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Travelers and diners are no longer navigating journeys on their own. Increasingly, AI agents are doing it for them.

By 2026, hospitality, dining, and travel brands will operate in an environment where discovery, comparison, booking, and service are mediated by intelligent agents acting on behalf of guests. These agents will not just search, but they will evaluate options and apply preferences to find the best value and most appropriate offering. Ultimately agents will eventually even be able to complete bookings and orders to transact in real-time.  That shift fundamentally changes how guests will come to discover and interact with hospitality and travel brands, and if those guests will even need – or want – to interact directly with a brand.

IDC’s FutureScape: Worldwide Hospitality, Dining, and Travel 2026 Predictions show that agentic AI is fundamentally changing the distribution “funnel.” This will reshape how brands compete, forcing a rethinking of data strategies, personalization, and even how brands are “found” in the first place.

From channels to agents: The new front door to travel and hospitality

Historically, hospitality and travel brands optimized for channels. Search engines, online travel agencies, loyalty apps, third-party delivery platforms, and physical locations defined how guests found and engaged with them.

Agentic AI changes that model.

IDC predicts that by 2030, 30% of travel bookings will be executed by AI agents, accelerating investment in LLM optimization and increasing direct bookings and profitability

In this environment, the first interaction may never involve a human browsing a website. Instead, an AI agent will query multiple sources, assess availability and pricing, weigh preferences, and complete the booking autonomously.

For hotels, airlines, and restaurants, this means one thing: if your data is incomplete, outdated, or fragmented, you effectively disappear from the agent’s decision set.

Agent-led search requires brands to rethink discoverability. It is no longer enough to rank well for keywords. Brands must ensure that large language models and agents can accurately understand what they offer, when it is available, and why it is relevant to a specific traveler or diner at any given moment.

Guest-centricity starts with a 360-degree data foundation

At the heart of this transformation is data. Not necessarily more data, but easier access to connected insights, so brands can quickly and easily analyze and take action to provide truly memorable and meaningful experiences.

IDC forecasts that by 2030, 50% of AI budgets in hospitality and travel will be allocated to personalization efforts, powering ambient intelligence and preference anticipation to increase guest satisfaction by 25%.

Achieving that level of personalization requires a unified, real-time view of the organization and the guest.

For hotels, this means connecting property management systems, loyalty programs, guest profiles, and on-property interactions into a single, actionable data fabric. For airlines, it means aligning inventory, pricing, operations, and customer history to anticipate needs from seat selection to disruption recovery. For restaurants, it means synchronizing menus, pricing, availability, and customer preferences across in-store, delivery, and digital channels.

Without this 360-degree view, agentic AI cannot deliver on its promise. Fragmented data leads to generic offers, broken experiences, and missed revenue opportunities. Unified data enables brands to move from reactive service to proactive engagement, recognizing guests and diners across every touchpoint.

Personalization becomes continuous, not campaign-based

In an agentic world, personalization is no longer a marketing tactic. It becomes an operating model and first-party data will be a secret sauce to ensure that brands don’t lose control of their guests to LLMs.

Agents will continuously interpret intent, context, and constraints. A traveler’s preferences, budget sensitivity, loyalty status, dietary needs, and timing constraints will all factor into decisions made in seconds. Brands that rely on static segments or periodic campaigns will struggle to keep up.

This is where ambient intelligence emerges. Personalization shifts from “what offer should we send?” to “how should the experience adapt right now?” Hotel rooms that can be adjusted to known preferences upon arrival. A restaurant that surfaces menu recommendations aligned to past behavior and real-time inventory. An airline that proactively rebooks a passenger before disruption becomes frustration.

These experiences depend on data that is current, trusted, and interoperable across systems.

Superapps, wallets, and the expansion of the digital guest journey

IDC also predicts that data modernization, security, and AI investments will increase by 65% as hospitality and travel organizations respond to demand for digital wallet–driven superapps, with 25% of major brands deploying one by 2030.

Superapps extend the customer relationship beyond booking into payments, identity, loyalty, and in-trip engagement. When combined with agentic AI, they become powerful orchestration layers. An agent can manage payments, redeem loyalty benefits, confirm availability, and coordinate experiences across partners, all on behalf of the guest.

But again, this only works if the underlying data is accurate and synchronized. Out-of-date room availability, inconsistent menu information, or disconnected loyalty data can yield undesired results. Hotels, restaurants, or travel options may not be surfaced by agents at all or if they are based on erroneous information can erode guest experience and undermine trust when guests don’t receive the specific service they were expecting.

What This Means for Hospitality Leaders in 2026

The shift to agentic AI is not incremental, and therefore should not be viewed as one-off projects, but rather as an infrastructure on which to build strategy.

Hospitality, dining, and travel brands must act now to:

  • Modernize data architectures to support real-time, enterprise-wide visibility.
  • Ensure offerings, availability, and pricing are machine-readable and continuously updated.
  • Invest in personalization capabilities that operate across the full guest journey, not isolated moments.
  • Rethink discoverability for an agent-led search environment, where accuracy and context determine inclusion.

Guest-centricity in 2026 will go beyond loyalty points and SEO. It will be defined by how well a brand leans into its first-party data to enable intelligent agents to represent their brand in a light that aligns with guests’ interests seamlessly, accurately, and at scale.

The brands that succeed will be those that treat data not as a back-office asset, but as the foundation of trust, personalization, and growth in an agent-driven economy.

Dorothy Creamer - Sr. Research Manager - IDC

Analyst Profile
Dorothy Creamer is Senior Research Manager for IDC Research, Hospitality & Travel Digital Transformation Strategies, providing research and advisory services for hotels, casinos, restaurants and travel organizations. Ms. Creamer's research will focus on how these business segments are transforming and leveraging technology to increase efficiencies, deliver operational benefits and identify new revenue streams. Ms. Creamer's research will report on effective digital strategies to empower both guests and employees and analysis of areas of opportunity in a fast-evolving and highly competitive segment.

For most CMOs, Q1 begins with a familiar reassurance: We’ll move fast. We’ll see what works. We can adjust.

That logic used to hold. But in 2026, it does not.

Q1 is no longer a learning quarter. It is the point where go-to-market direction begins to harden financially, operationally, and organizationally. By the time early results appear, budgets have already been deployed, teams aligned, and market narratives established. What feels flexible in January often becomes difficult to change by March.

That makes Q1 the most dangerous time of the year to be directionally wrong.

Commitment now happens earlier than most teams realize

In Q1, commitment accelerates faster than most teams expect.

Budgets move from plan to spend early in the quarter. Teams align around specific markets, messages, and motions. Enablement, content, and tooling go live. Leadership begins to form a point of view on what is working and where to double down.

Once that momentum builds, reversal becomes slow, expensive, and difficult to execute, even when later evidence points in a different direction. Direction often locks before performance data can meaningfully challenge it.

In previous years, this transition happened more gradually. Today, compressed buying cycles and pressure to show early momentum have shortened the window for reconsideration.

Directional risk outweighs execution risk in Q1

When Q1 underperforms, reviews often focus on execution. Messaging missed the mark. Campaigns ramped too slowly. Sales conversion lagged.

Those explanations miss the deeper issue.

The most damaging Q1 failures start with direction. Once a market is prioritized early in the year, everything organizes around that choice. Budget, headcount, content strategy, enablement, and leadership attention align behind it. When signs later point to underperformance, the cost of changing course extends beyond spend and into organizational friction.

