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市场调查报告书
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1934869

电信和网路管理中的基于代理的人工智慧：市场份额分析、行业趋势和统计数据、成长预测（2026-2031 年）

Agentic AI In Telecommunications And Network Management - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

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简介目录

预计通讯和网路管理领域基于代理的人工智慧市场将从 2025 年的 37.5 亿美元成长到 2026 年的 46.3 亿美元，到 2031 年将达到 133.5 亿美元，2026 年至 2031 年的复合年增长率为 23.57%。

电信和网路管理中的智慧体人工智慧市场-IMG1

随着5G和新兴的6G网路需要对数百万个变数进行即时优化，而传统的基于规则的系统无法应对，通讯业者正优先考虑自主编配。虽然云端原生平台是早期采用的基础，但为了降低推理延迟，边缘运算和多接取边缘运算（MEC）正在迅速发展。随着攻击者采用人工智慧，诈欺和安全管理尤其重要，迫使通讯业者在每一层都整合智慧异常检测功能。网路设备供应商、超大规模资料中心业者和人工智慧专家组成多厂商联盟，承诺提供开放介面和快速创新週期，竞争日益激烈。光纤和网路安全领域的策略併购预示着，未来整合连接和人工智慧安全将成为捍卫市场地位的必要前提。

全球基于代理的人工智慧市场趋势及电信和网路管理洞察

5G/6G网路复杂性的增加推动了自主编配

天线数量、频宽和服务等级要求的激增使得手动优化变得不切实际，迫使通讯业者嵌入能够学习并持续执行网路意图的自主代理。马来西亚数位国民有限公司 (Digital Nasional Berhad) 在部署爱立信的基于意图的平台六个月后，实现了 99.8% 的运转率和 500% 的告警减少。 6G 研究表明，将非地面电波链路整合到地面电波小区中将使编配负担翻倍，从而增强了其商业价值。诺基亚的模型显示，自主网路每年可透过资本支出 (CAPEX)、营运支出 (OPEX) 和收入收益的组合，为通讯业者带来 8 亿美元的收益。这些经济效益促使董事会迫切希望将概念验证(PoC) 转化为大规模运作部署。

资料流量的快速成长以及对预测性网路优化的需求

即时影片和人工智慧工作负载带来的每小时流量高峰令传统的规划週期不堪重负。 Verizon部署的无线智慧控制器透过在流量高峰到来之前转移容量，实现了15%的节能效果。通讯业者报告称，与被动响应式方法相比，利用预测代理进行主动资源分配可将拥塞事件减少30%至50%。边缘资料中心的情况更为严峻，因为那里的推理负载是突发的且局部的。因此，预测优化已成为保障使用者体验和企业服务等级协定 (SLA) 的必要手段。

通讯业者人工智慧倡议面临的资料隐私和监管障碍

GDPR 和即将出台的欧盟人工智慧法规迫使通讯业者增加多层可解释性措施和严格的资料本地化控制，从而延长计划週期。联邦学习虽然能够确保合规性，但可能会使计算成本增加三倍。跨境业者必须协调不同的框架，这会削弱规模经济效益。这种不确定性导致部署方式趋于渐进，并促使营运商更加依赖超大规模资料中心业者的隐私工具包来确保审核准备就绪。

细分市场分析

到2025年，解决方案和平台将占总支出的59.65%，这主要得益于通讯业者对可直接整合到现有OSS/BSS系统中的承包功能的需求。由于客製化工作流程，服务预计将以26.99%的复合年增长率成长，超过电信和网路管理领域基于代理的人工智慧市场的整体成长速度。由于需要对现有（棕地）网路进行特定领域的调整，电信和网路管理服务领域基于代理的人工智慧市场规模预计将迅速扩张。整合通讯业者负责资料管道调优、领域模型开发和生命週期管治，而这些功能是许多营运商内部所缺乏的。他们还提供託管优化服务，以使人工智慧代理商能够持续适应不断变化的业务KPI。因此，专业服务收入将随着人工智慧成熟阶段的推进而同步成长，这将使服务提供者深度融入通讯业者运营，创造持续的收入来源，并提升整体市场知名度。

