC's Enterprise Infrastructure global research domain. He provides quantitative insights on network infrastructure for the datacenter, cloud, and campus/branch environments as part of the Network Infrastructure and Services subdomain. Petr serves as the global lead for IDC's Network Infrastructure Trackers, which track Ethernet switches, routers, wireless equipment, and application delivery appliances and services. He also contributes to numerous custom data projects and supports the publication of market share and forecast documents for the subdomain.

Diego Anesini - VP D&A, LatAm & Director Enterprise and Telecom - IDC

Analyst Profile LinkedIn
Diego Anesini serves as Research Vice-President, Data & Analytics for IDC Latin America, overseeing all the Information and Communications Technologies. Prior to this position, Diego held various roles in the company. The most recent was Enterprise Infrastructure and Telecom Director for Latin America. He has extensive experience in the Telecom and IT markets, due to his more than 25 years in the industry.

OpenAI’s failed attempt to scale “pay in chat” revealed deeper structural constraints: it can neither be a commerce platform nor operate effectively as a middleman. To be a true commerce platform, it would need to build a Shopify-like ecosystem. Even if Codex could build something in a few months, it would take years to accumulate the millions of product listings, merchant relationships, transaction histories, pricing dynamics, fulfillment systems, and customer journey data required.

OpenAI must also contend with the fact that commerce platforms can easily implement their own AI interfaces, as many already are (Alibaba Accio, Amazon Agent Mode, Walmart AI, etc.). AI is merely a new front door. If OpenAI wants to become a true agentic commerce platform, it must own or control one or more of three strategic assets:

  1. The Commerce Graph (inventory, sellers, transactions)
  2. The Customer Graph (identity, purchase behavior, lifecycle data)
  3. The Product Data Graph (high-frequency usage and intent signals)

Let’s look at some potential acquisition candidates that could revive OpenAI’s agentic commerce ambitions based on strategic fit and financial feasibility.

Strategic fit criteria

  • Strength of proprietary data moat
  • Control over demand and transaction layer
  • Monetization leverage
  • Ability to reduce platform dependency.

Financial feasibility criteria

  • Approximate market capitalization
  • Acquisition realism given OpenAI’s capital structure.
  • Financing complexity
  • Regulatory and integration risk
CandidateStrategic
Impact		Financial
Feasibility		Overall
Assessment
KlaviyoHighHighOwn the customer graph
InstacartHighModerateFast cycle replenishment
EtsyModerateModerateSecondary Marketplace
BigCommerceModerateVery HighOwn the product data pipes
Cart.comLow-ModerateHighFulfillment and commerce infrastructure

Other candidates such as eBay, Shopify, Mercari are considered too big for OpenAI to acquire.

The case for Klaviyo

Own the Customer Graph

Klaviyo is a commerce customer data and lifecycle marketing platform serving 193,000+ merchants globally. It doesn’t own a marketplace it owns the customer identity layer across marketplaces. It processes billions of behavioral events, including email engagement, SMS interactions, purchase conversions, cart abandonment, and repeat buying patterns.

In its most recent fiscal year, Klaviyo delivered approximately 32% revenue growth, expanding margins, and strong free cash flow. It supports thousands of midmarket and enterprise brands and maintains net revenue retention above 109%, reflecting deep embedding in merchant workflows.

Primary value to OpenAI:

  • Deep behavioral identity graph: Access to engagement and purchase data across hundreds of thousands of merchants.
  • High-margin SaaS monetization: Recurring revenue aligned with merchant performance and retention.
  • AI-powered personalization engine: Enables OpenAI to embed agents directly into lifecycle marketing and conversion optimization workflows.

The case for Instacart

Own Fast Cycle Replenishment

Instacart is North America’s leading grocery delivery and retail media platform, partnering with 100,000+ retail locations and serving 26+ million active customers. In 2025, it processed approximately 338 million orders, generating over $37 billion in gross transaction value (GTV).

Grocery is high-frequency commerce—weekly or biweekly—creating repeated behavioral loops rarely found in discretionary retail. Instacart also operates a growing retail media business tightly integrated with shopper behavior.

Primary value to OpenAI:

  • High-frequency purchase data: Recurring basket-level signals ideal for agent habit formation.
  • Localized real-time inventory: Enables agents to optimize decisions across substitution, delivery speed, and pricing.
  • Integrated retail media monetization: Advertising revenue directly tied to purchase behavior.