Directional GTM risk occurs when early investment is committed to markets that lack buyer urgency at a time when internal alignment is hardest to unwind. In that environment, strong execution can still reinforce the wrong decision.

Pipeline arrives too late to protect early decisions

Many GTM plans still rely on pipeline as the primary validation mechanism. Teams launch, monitor early indicators, and plan to optimize based on what they see.

The limitation is timing.

Pipeline reflects reality only after investment, alignment, and momentum are already in motion. Early Q1 bets rarely fail loudly. They show up as steady but unremarkable performance that consumes budget while quietly limiting upside.

By the time pipeline confirms a mistake, recovery is no longer quick. The cost of change has already compounded.

Buyer behavior accelerates the cost of early mistakes

Buyer behavior has shifted in ways that further compress the margin for error.

B2B buyers now signal urgency digitally, often before vendors engage directly. Markets with active demand surface quickly. Markets that require education or reframing absorb spend without producing early signal.

This dynamic changes how Q1 investment behaves. Markets where buyer urgency already exists convert earlier. Markets without urgency require sustained spend before traction appears.

Early-year investment into the latter carries outsized risk. When urgency is absent, activity increases, but momentum does not.

Strong CMOs reduce risk by narrowing earlier

High-performing CMOs face the same uncertainty as everyone else. The difference is how they manage it.

They narrow focus earlier in the quarter. They pressure-test direction before scaling. They recognize that optionality decreases rapidly once execution is underway.

Rather than spreading investment across multiple attractive opportunities, they concentrate resources where buyer urgency is already visible and defensible. Early success is measured by signal quality, not volume. Clarity about what to delay is as important as clarity about what to accelerate.

In Q1, focus functions as a form of risk management.

The decision that shapes the rest of the year

As pressure builds to show early momentum, the most dangerous assumption leaders make is that there will be time to fix a wrong bet.

Q1 does not determine the entire year, but it sets the constraints under which the rest of the year operates. Early market choices shape where credibility accumulates, where teams invest effort, and where recovery remains possible.

In 2026, the most damaging Q1 GTM failure is committing to the wrong direction before market signals arrive. Once momentum builds, correction becomes increasingly costly.

The question is not whether teams can execute.

It is whether they are pointed in the right direction before execution begins.

Validate direction before momentum locks in

In a quarter where speed matters, confidence matters more.

IDC’s GTM Validation Brief helps marketing leaders pressure-test where to commit early in Q1 and where to wait. It uses buyer-side evidence and market signals to validate direction before budgets, teams, and narratives harden.

This approach is not about caution. It is about capital discipline. Early momentum should compound growth, not trap it in the wrong places.

Download the GTM Validation Brief to validate your Q1 GTM strategy before direction locks in.

Christina Cardoza - Content Marketing Manager - IDC

LinkedIn
Christina Cardoza is a Content Marketing Manager at IDC, where she specializes in brand content and social media strategy. With a background in journalism and editorial leadership, she has a proven ability to transform complex technology topics into clear, actionable insights.

Sustainability is no longer a side program or a reporting exercise. It is becoming an operational mandate.

Economic uncertainty, regulatory pressure, and accelerating AI adoption are converging to force a fundamental shift in how organizations approach environmental, social, and governance (ESG) goals. In IDC’s FutureScape: Worldwide Sustainability/ESG 2026 Predictions, we see sustainability moving decisively from strategy decks into day-to-day execution—powered by AI, embedded into core operations, and owned across the enterprise, not just by sustainability teams.

For business and technology leaders, the message is clear: ESG success over the next three to five years will depend less on ambition and more on operationalization.

Sustainability is becoming an execution discipline

For years, many organizations treated sustainability as a long-term aspiration. That is changing fast.

IDC predicts that by 2027, 80% of sustainability services engagements will focus primarily on operationalizing sustainability strategy, not defining it. This shift will drive demand for a new wave of IT and OT services that connect sustainability goals directly to systems, processes, and outcomes.

What this means in practice:

  • Sustainability targets will increasingly be translated into system requirements.
  • ESG initiatives will be measured by execution velocity and measurable impact.
  • Technology leaders will play a significant role in making sustainability real.

Sustainability is no longer about whether the strategy is sound. It is about whether the organization can execute it at scale.

AI turns ESG from reporting to real-time management

One of the most important changes in IDC’s Sustainability/ESG FutureScape is the role of AI.

By 2030, more than 65% of global enterprises will use agentic AI–driven ESG software to support sustainable sourcing, lowering Scope 3 emissions while improving efficiency and resilience across supply networks.

This signals a shift from periodic ESG reporting to continuous ESG management:

  • AI will ingest supplier, logistics, and operational data in near real time.
  • Sustainability risk will be modeled, predicted, and mitigated before it escalates.
  • ESG performance will increasingly influence procurement and sourcing decisions automatically.

In parallel, IDC expects that by 2027, at least 30% of enterprise sustainability-related AI use cases will focus on sustainability risk analytics and risk management, reinforcing ESG as a core risk discipline rather than a compliance afterthought.

For leaders, AI investments are becoming sustainability investments.

Manufacturing and data centers move to the front line

Operational sustainability will be most visible where energy and resource intensity are highest.

IDC predicts that by 2027, 40% of manufacturers will use AI-driven analytics and automation to optimize energy efficiency, reducing carbon emissions by as much as 30%. These gains will not come from incremental efficiency programs but from deeply integrated analytics tied to production systems.

Data centers are undergoing a similar reckoning. By 2028, 50% of data center decision-makers will prioritize investments in modular facilities, edge locations, efficient server and storage systems, and renewable energy infrastructure to meet rising demand sustainably.

Just as important is transparency. IDC forecasts that by late 2027, 80% of AI data centers will report resource consumption metrics such as water use and pollution, setting new expectations for environmental accountability and community impact.

Sustainability performance is becoming inseparable from infrastructure strategy.

Circular IT becomes a cost and trust advantage

Sustainability is also reshaping how organizations think about technology assets.

By 2028, 75% of enterprises will set formal IT asset circularity goals, with 90% of assets returned to the circular economy and 20% sourced as renewed equipment. IDC expects this to drive both cost savings and stronger vendor relationships.

This reflects a broader shift:

  • Sustainability initiatives are being justified through financial discipline.
  • Procurement teams are aligning ESG goals with cost optimization.
  • Vendors will increasingly be evaluated on their circularity capabilities.

Circularity is moving from a sustainability pledge to a commercial differentiator.

The role of the CSO expands—and connects to AI

As sustainability becomes operational, leadership models are evolving.

IDC predicts that by 2026, 60% of large organizations’ Chief Sustainability Officers (CSOs) will help drive AI deployment in procurement, scrutinizing supply chains end to end for social, environmental, and governance criteria.

This reflects a broader organizational change:

  • CSOs are becoming integrators across business, technology, and risk functions.
  • Sustainability leadership is increasingly data-driven and AI-enabled.
  • ESG accountability is moving closer to core decision-making.

The CSO of the future is not just a policy leader but a technology-enabled change agent.

What leaders should do now

IDC’s Sustainability/ESG FutureScape 2026 points to a narrow window for action. Organizations that wait for perfect clarity will fall behind those that start operationalizing now.

Key priorities for the next 12–24 months include:

  • Align sustainability goals with core operational and technology road maps.
  • Invest in AI-enabled ESG platforms that support continuous insight and action.
  • Embed sustainability metrics into procurement, manufacturing, and infrastructure decisions.
  • Treat ESG risk management as a strategic capability, not a compliance function.