电信和网路管理领域的基于代理的人工智慧市场受益于平台供应商和服务合作伙伴之间的共生循环。随着平台日趋成熟，它们会开放细粒度的API，从而促进第三方模组的开发。这形成了一个良性循环，推动了对整合和DevOps人才的需求。该循环加速了创新步伐，同时使营运商能够保持精简的内部团队。因此，服务将缩小（但不会完全消除）与解决方案之间的收入差距，从而确保在2031年整个组件堆迭中实现均衡成长。

到2025年，云端部署将维持57.62%的市场份额，这主要得益于超大规模资料中心业者提供的弹性运算资源，可用于训练大型模型。然而，随着自动驾驶汽车和工业自动化等需要毫秒响应时间的应用场景的兴起，边缘运算（MEC）实例预计将以26.02%的复合年增长率成长。一旦营运商在基地台台统一微型资料中心部署标准，电信和网路管理领域基于代理的人工智慧的边缘市场份额预计将大幅提升。领先采用者报告称，将推理处理保留在本地，可节省15%的能源并降低回程传输负载。云端策略引擎负责协调学习过程，而决策迴路则在边缘进行，从而支援混合拓扑结构。

尤其对于受严格主权法规约束的营运商而言，他们需要依赖国内部署的云端平台来实现超大规模运营，同时确保合规性。这种云端、边缘和本地部署的混合模式增加了生命週期管理的复杂性，也编配提供了确保模型一致性的机会。成功的解决方案将抽象化位置的复杂性，并在不影响延迟或安全性的前提下，在整个联合层提供统一的控制平面。

区域分析

预计到2025年，北美将维持38.34%的收入份额，这主要得益于5G的广泛应用、充裕的创业投资以及鼓励创新的明确监管政策。 Verizon和T-Mobile正与Google和英伟达合作，共同开发一款优化引擎，已将销售转换率提高了40%，并降低了能源成本。该地区在电信业的AI专利申请中占据主导地位，这为本地供应商带来了智慧财产权优势，同时也有利于海外授权。政府资助计画对区域边缘云端的津贴，进一步扩大了符合条件的站点范围，并加快了部署速度。

亚太地区预计将成为成长最快的市场，到2031年复合年增长率将达到25.78%。在中国，政府主导的投资正在确保全国范围内的5G覆盖，并建立针对通讯业者需求的先进人工智慧研究实验室。韩国一家大型通讯业者在2024年至2025年间向人工智慧Start-Ups投资超过2.1亿美元，以确保获得新兴演算法的独家使用权。印度智慧型手机的快速普及需要基于人工智慧的频谱效率，以便在不购买频宽的情况下服务人口密集的都市区。全球电信人工智慧联盟等区域合作正在促进成熟框架的跨境应用，并缩短引进週期。

欧洲在支出方面排名第三，但在隐私权保护创新方面领先，这主要得益于GDPR合规性推动了联邦学习技术的应用。通讯业者通常会在正式部署前对可解释代理进行试点，虽然这会延长开发週期，但有助于建立信任。为了避免巨额资本支出，南美洲倾向于透过託管服务提供经济高效的人工智慧解决方案，而中东和非洲则致力于利用人工智慧驱动的能源优化来抵消不断上涨的电价。这些市场通常具有多样化的进入路径，确保全球供应商能够根据区域限制调整其产品组合。

其他福利：

  • Excel格式的市场预测（ME）表
  • 3个月的分析师支持

目录

第一章 引言

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章 市场情势

  • 市场概览
  • 市场驱动因素
    • 5G/6G网路复杂性的增加推动了自主编配
    • 资料流量的快速成长以及对预测性网路优化的需求
    • 为降低客户流失率，对客户分析的需求日益增长
    • 通讯业者资本支出转向人工智慧驱动的开放式无线存取网和虚拟无线存取网部署
    • 通讯业者主权人工智慧资料中心的崛起
    • 在自主现场服务运作中引入基于代理的人工智慧
  • 市场限制
    • 通讯业者人工智慧倡议面临的资料隐私和监管障碍
    • 通讯业者严重缺乏人工智慧人才
    • 网路边缘推理能耗飙升
    • 使用专有AI原生网路协定栈的供应商锁定风险
  • 价值链分析
  • 监管环境
  • 技术展望
  • 波特五力分析
    • 新进入者的威胁
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 竞争对手之间的竞争
  • 宏观经济因素如何影响市场

