Summary

The AI in network market is estimated at USD 8.38 billion in 2026 and will reach USD 21.52 billion by 2032, at a CAGR of 17.0%. Market growth is driven by the increasing adoption of AI-powered network automation, 5G, edge computing, cloud infrastructure, and IoT. AI enables real-time network optimization, predictive maintenance, anomaly detection, automated troubleshooting, and enhanced cybersecurity, helping organizations improve network performance, reduce downtime, optimize resources, and lower operational costs. Rising investments in digital infrastructure and demand for reliable, low-latency connectivity are further accelerating adoption. Asia Pacific is expected to register the highest growth rate, supported by rapid 5G deployment, expanding cloud and edge infrastructure, and digital transformation initiatives. Adoption is expected to accelerate across telecom, enterprises, data centers, and public-sector organizations as networks shift toward more autonomous, intelligent operations. By network type, data center networks are expected to hold the largest market share during the forecast period. Data center networks are expected to account for the largest market share in the AI in network market, driven by the rapid adoption of AI workloads, cloud computing, and high-performance computing across enterprises and hyperscalers. AI applications require high-bandwidth, low-latency, and highly scalable network infrastructure to transfer large datasets and enable communication among GPUs, servers, and storage systems. AI-driven network solutions enable data centers to optimize traffic management, automate network operations, predict and resolve performance issues, and improve resource utilization. The growing deployment of generative AI, machine learning, and accelerated computing is further increasing demand for intelligent networking capabilities within data centers. As organizations continue to expand AI infrastructure and invest in next-generation data centers, the need for AI-enabled network monitoring, optimization, security, and automation is expected to sustain data center networks' leading market position during the forecast period. The cloud networks segment is expected to register the fastest growth rate during the forecast period. Cloud networks provide scalable, flexible connectivity across cloud environments, data centers, branch locations, and edge infrastructure. As enterprises accelerate cloud migration and adopt hybrid and multicloud architectures, demand is increasing for AI-enabled solutions that offer real-time network visibility, automated configuration, intelligent traffic management, and predictive performance optimization. AI helps analyze network data, detect anomalies, optimize resources, and automate operations, improving network reliability and efficiency. Growing cloud-native application adoption, multicloud complexity, and the need for seamless, secure connectivity are driving enterprises toward AI-driven cloud networking solutions. As organizations prioritize scalable, autonomous, and resilient cloud infrastructure, demand for AI-enabled cloud networks is expected to grow rapidly, making this the fastest-growing segment in the AI in network market during the forecast period. Asia Pacific will register the highest growth rate during the forecast period. The Asia Pacific region is witnessing rapid digital transformation, expanding 5G infrastructure, cloud adoption, and increasing demand for intelligent network management, driving strong growth in the AI in network market. Countries such as China, India, Japan, South Korea, and Australia are investing in advanced telecommunications infrastructure, data centers, and cloud networks to support growing data traffic and connected devices. Telecom operators and enterprises are increasingly adopting AI-powered network solutions for predictive maintenance, network optimization, traffic management, anomaly detection, and automated operations. In addition, the proliferation of IoT, edge computing, and 5G networks is generating large volumes of network data, creating opportunities for AI-driven analytics and automation. Supportive government initiatives promoting digitalization, smart infrastructure, and next-generation connectivity are further accelerating AI adoption across the region. Together, these