The organizations that succeed will be those that move sustainability out of reports and into systems.

Turning insight into impact

Sustainability is entering a new phase—one defined by execution, accountability, and technology-enabled scale.

IDC’s FutureScape: Worldwide Sustainability/ESG 2026 Predictions show that ESG leaders will not win by talking louder about sustainability. They will win by building it into how their organizations operate, decide, and invest.

In an era of economic and regulatory crosscurrents, sustainability is no longer about signaling values. It is about delivering outcomes—with confidence.

Learn more: Explore the full IDC FutureScape: Worldwide Sustainability/ESG 2026 Predictions to understand how sustainability, AI, and operational transformation are converging—and what it means for your organization’s next move.

Bjoern Stengel - Sr. Manager, Data & Analytics - IDC

Analyst Profile
Bjoern Stengel is IDC's global sustainability research lead. His research focuses on how environmental, social, and governance (ESG) topics impact and shape business strategies and technology usage. He provides insights into market opportunities, adoption strategies, and use cases for sustainability-related technologies and services. Bjoern helps IDC's clients understand the impact of technology-enabled, sustainable transformation processes in the context of sustainable business strategies, operations, and products and services through research reports, news publications, and speaking engagements at industry events such as Climate Week NYC.

Asia/Pacific enterprises are entering a new era of cybersecurity defined by the convergence of human expertise, autonomous AI agents, and trust frameworks. IDC calls this the Cyber Trinity, a security model that integrates human judgment, autonomous AI agents, and embedded trust frameworks. Drawing on IDC FutureScape: Worldwide Security and Trust 2026 Predictions – Asia/Pacific Excluding Japan (Implications), this analysis examines how AI-driven SOCs, embedded AI governance, synthetic identity threats, sovereign AI requirements, and quantum-era risks are reshaping security strategies across the region.

As organizations accelerate toward AI-first operating models, security and trust are no longer reactive controls. They are now engineered, governed, and continuously validated capabilities that determine enterprise resilience, regulatory compliance, and long-term competitiveness.

Why security and trust are being redefined in Asia/Pacific

The security landscape in Asia Pacific excluding Japan (APeJ) is undergoing rapid change. IDC forecasts that total security spending in the region will reach US$39.5 Billion in 2026, growing at a 10% CAGR to US$52.4 billion by 2029. This growth reflects more than rising threat volumes. It signals a structural shift in how organizations must build and govern trust in an AI-driven world.

As enterprises adopt agentic AI, face fragmented regulatory requirements, and contend with sophisticated adversaries using AI-powered techniques, traditional security models are proving insufficient. Trust, once implicit, must now be engineered, governed, and continuously validated.

Five security and trust shifts shaping 2026

IDC’s analysis points to five major shifts that will define security and trust strategies across Asia/Pacific over the next 18–24 months.

1. Autonomous, AI-driven security operations

Security Operations Centers (SOCs) are evolving from human-centric environments to AI-augmented and increasingly autonomous operations. AI agents are deployed to triage alerts, reduce false positives, normalize incident response, and orchestrate remediation at machine speed. IDC’s Asia Pacific Security Study 2025 states that 39% of enterprises plan to apply AI/GenAI solutions in the next 12 months to optimize threat detection and analysis capabilities. This shift is essential as skills shortages and exploding telemetry volumes overwhelm traditional SOC models.

2. Embedded AI governance and sovereign AI requirements

Governments across Asia/Pacific are tightening controls on data usage and AI systems. Only 7% of enterprises are highly prepared in terms of GRC skills to support these new requirements, driving demand for privacy-by-design, compliance-by-design, and sovereign AI architectures Enterprises are reassessing cloud strategies, adopting retrieval-augmented generation (RAG), and exploring private compute environments to meet data residency and regulatory requirements while scaling AI responsibly.

3. Synthetic identity as a core trust threat

According to IDC’s 2025 Future Enterprise Resiliency & Spending (FERS) study, 49% of APeJ enterprises have paid at least US$10,000 in ransom due to ransomware breaches. Adversaries are using AI to create synthetic identities that blend real and fabricated data, undermining authentication systems across financial services, e-commerce, and government platforms. These attacks erode digital trust at scale, forcing organizations to modernize identity protection and adopt AI-powered anomaly detection to distinguish legitimate users from synthetic fraud.

4. Quantum readiness and cyber risk quantification

As quantum computing advances, enterprises are beginning to assess the long-term viability of existing cryptographic systems. Crypto-agility and quantum readiness are emerging as strategic imperatives. By 2028, IDC predicts that 20% of Asia’s top 2000 enterprises will engage cybersecurity professional services firms to conduct quantum risk assessments. The ability to quantify cyber risk in financial terms is also becoming a board-level requirement, shaping budgets, insurance strategies, and M&A decisions.

5. Dynamic playbooks and endpoint-level trust

Static security playbooks are giving way to dynamic, AI-generated response models that adapt in real time to evolving threats. 30% of enterprises will be prioritizing the expansion of its MDR capabilities across assets, endpoints and applications. The rise of deepfakes and AI-enabled deception is also accelerating demand for endpoint detection capabilities that balance privacy, performance, and resilience.

What Cyber Trinity means for enterprise leaders

Together, these shifts signal a fundamental change: security and trust are no longer reactive controls. They are strategic foundations for innovation. Organizations that succeed will be those that can:

  • Balance human oversight with autonomous AI decision-making
  • Embed governance directly into AI and security architectures
  • Treat trust as a measurable, managed asset
  • Anticipate regulatory and technological disruption rather than respond after the fact

From Insight to Action

These themes form the foundation of IDC’s FutureScape 2026 Security & Trust Predictions for Asia/Pacific, which will be explored in depth by IDC analysts Sakshi Grover and Yih Khai Wong in an upcoming webinar. The discussion will focus on how organizations can architect, govern, and operationalize the Cyber Trinity to strengthen resilience and lead with confidence in an autonomous security landscape. Register now.

About the Authors

Sakshi Grover - Senior Research Manager - IDC

Analyst Profile
Sakshi Grover is a senior research manager for IDC Asia/Pacific Cybersecurity Services, supporting its research and client engagement activities across Asia/Pacific markets. Additionally, she serves as the lead security analyst for IDC India. Sakshi is responsible for delivering syndicated custom research and consulting engagements on next-generation emerging and disruptive technologies. Her tasks include developing and socializing IDC's point of view within security services, covering both legacy and modern cybersecurity technologies. Her role involves close collaboration with technology vendors and buyers, developing market insights, and providing research, consulting, and advisory services in the fields of security software and services. This includes partnering on research efforts with relevant country analysts in the local IDC offices. Sakshi's views on security have been quoted in numerous publications, such as the Economic Times, Business Standard, Data Quest, CRN, and others.

Yih Khai Wong - Senior Research Manager - IDC

Analyst Profile
Yih Khai Wong is a senior research manager for IDC Asia/Pacific's Cybersecurity practice, supporting cybersecurity research and client engagements through the Asia/Pacific Security Opportunities: Trust and Resilience program. Yih Khai's area of focus is on security technologies, including cloud-native application protection, identity, endpoint and network security. He works closely with technology vendors and buyers, delivering actionable market insights and advice within the cybersecurity ecosystem. Before rejoining IDC, Yih Khai was a principal analyst covering the cloud, datacenter, and edge computing market with ABI Research. Prior to that, Yih Khai was in EY, in his capacity as an assistant director at EY's research and insights group. Yih Khai started his analyst career with IDC Malaysia as an analyst covering the enterprise applications market.