第五章 市场规模与成长预测

  • 按组件
    • 解决方案/平台
    • 服务
  • 透过部署模式
    • 云
    • 本地部署
    • Edge/MEC
  • 透过使用
    • 客户分析
    • 网路优化与编配
    • 诈欺和安全控制
    • 虚拟助理和客户体验自动化
    • 预测性维护
    • 其他用途
  • 透过网路域
    • 核心网路
    • 无线接取网路（RAN）
    • 运输/回程传输
    • OSS/BSS
  • 借助人工智慧技术
    • 机器学习
    • 自然语言处理
    • 深度学习
    • 人工智慧世代
    • 强化学习
  • 按地区
    • 北美洲
      • 我们
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 智利
      • 其他南美洲
    • 欧洲
      • 德国
      • 英国
      • 法国
      • 义大利
      • 西班牙
      • 其他欧洲地区
    • 亚太地区
      • 中国
      • 日本
      • 印度
      • 韩国
      • 澳洲
      • 新加坡
      • 马来西亚
      • 亚太其他地区
    • 中东和非洲
      • 中东
        • 沙乌地阿拉伯
        • 阿拉伯聯合大公国
        • 土耳其
        • 其他中东地区
      • 非洲
        • 南非
        • 奈及利亚
        • 其他非洲地区

第六章 竞争情势

  • 市场集中度
  • 策略趋势
  • 市占率分析
  • 公司简介
    • Telefonaktiebolaget LM Ericsson
    • Huawei Technologies Co., Ltd.
    • Nokia Corporation
    • Samsung Electronics Co., Ltd.
    • Cisco Systems, Inc.
    • Juniper Networks, Inc.
    • ZTE Corporation
    • NEC Corporation
    • Mavenir Systems, Inc.
    • Parallel Wireless, Inc.
    • Airspan Networks Holdings Inc.
    • Rakuten Symphony Singapore Pte. Ltd.
    • Amdocs Limited
    • Netcracker Technology Corporation
    • Ribbon Communications Inc.
    • Casa Systems, Inc.
    • Radisys Corporation
    • Ciena Corporation
    • VIAVI Solutions Inc.
    • EXFO Inc.
    • TEOCO Corporation
    • Subex Limited
    • Intracom SA Telecom Solutions
    • MATRIXX Software, Inc.
    • Sandvine Corporation
    • DeepSig, Inc.

第七章 市场机会与未来趋势

  • 閒置频段与未满足需求评估
简介目录
Product Code: 94390

The Agentic AI in Telecommunications and Network Management market is expected to grow from USD 3.75 billion in 2025 to USD 4.63 billion in 2026 and is forecast to reach USD 13.35 billion by 2031 at 23.57% CAGR over 2026-2031.

Agentic AI In Telecommunications And Network Management - Market - IMG1

Operators are prioritizing autonomous orchestration because 5G and emerging 6G networks require real-time optimization across millions of variables that conventional rule-based systems cannot manage. Cloud-native platforms anchor early deployments, yet rapid migration toward edge and multi-access edge computing (MEC) is underway to shave inference latency. Fraud and security management is enjoying outsized attention as adversaries adopt AI, pushing operators to embed intelligent anomaly detection at every layer. Competitive intensity is rising as network equipment makers, hyperscalers, and AI specialists form multi-vendor coalitions that promise open interfaces and faster innovation cycles. Strategic mergers in fibre and cybersecurity hint at a future where integrated connectivity and AI security become table stakes for defending market positions.