factors position Asia Pacific as the fastest-growing regional market for AI in networks during the forecast period. Breakdown of primaries The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The breakdown of primaries is as follows: ・By Company Type: Tier 1 (34%), Tier 2 (43%), and Tier 3 (23%) ・By Designation: C-level Executives (50%), Directors (30%), and Others (20%) ・By Region: North America (25%), Europe (30%), Asia Pacific (30%), Middle East & Africa (10%), and Latin America (5%) The major players in the AI in network market are Cisco (US), HPE (US), Nokia (Finland), Ericsson (Sweden), Huawei (China), Arista Networks (US), NVIDIA (US), Extreme Networks (US), Broadcom (US), IBM (US), Fujitsu (Japan), Dell Technologies (US), Ciena (US), NEC (Japan), Forward Networks (US), BlueCat Networks (Canada), A10 Networks (US), ScienceLogic (US), Versa Networks (US), Dynatrace (US), Infoblox (US), EfficientIP (France), Riverbed (US), NETSCOUT (US), SolarWinds (US), NetBrain (US), ManageEngine (US), VIAVI Solutions (US), Selector (US), Aviz Networks (US), Nile (US), NetBox Labs (US), Celona (US), Shabodi (Canada), and A5G Networks (US). Research Coverage The market study covers the AI in network market size across different segments. It aims to estimate market size and growth potential across segments, including offering, network type, end user, and regions. The study includes an in-depth competitive analysis of leading market players, including company profiles, key observations on product and business offerings, recent developments, and market strategies. Key Benefits of Buying the Report The report will help market leaders/new entrants with information on the closest approximations of the global AI in network market's revenue numbers and subsegments. This report will help stakeholders understand the competitive landscape and gain insights to better position their businesses and plan suitable go-to-market strategies. Moreover, the report will help stakeholders understand the market's pulse and provide information on key market drivers, restraints, challenges, and opportunities. The report provides insights on the following pointers: Analysis of key drivers (AI agent proliferation increasing DNS/IP demand; growing adoption of AI, generative AI, and AI agents for network operations and automation; rising complexity and changing traffic patterns driven by AI workloads; and growing focus on autonomous, self-optimizing, and closed-loop networks), restraints (lack of explainability and trust in AI-driven network decisions and high complexity of integrating AI with legacy network infrastructure), opportunities (growing adoption of generative and agentic AI for autonomous network operations and expansion of AI-powered network management across cloud, edge, and 5G environments), and challenges (ensuring high-quality, reliable, and secure network data for AI models and managing cybersecurity, data governance, and operational risks). Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product and service launches in the AI in network market. Market Development: Comprehensive information on lucrative markets; the report analyzes AI in network markets across various regions. Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the AI in network market. Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players like Cisco (US), HPE (US), Nokia (Finland), Ericsson (Sweden), Huawei (China), Arista Networks (US), NVIDIA (US), Extreme Networks (US), Broadcom (US), IBM (US), Fujitsu (Japan), Dell Technologies (US), Ciena (US), NEC (Japan), Forward Networks (US), BlueCat Networks (Canada), A10 Networks (US), ScienceLogic (US), Versa Networks (US), Dynatrace (US), Infoblox (US), EfficientIP (France), Riverbed (US), NETSCOUT (US), SolarWinds (US), NetBrain (US), ManageEngine (US), VIAVI Solutions (US), Selector (US), Aviz Networks (US), Nile (US), NetBox Labs (US), Celona (US), Shabodi (Canada), and A5G Networks (US).

ページTOPに戻る

Table of Contents

1 INTRODUCTION 33
1.1 STUDY OBJECTIVES 33
1.2 MARKET DEFINITION 33
1.3 MARKET SCOPE 34
1.3.1 MARKET SEGMENTATION AND REGIONAL SCOPE 34
1.3.2 INCLUSIONS AND EXCLUSIONS 35
1.4 YEARS CONSIDERED 35
1.5 CURRENCY CONSIDERED 35
1.6 STAKEHOLDERS 36
2 EXECUTIVE SUMMARY 37
2.1 MARKET HIGHLIGHTS AND KEY INSIGHTS 37