一个正在发生的变化：软件不再只是“人写的”

在过去二十年里，软件工程的核心始终围绕“人如何写代码、交付系统”展开。即便进入 DevOps 时代，自动化更多也只是加快了既有流程。但 IDC 指出，随着 Agentic AI 的成熟，软件开发正在发生一次结构性转变：开发不再完全由人主导执行，而是由人类开发者与自主 AI 智能体协作完成。

在《IDC FutureScape：全球开发者和 DevOps 2026 年预测——中国启示》（Doc# CHC54059126

，2026年1月）中，IDC 明确提出：未来五年，Agentic AI 将深度嵌入从开发、测试到运维和安全的整个生命周期，迫使 DevOps 从“工具链升级”走向“运行模式重构”。

IDC 的核心洞察：DevOps 的问题，已经不只是效率

在中国市场，许多企业仍将 DevOps 视为提升交付速度、降低沟通成本的方法。但 IDC 认为，这种理解正在失效。
当 AI 智能体开始自动生成代码、执行测试、修复缺陷并参与决策，真正的挑战不再是“怎么用工具”，而是：

  • 谁来管理和监督智能体？
  • 如何保证 Agent 的行为可解释、可审计？
  • 人类开发者的角色将如何转型？
  • 企业是否具备规模化运行智能体的治理与平台能力？

这些问题，正是 FutureScape 2026 十大预测试图回答的核心。

十大预测：Agentic AI 将如何重塑开发者与 DevOps 生态

预测 1｜智能体开发采用

到 2028 年，面对智能体部署量增长 10 倍的局面，50% 的中国 1000 强企业将采用智能体开发生命周期，以实现企业级智能体 AI 的有效规模化落地。

这意味着，传统 SDLC 已不足以支撑智能体开发，企业必须引入专门面向 Agent 的开发与治理方法论。

预测 2｜多智能体编排

到 2029 年，多智能体编排的风险与复杂性将促使企业强化战略布局、扩充卓越中心（COE）资源，并将 AI 治理与监控工具的支出增加 30%。

当单一 Agent 变成 Agent 集群，治理与可见性将成为规模化落地的前提。

预测 3｜自主式智能体 AI 工作单元

到 2030 年，80% 的开发者将与自主 AI 智能体展开协作，推动人类开发者向规划、设计与编排角色转型，并重塑开发者工具生态系统。

开发者将不再只是“写代码的人”，而是“引导和监督智能体的人”。

预测 4｜氛围编程采用

到 2027 年，随着企业级能力的成熟，35% 的专业开发者将采用氛围编程开发平台构建生产级应用。

自然语言正在成为新的开发接口，但前提是企业级治理与质量控制能力同步成熟。

预测 5｜嵌入 DevOps 的智能体应用

到 2030 年，65% 的企业将把 AI 智能体嵌入 DevOps 和 DevSecOps 流水线，用于执行开发与安全工作流。

Agent 将成为流水线中的“常驻成员”，而非外部插件。

预测 6｜前沿模型采用

到 2027 年，在开发者偏好的驱动下，70% 的 AI 用例将仅由少数几个前沿模型提供支持。

模型选择正在从“多而杂”走向“少而精”。

预测 7｜智能体 AI 项目失败

到 2028 年，70% 的“自建型”智能体 AI 项目将因未能达成投资回报率目标而被放弃。

低估治理、运维和组织成本，是失败的主要原因。

预测 8｜AI 质量保障扩展

到 2028 年，AI 质量保障将推动智能体测试和跨应用生命周期管理的采用率至少提升 30%。

没有质量保障的 Agentic DevOps，无法进入生产核心。

预测 9｜AI 加速应用开发

到 2029 年，通过使用智能体 AI 软件开发工具，企业的应用开发与现代化迭代速度将提升 400%。

速度跃迁的前提，是平台化与治理并行。

预测 10｜开发者模型微调

到 2027 年，微调将取代检索增强生成（RAG）成为大语言模型改造的主流模式，这将推动开发者对开源权重模型的使用率提升 80%。

模型工程正在走向更深度的定制化。

分析师观点

IDC 中国研究经理王彦翔认为，开发者和 DevOps 正站在从“自动化时代”迈向“智能体时代”的关键门槛。FutureScape 2026 显示，真正拉开差距的，不是是否引入 AI 编码工具，而是企业是否具备平台工程、治理能力和开发者角色转型的整体规划。那些仅在局部场景试点智能体的组织，将很难释放规模化价值；而将 Agentic AI 作为企业级能力来建设的组织，更有可能在速度、质量和创新能力上形成长期优势。

一个面向技术与业务领导者的综合建议

IDC 并不建议企业急于“全面智能体化”。更重要的是，以 DevOps 为核心，系统性重构开发流程、平台能力与治理机制：建立智能体开发生命周期（ADLC）、强化多智能体编排与监控、同步推进开发者技能转型，并将 AI 治理嵌入每一个交付环节。


只有这样，Agentic AI 才能成为持续创新的引擎，而不是新的技术债务来源。

行动指南：企业可以从哪里开始？

  • 从 高价值、低风险的开发或运维场景 切入，验证 Agent 的实际收益
  • 建立 跨职能的 AI / Agent 卓越中心（COE），统一治理与平台策略
  • 投资 平台工程与 AI 质量保障，而不仅是开发工具
  • 提前规划 开发者角色与能力转型，为人机协作做好准备

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。

Bryan Wang - Senior Market Analyst - IDC

Bryan Wang is a senior market analyst for Cloud Computing in the Emerging Technology sector for IDC China. He focuses on research and analysis of China's cloud computing market, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SAAS). Bryan is also responsible for providing market analysis and research in relevant fields together with IDC's regional and global research teams. Before joining IDC, Bryan worked as a cloud computing solution architect for well-known manufacturers and systems integrators. He was mainly responsible for presales consulting, project design, industry insight, project management, and other work. He has rich experience and a profound understanding of the cloud computing field. Bryan graduated with a B.A. in Inorganic Nonmetallic Materials Engineering from Central South University.

企业连接，正在从“基础设施”演进为战略能力

在 AI 工作负载快速增长、业务连续性要求不断提高的背景下，企业连接已不再只是网络团队的技术议题，而正在成为影响 业务韧性、运营效率与创新速度 的核心能力。
IDC 认为，企业正在进入一个全新的连接阶段：连接不再只是“管道”，而是由 AI 驱动编排、可感知并持续演进的数字底座。

为什么这份 FutureScape，对企业连接战略具有参考价值?