Global Agentic AI In Telecommunications And Network Management Market Trends and Insights

Rising 5G/6G Network Complexity Driving Autonomous Orchestration

Escalating antenna counts, spectrum bands, and service-level requirements make manual optimisation unworkable, prompting operators to embed autonomous agents that learn network intent and enforce it continuously. Digital Nasional Berhad achieved 99.8% uptime and a 500% alarm reduction within six months of adopting Ericsson's intent-based platform. Research for 6G suggests the orchestration burden will multiply as non-terrestrial links join terrestrial cells, reinforcing the business case. Nokia's modelling shows autonomous networks can unlock USD 800 million in annual operator benefits through combined CAPEX, OPEX, and revenue effects. Those economics drive board-level urgency to convert proof-of-concepts into production deployments at scale.

Surging Data Traffic and Need for Predictive Network Optimisation

Hourly traffic spikes fuelled by live video and AI workloads now overwhelm conventional planning cycles. Verizon's deployment of radio-intelligent controllers delivers 15% energy savings by shifting capacity ahead of surges. Operators report 30-50% reductions in congestion events when predictive agents pre-allocate resources versus reactive steps. Edge data centres intensify the challenge because inference loads appear suddenly and locally. Consequently, predictive optimisation is no longer optional for safeguarding user experience and enterprise SLA commitments.

Data-Privacy and Regulatory Hurdles for Telco AI Initiatives

GDPR and impending EU AI Act rules force operators to add explainability layers and strict data-localisation controls that stretch project timelines. Federated learning offers compliance but can triple compute costs. Cross-border operators must juggle divergent frameworks that undercut scale economies. The uncertainty prompts phased deployments and higher dependence on privacy-preserving toolkits from hyperscalers that guarantee audit readiness.

Other drivers and restraints analyzed in the detailed report include:

  1. Growing Demand for Churn-Reducing Customer Analytics
  2. Operator CAPEX Shift Toward AI-Powered Open RAN and vRAN Roll-outs
  3. Acute Shortage of Telecom-Grade AI Talent

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Solutions and platforms accounted for 59.65% of 2025 spending as operators sought turnkey functionality that plugs into existing OSS/BSS. Services are projected to expand at a 26.99% CAGR, outpacing the overall Agentic AI in Telecommunications and Network Management market due to customisation workstreams. The Agentic AI in Telecommunications and Network Management market size for services is forecast to widen quickly as brownfield networks require domain-specific tuning. Integration specialists orchestrate data pipelines, develop domain models, and handle lifecycle governance, functions that many operators lack in-house. They also deliver managed optimisation that continuously aligns AI agents with shifting business KPIs. Professional services revenue, therefore, rises in tandem with AI maturity phases, embedding providers deep within operator operations and creating annuity streams that lift overall market visibility.

The Agentic AI in Telecommunications and Network Management market benefits from a symbiotic cycle between platform vendors and service partners. As platforms mature, they expose granular APIs that foster third-party modules, which in turn spur demand for integration and DevOps talent. This virtuous loop accelerates innovation velocity while allowing operators to maintain lean internal teams. Consequently, services will narrow but not erase the revenue gap with solutions, ensuring balanced growth across the component stack through 2031.

Cloud deployments retained a 57.62% share in 2025 because hyperscalers supply elastic compute for training massive models. However, MEC instances are set to post a 26.02% CAGR as use cases, such as autonomous vehicles and industrial automation, demand single-digit millisecond responses. The Agentic AI in Telecommunications and Network Management market share for edge is expected to rise sharply once operators standardise micro-data-centre footprints across base-station sites. Early adopters cite 15% energy savings and reduced backhaul when inference stays local. Policy engines in the cloud still coordinate learning, yet decision loops shrink at the edge, reinforcing a hybrid topography.

Notably, operators with stringent sovereignty rules rely on on-premises clouds inside national borders, preserving compliance while retaining hyperscale-like operations. This blend of cloud, edge, and on-premises outposts complicates lifecycle management, creating room for orchestration vendors that guarantee model consistency. Winning solutions will abstract location complexity, providing a single control plane across federation layers without compromising latency or security.