The case for Etsy

Own the marketplace

Etsy operates a global marketplace focused on handmade, vintage, and specialty goods, with 100+ million active listings, 8+ million sellers, and approximately 96 million active buyers. In 2024, Etsy generated more than $12.6 billion in gross merchandise sales.

Its experience is driven by discovery rather than price, emphasizing personalization, gifting, and niche communities.

Primary value to OpenAI:

  • High-signal preference data: Deep insights into taste, gifting, and niche category behavior.
  • 2nd tier marketplace: Large enough to matter, less complex than dominant incumbents.
  • Discovery-optimized commerce: AI agents could materially improve search and recommendation quality.

The case for BigCommerce (Feedonomics)

Own the product data pipes

BigCommerce powers over 130,000 merchants across 150+ countries, generating roughly $350 million in ARR. Feedonomics provides structured product data feeds to major marketplaces (Amazon, Google, TikTok) and ad channels.

It is particularly strong in B2B commerce, where early agentic commerce value is emerging.

Primary value to OpenAI:

  • Structured product feed layer: Clean SKU, pricing, and catalog normalization critical for AI accuracy.
  • B2B commerce exposure: Early advantage in high-margin procurement automation.
  • Ecosystem leverage: Influence over product data standards feeding major marketplaces.

The case of Cart.com

Fulfillment and commerce infrastructure

Cart.com provides end-to-end commerce services, including storefronts, analytics, warehousing, and fulfillment. It has raised over $380 million and expanded through acquisitions to build a distributed logistics network.

Its platform captures operational data such as inventory velocity, shipping performance, and fulfillment timelines—data typically unavailable to discovery-layer platforms.

Primary value to OpenAI:

  • Operational telemetry: Real-world delivery and inventory data to inform agent optimization.
  • Discovery to delivery: Enables AI to reason about fulfillment constraints.
  • Multi-channel insight: Visibility across marketplaces and merchant storefronts.

OpenAI would have to buy several of these companies, top three Klaviyo (customer graph), BigCommerce (data pipes), and Instacart (fast cycle replenishment). Cart.com adds operational telemetry but is most valuable after OpenAI has control of demand and identity. Without the customer graph and habit loop, fulfillment intelligence is secondary. Etsy is a large secondary global marketplace, but Instacart delivers a marketplace and faster cycle replenishment buying activity.

Acquisitions would radically change the monetization potential of OpenAI’s commercial business. New revenue streams from AI SaaS (Klaviyo), transactions and retail media (Instacart), merchant services (BigCommerce), in addition to their enterprise contracting and consumer subscriptions. These acquisitions would make a powerful strategic statement, legitimize OpenAI’s vision of being the default interface to commerce (or at least being competitive as such), and radically rebrand the company as the AI OS for commerce.

Who owns the personal shopper?

Assuming the industry resolves the operational challenges of agentic commerce, the key question becomes: who owns the consumer interface? Consumers will likely default to a single personal shopper agent that interacts across brands and marketplaces.

OpenAI is a strong interface but has structural vulnerabilities. At best, it is a third-party app unless it secures exclusive distribution with a major device manufacturer. Even then, marketplace operators can control and meter third-party agent access—pushing OpenAI back into a margin squeeze.

More critically, platform-native competitors are emerging. A Gemini-powered Siri deployed across billions of Apple devices could be extremely difficult to displace. If OpenAI cannot effectively monetize commerce or advertising, it will depend on enterprise and consumer subscriptions—yet consumers will gravitate toward the lowest-friction interface.

Gerry Murray - Research Director, Marketing and Sales Technology - IDC

Analyst Profile
Gerry Murray is a Research Director with IDC's Marketing and Sales Technology service where he covers marketing technology and related solutions. He produces competitive assessments, market forecasts, innovator reports, maturity models, case studies, and thought leadership research. Prior to his role at IDC, Gerry spent six years in marketing at Softrax Corp. an enterprise financial solutions provider. There, he managed marketing programs that produced 4 million emails a year, multiple websites, interactive tools and product tours, an online game, collateral, and PR. Concurrently, he was Managing Editor at RevenueRecognition.com, a thought leadership site featuring partnerships with IDC and the Financial Accounting Standards Boards (FASB) which was quoted and referenced in leading industry publications such as CFO magazine, BusinessFinance, and others. Gerry spent the first half of his career at IDC advising executives from some of the world's largest software and services providers on market strategy, competitive positioning, and channel management. He was the Director of Knowledge Management Technology and conducted research on a worldwide scale including: market sizing and forecasting, ROI models, case studies, multi-client studies, focus groups, and custom consulting projects.