在《IDC FutureScape：全球企业连接2026年预测——中国启示》（Doc#CHC52329725，2025年12月）中，IDC 指出，随着 AI、Agentic AI 与边缘计算深度融入企业运营，连接能力正在被重新定义。
企业对连接的期望，已从“稳定可用”升级为 敏捷、自治、安全、面向 AI 的能力体系。这一转变，使网络与连接成为 AI 规模化落地不可或缺的前提条件。

IDC FutureScape 给出的十大关键预测：

预测1｜AI 重塑云通信

到2027年，50%的企业将部署由 Agentic 人工智能（AI）驱动的云通信 API，从而以更高水平的个性化和自动化重塑通信与协作的使用方式。
要点：个性化和智能化化重塑通信与协作。

预测2｜AI 赋能的数字全连接底座（LEO 卫星）

到2029年，50%的企业将采用低轨道（LEO）卫星连接来补充地面网络，将关键的卫星直连消费者（D2C）、直连终端（D2D）以及高速宽带纳入统一的数字全连接底座。
要点：连接韧性开始向“天地一体”扩展。

预测3｜一体化蜂窝物联网

到2027年，60%的企业将利用蜂窝物联网应用、多 SIM 卡与嵌入式SIM卡（eSIM）方案，以及窄带物联网（NB-IoT）和 5G，构建面向关键业务场景的泛在连接网络。
要点：蜂窝物联网连接正在成为业务规模化的基础。

预测4｜无线广域网（WLAN）加速扩张

到2027年，80%的企业将全网集成 AI 驱动的无线广域网（wireless WAN），以提供可扩展、安全且具备高弹性的园区和分支机构连接。
要点：AI 正在重塑无线广域网的运维与自治能力。

预测5｜超大规模与网络平台（Cloud WAN）

到2028年，50%的“云优先”企业将为其 AI 工作负载采用云广域网（cloud WAN），强化云服务提供商在网络中的角色。
要点：网络能力正加速平台化、云化。

预测6｜边缘侧推理部署

到2028年，50%的企业将把推理类用例部署在边缘侧，以驱动新增收入、改善客户体验和 / 或优化内部流程。
要点：AI 推理开始向连接边缘迁移。

预测7｜零信任网络架构

到2027年，仍有30%的企业在安全访问服务边缘（SASE）的实施上保持碎片化策略，在其 SD-WAN 部署向零信任网络演进的过程中逐步调整。
要点：零信任是方向，但路径并不一致。

预测8｜虚拟 AI 网络工程师

到2027年，Agentic AI 将在不显著扩张人力规模的前提下，使网络团队的有效人效实现近乎翻番。
要点：网络团队正在被“数字员工”增强。

预测9｜AI 重塑专业服务

到2027年，AI / 生成式 AI 以及 Agentic AI 将全面融入咨询与集成服务，使服务交付能力提升25%，并将设计与配置时间缩短60%。
要点：网络专业服务进入 AI 驱动时代。

预测10｜AI 保障数据合规与可信（ESG 连接）

到2029年，围绕 ESG 强制性要求的提升，将导致仅有40%的企业会主动投资用于遥测数据采集的网络连接。
要点：连接与 ESG 的关系更加务实与现实。

这些预测对企业意味着什么？

IDC FutureScape 2026 表明，企业连接正在经历一次角色升级：从支撑 IT 运行的基础设施，转向 支撑 AI、业务连续性与组织敏捷性的战略平台。企业若仍以传统网络视角规划连接，将难以支撑 AI 推理、边缘自治与实时决策的需求。

IDC中国助理研究总监崔凯表示，未来五年，领先企业将把连接视为“AI 原生能力”的组成部分，通过 AI 驱动的云通信、无线 WAN、边缘推理与多网络融合，构建可持续演进的数字连接底座。FutureScape 2026 显示，只有将连接、AI 与安全统一规划的企业，才能在复杂环境中保持韧性与创新速度。

给企业管理层的近期行动建议

  • 将 AI 工作负载需求系统性映射到连接与网络规划中
  • 评估无线 WAN、Cloud WAN 与卫星连接的组合策略
  • 在网络运维中引入 Agentic AI 与 AIOps
  • 将边缘推理与数据主权纳入连接架构设计
  • 与服务提供商建立长期、平台化合作关系

未来 12–24 个月值得关注的信号

  • AI 驱动连接在园区与分支机构的规模化落地
  • 边缘推理对带宽与时延需求的重塑
  • 网络团队角色从“运维者”向“平台工程师”转变

进一步推荐

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。

Kai Cui - Associate Research Director - IDC

Kai Cui is an associate research director for IDC China's Telecommunications and Internet of Things (IoT) Group. His research covers telecommunications, enterprise communication, and IoT industries. He is responsible for tracking and analyzing relevant areas as well as providing research and consulting services based on customized requests. Kai has more than 15 years of experience in the communications and telecom industry. Prior to joining IDC, Kai worked at Polycom, Huawei, and other communication enterprises, where he engaged in technical support, project management, and solution planning. He has an in-depth knowledge of deployment and application of communications solutions in vertical industries. Kai graduated from the Beijing Union University in 2001, with a bachelor's degree in Computer Science.

CES 2026 made one thing clear: smart glasses are no longer a niche experiment, they’re rapidly evolving into a mainstream category with serious innovation, big partnerships, and compelling use cases. From gaming-focused specs to next-gen waveguides, the show floor and private suites were buzzing with announcements that signal a transformative year ahead for augmented reality (AR) and extended reality (XR).

XREAL steals the spotlight with big partnerships and big ambitions

XREAL had arguably the most headline-grabbing announcements at CES:

  • Gaming gets serious: XREAL unveiled its partnership with Asus ROG, introducing the first smart glasses with a 240 Hz display; a spec that gamers will appreciate for ultra-smooth visuals. This move positions further cements XREAL’s glasses as a gaming accessory and when paired with a PC, they can also function as a productivity tool.
  • Google partnership: Beyond gaming, XREAL announced a multi-year collaboration with Google, marking the first major Android XR development news of 2026 and likely means that XREAL won’t stop working on Android XR after Project Aura.
  • Fuel for growth: To top it off, XREAL secured $100 million in new funding, signaling strong investor confidence and giving the company plenty of runway to innovate and scale.

Viture’s “Beast” lives up to its name

In a private suite, Viture showcased its latest device, aptly named The Beast, and it didn’t disappoint. The display quality was stunning, truly worthy of the moniker. But the real game-changer? 3 Degrees of Freedom (3 DoF) tracking, which puts Viture in direct competition with XREAL. Expect this feature to trickle down to other brands later in 2026, intensifying competition and benefiting consumers with more choice and better tech.

Lumus pushes the boundaries of AR displays

My best demo experience came from Lumus, the company behind the optics in Meta’s AR glasses. Lumus introduced new geometric waveguides offering a 70° field of view which is a massive leap forward. While these won’t hit consumer products this year, expect them in devices within the next two years.

Why does this matter? These waveguides are highly efficient, minimizing light loss and eliminating the dreaded eye glow problem. Combined with a lightweight form factor and high fidelity, this tech will enable AR glasses to transition from simple heads-up displays to fully immersive experiences.

More brands are jumping in—thanks to a mature supply chain

One of the most interesting trends at CES 2026 was the influx of new players entering the smart glasses space. Brands like Amazfit and XGIMI, traditionally known for wearables and projectors respectively, are now launching AR glasses. Why? The technology and supply chain have matured to the point where reference designs are readily available. This means companies can make minimal changes to existing designs and still deliver competitive products.

This evolution lowers the barrier to entry, accelerates innovation, and ensures consumers will have more options at different price points. It’s a sign that smart glasses are moving from early adopter tech to a broader consumer category.

Beyond AI: Real use cases are emerging

While “AI” is the default answer to the question of smart glasses’ purpose, CES showcased a broader range of practical applications:

  • Payments on the go: Rokid demonstrated glasses capable of mobile payments, hinting at a future where wallets become obsolete.
  • Fitness integration: Brands like Amazfit and Meta displayed workout stats in real time, turning glasses into personal trainers.
  • Health tracking: Even Realities G2, announced before CES, now integrates health metrics via the R1 ring.
  • Smarter AI assistants: AI isn’t just answering questions anymore, it’s actively listening and interjecting with relevant information when needed.