Agentic AI in Telecommunications and Network Management Market Report is Segmented by Component (Solutions/Platforms and Services), Deployment Mode (Cloud and More), Application (Customer Analytics and More), Network Domain (Core Network, Radio Access Network, and More), AI Technology (Machine Learning, Natural Language Processing, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America retained 38.34% revenue share in 2025 owing to pervasive 5G, deep venture capital, and clear regulatory signals that reward experimentation. Verizon and T-Mobile partner with Google and NVIDIA to co-create optimisation engines that have already lifted sales conversions by 40% and trimmed energy bills. The region also commands the lion's share of AI patent filings in telecoms, giving local vendors an intellectual-property edge that travels well when licensing abroad. Government funding programmes that subsidise rural edge clouds further expand addressable sites, accelerating rollout velocity.

Asia-Pacific is projected to post a 25.78% CAGR to 2031, making it the fastest-expanding theatre. China's state-backed investments guarantee nationwide 5G coverage and seed advanced AI research labs that dovetail with operator needs. South Korea's leading telcos invested over USD 210 million in AI start-ups during 2024-2025 to secure exclusive access to emerging algorithms. India, propelled by surging smartphone adoption, demands AI-based spectral efficiency to serve dense urban clusters without exhaustive spectrum purchases. Regional collaborations, such as the Global Telco AI Alliance, spread proven frameworks across borders, compressing deployment cycles.

Europe ranks third in spending but first in privacy-preserving innovation as GDPR compliance drives adoption of federated learning. Operators often pilot explainable agents before turning them loose in production, lengthening timelines yet fostering trust. South America favours cost-efficient AI delivered via managed services to sidestep capex spikes, while the Middle East and Africa pursue AI-enabled energy optimisation to offset high power costs. Collectively, these markets demonstrate diverse entry paths, ensuring global suppliers tailor portfolios to local constraints.

  1. Telefonaktiebolaget LM Ericsson
  2. Huawei Technologies Co., Ltd.
  3. Nokia Corporation
  4. Samsung Electronics Co., Ltd.
  5. Cisco Systems, Inc.
  6. Juniper Networks, Inc.
  7. ZTE Corporation
  8. NEC Corporation
  9. Mavenir Systems, Inc.
  10. Parallel Wireless, Inc.
  11. Airspan Networks Holdings Inc.
  12. Rakuten Symphony Singapore Pte. Ltd.
  13. Amdocs Limited
  14. Netcracker Technology Corporation
  15. Ribbon Communications Inc.
  16. Casa Systems, Inc.
  17. Radisys Corporation
  18. Ciena Corporation
  19. VIAVI Solutions Inc.
  20. EXFO Inc.
  21. TEOCO Corporation
  22. Subex Limited
  23. Intracom S.A. Telecom Solutions
  24. MATRIXX Software, Inc.
  25. Sandvine Corporation
  26. DeepSig, Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Rising 5G/6G network complexity driving autonomous orchestration
    • 4.2.2 Surging data traffic and need for predictive network optimisation
    • 4.2.3 Growing demand for churn-reducing customer analytics
    • 4.2.4 Operator CAPEX shift toward AI-powered Open RAN and vRAN roll-outs
    • 4.2.5 Emergence of sovereign AI data-centres operated by telcos
    • 4.2.6 Adoption of agentic AI for autonomous field-service operations
  • 4.3 Market Restraints
    • 4.3.1 Data-privacy and regulatory hurdles for telco AI initiatives
    • 4.3.2 Acute shortage of telecom-grade AI talent
    • 4.3.3 Escalating inference energy costs at network edge
    • 4.3.4 Vendor lock-in risk in proprietary AI-native network stacks
  • 4.4 Value Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Threat of New Entrants
    • 4.7.2 Bargaining Power of Suppliers
    • 4.7.3 Bargaining Power of Buyers
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Intensity Competitive Rivalry
  • 4.8 Impact of Macroeconomic Factors on the Market