What this means for 2026 and beyond

The smart glasses category is heating up. XREAL’s partnerships and funding show confidence in the long-term vision, while competitors like Viture and RayNeo are upping the ante with immersive features. Meanwhile, Lumus is laying the groundwork for the next generation of AR optics that will redefine what “immersive” truly means. And with new brands entering the space thanks to mature supply chains, expect rapid growth and diversification.

The big question now: Will consumers embrace these devices beyond gaming and fitness? With AI becoming proactive and new use cases emerging, the answer might be yes sooner than we think.

Bottom line: CES 2026 wasn’t just about flashy prototypes rather it was a clear signal that smart glasses are moving toward mass adoption. With major players investing heavily and technology advancing rapidly, the next two years will be pivotal for AR and XR.

Jitesh Ubrani - Research Manager - IDC

Analyst Profile
Jitesh is a Research Manager for the Worldwide Mobile Device Trackers, including Wearables, Augmented Reality (AR), Virtual Reality (VR), Tablets, and Phones. The team focuses on the market sizing, forecasting, and analyzing trends to provide insight into the competitive landscape of the worldwide mobile industry. Prior to joining IDC in 2012, Jitesh was part of the Market Analysis and Intelligence team at Bell Mobility, one of Canada's largest telecom service providers, where his role focused on understanding smartphone adoption and usage as well as consumer purchasing behavior. Mr. Ubrani holds a bachelor of commerce degree with a major in Economics from Ryerson University and is currently based in Toronto, Canada.

制造业，正站在从“自动化”迈向“自主化”的门槛

制造业不确定性持续上升、产品复杂度与柔性需求并行增长的背景下，中国制造企业正面临一次关键抉择：是继续以点状自动化与局部优化应对变化，还是系统性迈向以数据、模型与智能体驱动的自主化运营。IDC 认为，这一选择将直接决定企业未来五年的运营韧性、创新效率与全球竞争力。

IDC 认为，中国制造业正在进入一个新的关键阶段：AI 不再只是提升局部效率的工具，而是推动生产系统向“自主化运营”演进的核心引擎。

为什么这份 FutureScape，对中国制造业尤为关键

在《IDC FutureScape：全球制造业2026年预测——中国启示》（Doc# CHC52915025，2025年12月）中，IDC 指出，中国制造业未来五年的智能化升级，将不再以单点应用为主，而是围绕自动化平台开放化、AI 驱动的计划与控制、OT 数据智能整合、人机协同、工业安全以及混合云与智能体治理等关键能力展开。
这些能力的成熟度，将直接决定制造企业能否从“数字化工厂”跨越到“自主化工厂”，并在全球竞争中建立可持续优势。

IDC FutureScape 给出的十大关键预测:

预测1｜软件定义工厂

受自主化运营的潜力驱动，到2029年，将有30%的中国工厂通过开放、虚拟化、软件定义的自动化平台，在中央统一配置和管理自动化控制系统。
要点：自动化控制正在从封闭专有系统走向开放、可编排的平台化形态。

预测2｜AI APS

到2026年，超过40%已部署 APS 的中国制造商将升级为 AI 赋能的 APS，从而开始实现自主化流程。
要点：生产计划与排程正从“人主导”迈向“持续自优化”。

预测3｜IT/OT 融合 Agent

到2027年，随着标准化水平提升以及面向特定数据类型的 AI 智能体（AI Agents）广泛应用，40%的 OT 数据将能够在应用与平台之间实现自主集成。
要点：智能体正在改变工业数据工程的效率边界。

预测4｜AI 后服务

为打通设计与服务之间的闭环，到2027年底，25%的中国头部 OEM 及售后服务企业将利用 AI 连接现场与工程数据，从而提升产品与服务质量。
要点：产品创新开始真正进入全生命周期闭环。

预测5｜可预测工业数据安全

为应对数据模型安全风险，到2029年，60%的大型制造企业将采用 AI 驱动的 OT 网络防御系统，将威胁检测时间缩短60%。
要点：工业 AI 安全正从“被动防御”转向“预测与自主响应”。

预测6｜人机技能互学

到2028年，未能建立人机技能闭环的中国企业，将面临比同行高出20%的停机和再培训成本，其生产效率也将明显低于已实施双向培训机制的企业。
要点：人机协同能力成为生产韧性的核心变量。

预测7｜设计仿真 Agent

到2028年，65%的中国头部制造企业将在设计与仿真工具中结合 AI 智能体（AI Agents），以持续验证设计更改、配置与变体是否符合产品要求。
要点：仿真与工程决策正在加速智能化。

预测8｜AI 员工培训

到2028年，超过30%的中国头部制造企业将采用 AI 驱动的知识管理工具，对员工进行再培训和技能升级，并促进产业生态内的协作共享。
要点：知识数字化成为应对劳动力波动的关键手段。

预测9｜复合式工业 AI

到2030年，70%的中国头部制造企业将借助 AI 智能体（AI Agents）构建数据模型并管理混合云工作负载，从而将质量成本降低2%。
要点：混合云与多智能体协同成为工业 AI 的主流架构。

预测10｜工业模型管理

到2029年，40%的中国头部制造企业将依托超大规模云生态，构建、部署并扩展新一代 AI 解决方案，加速数字化转型进程。
要点：行业云与模型生态将重塑制造软件格局。

这些预测对制造企业意味着什么

IDC FutureScape 2026 清晰表明，中国制造业的竞争焦点正在发生结构性转移：
从单点自动化，转向系统级自主化；从经验驱动，转向数据与模型驱动；从局部优化，转向跨设计、生产与服务的全局协同。无法建立这些基础能力的企业，即便部署了 AI，也难以真正释放规模化价值。

IDC中国高级研究经理杜雁泽表示，中国制造业正在跨越“数字化到智能化”的关键拐点。FutureScape 2026 显示，领先企业正通过开放式自动化平台、AI 智能体和混合云架构，将 AI 深度嵌入生产控制、工程决策与知识传承之中，从而构建可持续、自主演进的运营体系；而仍停留在封闭系统与点状应用阶段的企业，将在效率、韧性和创新速度上持续承压。

给制造企业管理层的近期行动建议：

  • 评估现有自动化系统向开放、软件定义架构演进的可行性
  • 以 APS、质量与能耗等高价值场景为切入口推进 AI 自主化
  • 建立 OT 数据标准化与智能体协同的数据治理基础
  • 将 AI 安全与模型治理纳入工业网络安全战略
  • 投资人机技能闭环与 AI 知识平台，提升组织韧性

未来 12–24 个月需要重点关注的信号

  • 软件定义自动化在中国头部工厂的规模化进展
  • AI 智能体在工业数据工程与仿真中的成熟度
  • 工业 AI 安全从“合规导向”向“风险导向”的转变

进一步推荐

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。

Yanze Du - Senior Research Manager - IDC

Yanze Du is a senior research manager for the Manufacturing Insights group in IDC China, and he is responsible for conducting research on and analysis of the China manufacturing industry and supply chain. He is also involved in regional and global consulting, and business development in related markets. Prior to joining IDC, Yanze had an in-depth working experience in the digital transformation field and had wide exposure to various businesses in the manufacturing industry including smart manufacturing and industry software. These experiences gave him a deep understanding of both the status quo and future trends of the market. Yanze graduated from Tianjin University with a bachelor's degree in Computer Science.

在技术突破、产业成熟与应用需求共同推动下，中国机器人与具身智能市场正加速进入规模化发展阶段。进入2026年，IDC重点关注清洁、教育陪伴、服务、人形及四足机器人等产品在应用边界拓展、智能能力提升和真实场景落地上的进展。与此同时，具身智能正成为新一代机器人智能系统的“通用底座”，随着具身智能机器人的研发、部署与商业化路径加速成型，中国凭借完善产业链、丰富场景和工程化迭代优势，正成为技术验证与商业模式创新的核心策源地。

未来机器人市场将从单机智能向系统级智能演进，从展示型创新向价值验证与规模复制转变，并由硬件销售逐步迈向服务化与长期运营。基于对中国机器人与具身智能行业的持续跟踪，IDC总结十大趋势洞察揭示行业发展的核心方向与关键变量，为厂商与行业生态提供战略参考。

洞察一：清洁机器人迈向全场景化发展，细分赛道加速分化

中国清洁机器人的应用边界正持续扩展，逐步正从室内核心生活区域的地面清洁、扫拖一体等基础功能，加速向室外庭院、露台、泳池、入户小径等多元家庭场景延伸，真正构建起 “全屋 + 庭院” 的全维度清洁服务生态。大模型助力、机械臂搭载、导航能力提升等多维度进步推动家庭清洁机器人产品不断精准匹配用户需求。随着应用复杂度提升，行业竞争格局加速分化，垂直赛道厂商凭借场景理解与专业能力持续深耕细分领域，头部综合型厂商则依托品牌、供应链与渠道优势推进品类横向扩展。IDC预测，2026年中国清洁机器人市场规模近34亿美元，同比增长18%。

洞察二：教育陪伴机器人向全龄段长期陪伴型家庭智能终端演进

在大模型、多模态感知与自然交互能力加持下，中国教育与陪伴机器人正从单一学习辅助工具，升级为覆盖儿童学习引导、成人情绪价值与养老陪护的全龄段家庭智能终端。产品形态更加重视长期陪伴、情境理解与内容服务深度，应用价值由“功能使用”向“关系与服务持续性”延伸。随着家庭教育精细化、情感陪伴需求与老龄化趋势叠加，商业模式亦由一次性硬件销售，加速向内容订阅与服务化运营演进，推动该赛道具备更强的持续变现与规模化潜力。IDC预测，中国教育陪伴机器人市场规模超10亿美元，同比增长89%。

洞察三：服务机器人向智能化与人文价值升级

商用服务机器人已在餐饮、酒店、医疗、零售等多个行业场景中实现规模化落地，全面提供配送、清洁、引导、辅助操作等服务任务，逐步融入用户日常运营体系。在持续积累的应用实践中，中国厂商通过多模态感知、大模型、具身智能等技术的融合，强化机器人在跨场景、多任务执行中的稳定性与通用性，推动其由单一功能设备向综合智能服务平台演进。随着应用深化，商用服务机器人的价值边界进一步拓展，在提升运营效率的同时，通过降低人工强度、提升安全性与服务体验，释放更具长期意义的社会价值。IDC预测，2026年中国商用服务机器人市场规模将近4亿美元，同比增长15%。

洞察四：人形机器人应用场景快速扩张，技术突破加速商业化落地

中国人形机器人市场快速扩张，应用场景由导览、文娱、教育延伸至工业制造、物流仓储、零售服务等生产服务型场景。多行业落地需求推动厂商在本体结构、执行系统、小脑运动控制及大脑决策与认知能力上的技术积累。从落地工程化角度看，轮式人形机器人可用于高效移动与辅助任务，同时上半身的精细操作能力也将进一步提升，整体系统效率与场景适应能力显著增强。依托系统集成、硬件自主设计与多场景经验，中国厂商正形成差异化技术路线，加速人形机器人与多形态协同的商业化落地。IDC 预测，到 2026 年，中国人形机器人应用场景将提升至当前的3倍以上，市场规模将近13亿美元，同比增长翻倍以上。

洞察五：四足机器人“双轮驱动”发展，消费情绪价值与行业实用价值并行

四足机器人市场呈现出消费级与行业级应用并发的发展特征。在消费市场，四足机器人以陪伴、互动与情绪价值为核心，融合大模型的能力，强调拟态表现、智能交互与内容体验，逐步进入家庭与个人娱乐场景；在行业应用市场，四足机器人更侧重实用与可靠性，在巡检、安防、应急、能源等复杂环境中发挥稳定移动与负载能力优势。消费端推动产品形态与体验创新，行业端验证规模化价值，两者协同加速四足机器人从展示型产品向可持续应用演进。IDC 预测，到 2026 年，中国四足机器人市场规模将超7亿美元，同比增长翻倍。

洞察六：灵巧手成为精细作业与多场景协同的核心利器

灵巧手正迈向高精度装配、物流分拣及服务型场景应用。通过高自由度控制、触觉感知及视觉+大模型算法融合，灵巧手具备自主抓取调整与多机器人协同操作能力。产业需求吸引更多厂商入局灵巧手研发制造，推动模块化设计、智能控制与系统集成快速迭代，使其成为人形、四足等多形态机器人跨平台协作的核心操作工具，有效提升复杂任务的精细性与可靠性。IDC预测，到2026年，中国灵巧手市场规模将突破3亿美元，实现150%以上增长。

洞察七：产业生态竞争格局重塑，中国品牌加速全球化

在消费与服务机器人市场，中国厂商凭借成本优势、工程化能力和场景适配速度构建竞争壁垒，推动市场格局持续优化。随着应用需求向系统化、全流程解决方案演进，厂商在核心模块研发、系统集成与智能化能力上持续突破，并通过丰富的落地经验加速产品迭代与服务优化，实现对多行业、多场景需求的快速响应。同时，中国厂商积极布局海外市场，通过本地化生产、本土化渠道布局和多元化服务体系加快全球化扩张，提升国际市场份额。IDC预测，到 2026 年，中国服务和消费机器人厂商在全球市场出货量占比将超过85%，成为全球增长的重要推动力。

洞察八：中国引领全球具身智能机器人增长主导市场加速扩张

政产学研协同推动具身智能机器人发展，助力制造业与服务业智能化升级。国家及地方政府打造产业平台，整合资源并促进协同；产业界凭借成熟零部件、整机集成与系统工程能力持续扩大规模；科研机构与企业联合突破数据、模型、多模态感知、新材料与新能源等技术，并加速场景落地，实现从实验室示范到商业化的完整生态。RaaS、订阅、本体+模型联合计费及运维数据服务等多元商业模式延长价值回收周期，提升客户体验与粘性，推动市场快速增长。IDC预测，到 2026 年，中国具身智能机器人用户支出规模超110亿美元，持续近120%的高速增长。

洞察九：功能价值驱动具身智能应用，人形机器人与多形态协同提升系统效率

中国具身智能机器人正从以演示试点阶段迈入以效率提升、成本优化和流程改进为核心的价值验证阶段。市场关注点转向机器人在真实业务中的稳定性、可复制性与 ROI。为兼顾效率、可靠性与成本，行业加速采用“人形 + 轮式 + 多足 + 机械臂”等多形态机器人协同作业体系，明确任务分工，并通过统一调度与认知体系提升整体系统效能和场景适配能力，同时降低部署风险与运营成本。IDC 预测，到 2026 年，约60% 的中大型具身智能机器人应用项目将采用两种及以上机器人形态协同作业。