5 MARKET SIZE AND GROWTH FORECASTS (VALUES)

  • 5.1 By Component
    • 5.1.1 Solutions/Platforms
    • 5.1.2 Services
  • 5.2 By Deployment Mode
    • 5.2.1 Cloud
    • 5.2.2 On-premises
    • 5.2.3 Edge/MEC
  • 5.3 By Application
    • 5.3.1 Customer Analytics
    • 5.3.2 Network Optimisation and Orchestration
    • 5.3.3 Fraud and Security Management
    • 5.3.4 Virtual Assistants and CX Automation
    • 5.3.5 Predictive Maintenance
    • 5.3.6 Other Applications
  • 5.4 By Network Domain
    • 5.4.1 Core Network
    • 5.4.2 Radio Access Network (RAN)
    • 5.4.3 Transport/Backhaul
    • 5.4.4 OSS/BSS
  • 5.5 By AI Technology
    • 5.5.1 Machine Learning
    • 5.5.2 Natural Language Processing
    • 5.5.3 Deep Learning
    • 5.5.4 Generative AI
    • 5.5.5 Reinforcement Learning
  • 5.6 By Geography
    • 5.6.1 North America
      • 5.6.1.1 United States
      • 5.6.1.2 Canada
      • 5.6.1.3 Mexico
    • 5.6.2 South America
      • 5.6.2.1 Brazil
      • 5.6.2.2 Argentina
      • 5.6.2.3 Chile
      • 5.6.2.4 Rest of South America
    • 5.6.3 Europe
      • 5.6.3.1 Germany
      • 5.6.3.2 United Kingdom
      • 5.6.3.3 France
      • 5.6.3.4 Italy
      • 5.6.3.5 Spain
      • 5.6.3.6 Rest of Europe
    • 5.6.4 Asia-Pacific
      • 5.6.4.1 China
      • 5.6.4.2 Japan
      • 5.6.4.3 India
      • 5.6.4.4 South Korea
      • 5.6.4.5 Australia
      • 5.6.4.6 Singapore
      • 5.6.4.7 Malaysia
      • 5.6.4.8 Rest of Asia-Pacific
    • 5.6.5 Middle East and Africa
      • 5.6.5.1 Middle East
        • 5.6.5.1.1 Saudi Arabia
        • 5.6.5.1.2 United Arab Emirates
        • 5.6.5.1.3 Turkey
        • 5.6.5.1.4 Rest of Middle East
      • 5.6.5.2 Africa
        • 5.6.5.2.1 South Africa
        • 5.6.5.2.2 Nigeria
        • 5.6.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
    • 6.4.1 Telefonaktiebolaget LM Ericsson
    • 6.4.2 Huawei Technologies Co., Ltd.
    • 6.4.3 Nokia Corporation
    • 6.4.4 Samsung Electronics Co., Ltd.
    • 6.4.5 Cisco Systems, Inc.
    • 6.4.6 Juniper Networks, Inc.
    • 6.4.7 ZTE Corporation
    • 6.4.8 NEC Corporation
    • 6.4.9 Mavenir Systems, Inc.
    • 6.4.10 Parallel Wireless, Inc.
    • 6.4.11 Airspan Networks Holdings Inc.
    • 6.4.12 Rakuten Symphony Singapore Pte. Ltd.
    • 6.4.13 Amdocs Limited
    • 6.4.14 Netcracker Technology Corporation
    • 6.4.15 Ribbon Communications Inc.
    • 6.4.16 Casa Systems, Inc.
    • 6.4.17 Radisys Corporation
    • 6.4.18 Ciena Corporation
    • 6.4.19 VIAVI Solutions Inc.
    • 6.4.20 EXFO Inc.
    • 6.4.21 TEOCO Corporation
    • 6.4.22 Subex Limited
    • 6.4.23 Intracom S.A. Telecom Solutions
    • 6.4.24 MATRIXX Software, Inc.
    • 6.4.25 Sandvine Corporation
    • 6.4.26 DeepSig, Inc.

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

  • 7.1 White-space and Unmet-Need Assessment