洞察十：局部任务闭环成为具身智能机器人通用能力演进的现实路径

中国具身智能机器人落地实践逐步形成以具体场景为切入、围绕岗位职责拆解子任务的实施路径。优先跑通单一场景闭环可降低系统复杂度，提高部署成功率，并沉淀可复用工程模板。在此基础上，各种形态的家用及服务机器人将不断积累现实数据并优化升级具身智能大模型能力，通过迁移学习与策略复用，将感知、决策与控制经验扩展至相邻场景，突破单一功能与场景的局限。实现从局部智能向泛化能力的演进。IDC预测，到 2026 年，中国具身智能机器人在相似场景间的任务复用率将约 40%。

IDC认为，中国机器人与具身智能市场已进入关键拐点期。技术不再是稀缺资源，差距在于厂商能否将感知、决策、控制、系统集成与场景理解整合为稳定、可复制、可扩展的整体解决方案。未来两到三年，行业竞争特征为：

  • 硬件参数差异缩小，软硬系统能力成为分水岭。本体结构、算力与传感器将逐步标准化，厂商核心竞争力将集中在运动控制、模型算法、任务编排与跨场景迁移等能力上。
  • 场景理解与工程化经验价值持续提升。具备真实部署数据、行业经验和交付模板的厂商，在商业化落地中将获得显著优势。
  • 生态协同取代单打独斗。具身智能机器人的发展需要算法、硬件、系统集成、行业客户与服务商的协同，开放生态和合作能力将成为重要竞争要素。

基于此，IDC建议以应用场景价值为核心稳步推进具身智能机器人落地。机器人与具身智能厂商应优先聚焦具备闭环价值的具体场景和岗位任务，强化系统集成与工程化交付能力，将算法与技术优势转化为可复制、可规模化的解决方案，并提前布局服务化与长期运营模式；行业用户应以效率提升、成本优化和风险降低为核心评估标准，从单点试点逐步向系统化部署演进，深化与厂商的长期协同；产业生态与投资方则应重点关注具备真实落地与持续交付能力的厂商，支持关键基础模块和通用软件平台建设。

进入2026年，IDC中国机器人与具身智能研究团队持续跟进技术、市场、应用进展，如需进一步了解报告内容或机器人市场，请与IDC 中国研究经理李君兰（邮箱：lyli@idc.com）、高级分析师赵思泉（邮箱：czhao@idc.com）、研究总监潘雪菲（邮箱：span@idc.com）联系。

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。

Lily Li - Research Manager - IDC

Lily Li is a research manager for emerging technologies in IDC China. She is responsible for conducting research and analysis for Internet of Things (IoT) in the same country. She is also involved in global and regional consulting as well as business development in related markets. Prior to joining IDC, Lily has had in-depth working experiences in the urban digital transformation (DX) field and a wide range exposure to Smart City developments. She has a deep understanding of the status quo and is knowledgeable about the market's future trends. Lily holds a master's degree from the Graduate University of Chinese Academy of Sciences (GUCAS).

Quantum computing and the awareness of quantum enabled threats are no longer a futuristic concept. They are fast-approaching reality with profound implications for cybersecurity, IT infrastructure, and business strategy.

When conducting the IDC MarketScape: Worldwide Data Protection and Governance Services 2025 Vendor Assessment research, I was pleasantly surprised that post-quantum cryptography (PQC) is gaining significant momentum. It is shaped by sector-specific priorities and a few broad enablers such as regulatory deadlines and NIST standards. For example, U.S. federal agencies, Canadian federal government IT systems and, EU member states must be quantum-resistant by 2035, with some mandates as early as 2030. NIST has released PQC standards while simultaneously announcing the deprecation of widely used algorithms like RSA and ECC by 2030, and fully disallowing them after 2035.

In response, a reality check is needed: organizations need to transition toward quantum-safe cryptography faster than what they might comfortable. Recognizing this new reality, IDC predicts 40% of G2000 organizations are expected to engage cybersecurity professional services firms by 2027 to conduct quantum risk assessments and prepare for the post-quantum era.

Why Quantum Risk Assessments Matter

Quantum risk assessments are the first step in understanding how vulnerable an organization’s digital assets are to quantum-enabled threats. These assessments typically involve:

  • Inventorying cryptographic assets across applications, databases, and communication channels.
  • Evaluating exposure to “harvest now, decrypt later” attacks, where encrypted data is stolen today and decrypted once quantum computers become powerful enough.
  • Prioritizing systems for migration to post-quantum cryptography (PQC).
  • Developing a roadmap for secure, scalable, and compliant transition.

Why G2000 Enterprises Must Act Now

For G2000 enterprises, especially those with global operations, complex IT environments, and high-value data face significant risks if they delay quantum readiness. Benefits of early action include:

  • Risk mitigation: Organizations that delay quantum preparation risk data breaches, regulatory penalties, and reputational damage. Early assessments help identify and mitigate these risks.
  • Customer trust: In sectors like finance, healthcare, and government, data security is a cornerstone of customer trust. Quantum readiness signals a proactive commitment to safeguarding sensitive information.
  • Competitive advantage: Enterprises that lead in quantum readiness can differentiate themselves in the market, attract security-conscious customers, and influence industry standards.
  • Strategic planning: Quantum risk assessments inform broader digital transformation strategies, helping organizations align IT investments with long-term resilience goals.

IT Impact: Infrastructure, Integration, and Innovation

Quantum readiness affects every layer of IT:

  • Infrastructure overhaul: Legacy systems using RSA or ECC encryption must be identified and upgraded. This may involve rearchitecting applications, updating protocols, and ensuring compatibility with PQC algorithms.
  • Vendor coordination: IT leaders must work closely with technology vendors to ensure their platforms support quantum-safe cryptography. This includes cloud providers, networking equipment, and software vendors.
  • Performance testing: PQC algorithms can be more resource intensive. IT teams must evaluate the impact on latency, throughput, and scalability—especially for mission-critical systems.
  • Security operations: Quantum readiness will reshape threat modelling, incident response, and compliance frameworks. Security teams must adapt to new cryptographic standards and evolving attack vectors.

The Role of Cybersecurity Professional Services Firms

Quantum computing will reshape the digital landscape. For G2000 enterprises (especially those in critical sectors), conducting quantum risk assessments is not just a technical necessity, but also a strategic investment in resilience, trust, and future competitiveness.

Organizations should:

  1. Partner with a right provider that knows the industry and have gone down the PQC path to evaluate exposure and plan mitigation.
  2. Map out where and how encryption is used across the enterprise.
  3. Test pilot PQC algorithms in controlled environments to evaluate performance and integration.
  4. Educate stakeholders: Build awareness across leadership, IT, and security teams.

The quantum clock is ticking. Is your organization ready? To find out more details, please refer to the IDC FutureScape: Worldwide Security and Trust 2026 Predictions.

Cathy Huang - Senior Research Director, Worldwide Security Services - IDC

Analyst Profile LinkedIn
Cathy Huang is Senior Research Director for IDC’s Worldwide Security Services research practice. In her role, Cathy collaborates with other worldwide and regional analysts to develop a set of thought leadership and actionable research for IT buyers and suppliers. Specifically, she develops core research around professional security services and cybersecurity consulting services, cloud security services within the program. She also incorporates IDC’s overarching agenda to drive new research such as AI Impact for cybersecurity services, data protection & governance services, deepfake detection for the program. Ms. Huang draws on her deep domain expertise across a broad range of ICT segments to support any custom research or advisory work regarding security services.