2.2 KEY MARKET PARTICIPANTS: MAPPING OF STRATEGIC DEVELOPMENTS 39
2.3 DISRUPTIVE TRENDS IN AI IN NETWORK MARKET 40
2.4 HIGH-GROWTH SEGMENTS 41
2.5 REGIONAL SNAPSHOT: MARKET SIZE, GROWTH RATE, AND FORECAST 42
3 PREMIUM INSIGHTS 43
3.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN NETWORK MARKET 43
3.2 AI IN NETWORK MARKET, BY SERVICE AND REGION 44
3.3 AI IN NETWORK MARKET, BY OFFERING 44
3.4 AI IN NETWORK MARKET, BY END USER 45
4 MARKET OVERVIEW AND INDUSTRY TRENDS 46
4.1 INTRODUCTION 46
4.2 MARKET DYNAMICS 46
4.2.1 DRIVERS 47
4.2.1.1 AI agent proliferation increasing DNS/IP demand 47
4.2.1.2 Growing adoption of AI, generative AI, and AI agents for network operations and automation 48
4.2.1.3 Rising complexity and changing traffic patterns driven by AI workloads 48
4.2.1.4 Increasing focus on autonomous, self-optimizing, and closed-loop networks 48
4.2.2 RESTRAINTS 49
4.2.2.1 Lack of explainability and trust in AI-driven network decisions 49
4.2.2.2 High complexity of integrating AI with legacy network infrastructure 49
4.2.3 OPPORTUNITIES 49
4.2.3.1 Expansion of autonomous and intent-based networking enabled by AI 49
4.2.3.2 Expansion of AI-powered network management across cloud, edge, and 5G environments 50
4.2.4 CHALLENGES 50
4.2.4.1 Ensuring high-quality, reliable, and secure network data for AI models 50
4.2.4.2 Managing cybersecurity, data governance, and operational risks 50
4.3 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES 51
4.3.1 CLOUD COMPUTING AND DATA CENTER MARKET 51
4.3.2 INTERNET OF THINGS (IOT) MARKET 51
4.3.3 CYBERSECURITY MARKET 51
4.3.4 TELECOMMUNICATIONS AND 5G MARKET 51
4.3.5 HEALTHCARE AND LIFE SCIENCES 52
4.3.6 MANUFACTURING AND INDUSTRIAL AUTOMATION 52
4.3.7 TRANSPORTATION AND SMART MOBILITY 52
4.3.8 ENERGY AND UTILITIES 52
4.3.9 RETAIL AND SMART ENTERPRISE 53
4.4 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS 53
5 INDUSTRY TRENDS 55
5.1 PORTER’S FIVE FORCES ANALYSIS 55
5.1.1 THREAT OF NEW ENTRANTS 56
5.1.2 THREAT OF SUBSTITUTES 56
5.1.3 BARGAINING POWER OF SUPPLIERS 57
5.1.4 BARGAINING POWER OF BUYERS 57
5.1.5 INTENSITY OF COMPETITIVE RIVALRY 57
5.2 MACROECONOMICS INDICATORS 58
5.2.1 INTRODUCTION 58
5.2.2 GDP TRENDS AND FORECAST 58
5.2.3 TRENDS IN TELECOMMUNICATIONS INDUSTRY 60
5.2.4 TRENDS IN DATA CENTER & CLOUD INFRASTRUCTURE INDUSTRY 60
5.3 SUPPLY CHAIN ANALYSIS 60
5.4 ECOSYSTEM ANALYSIS 63
5.5 PRICING ANALYSIS 65
5.5.1 AVERAGE SELLING PRICE OF AI-ENABLED NETWORK MANAGEMENT PLATFORMS, BY KEY PLAYERS 66
5.5.2 INDICATIVE PRICING ANALYSIS OF KEY PLAYERS, BY SOLUTION, 2025 66
5.6 KEY CONFERENCES AND EVENTS, 2026–2027 68
5.7 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 69
5.8 INVESTMENT AND FUNDING SCENARIO 69
5.9 CASE STUDY ANALYSIS 70
5.9.1 CISCO'S SELF-DEFENDING NETWORK FOR AI-DRIVEN SECURITY 70
5.9.2 NOKIA AI-POWERED AUTONOMOUS RAN OPERATIONS FOR STC 70
5.9.3 ERICSSON AI-DRIVEN NETWORK OPTIMIZATION FOR AT&T 71
5.9.4 SHABODI ENABLES AI-DRIVEN COGNITIVE FACTORY FOR GLOBAL MANUFACTURER 72
5.9.5 AVIZ NETWORKS BUILDS AI-READY NETWORK FOR GLOBAL E-COMMERCE 72
5.10 IMPACT OF 2025 US TARIFF – AI IN NETWORK MARKET 73
5.10.1 INTRODUCTION 73
5.10.2 KEY TARIFF RATES 74
5.10.3 PRICE IMPACT ANALYSIS 75
5.10.3.1 Strategic shifts and emerging trends 75
5.10.4 IMPACT ON COUNTRIES/REGIONS 76
5.10.4.1 US 76
5.10.4.2 Europe 76
5.10.4.3 Asia Pacific 76
5.10.5 IMPACT ON END-USER INDUSTRIES 76
5.10.5.1 Enterprises 76
5.10.5.2 Telecom & communication service providers 77
5.10.5.3 Government & defense 77
6 TECHNOLOGICAL ADVANCEMENTS, AI-DRIVEN IMPACT, PATENTS, INNOVATIONS, AND FUTURE APPLICATIONS 78
6.1 KEY EMERGING TECHNOLOGIES 78
6.1.1 ARTIFICIAL INTELLIGENCE (AI) 78
6.1.2 MACHINE LEARNING (ML) 78
6.1.3 GENERATIVE AI (GEN AI) AND LARGE LANGUAGE MODELS (LLMS) 79
6.1.4 AGENTIC AI 79
6.1.5 AI-NATIVE NETWORK AUTOMATION AND AUTONOMOUS NETWORKING 79
6.1.6 COMPLEMENTARY TECHNOLOGIES 79
6.1.6.1 Edge computing 79
6.1.6.2 Cloud computing 80
6.1.6.3 Network telemetry and observability 80
6.1.6.4 5G and 6G connectivity 80
6.1.7 ADJACENT TECHNOLOGIES 80
6.1.7.1 Digital twins 80
6.1.7.2 Internet of Things (IoT) 80
6.1.7.3 Intent-based networking (IBN) 81
6.1.7.4 Zero-touch network management 81
6.2 TECHNOLOGY/PRODUCT ROADMAP 81
6.2.1 SHORT-TERM ROADMAP (2026–2027) 81
6.2.2 MID-TERM ROADMAP (2028–2029) 82
6.2.3 LONG-TERM ROADMAP (2030–2032) 82
6.3 PATENT ANALYSIS 83
6.4 IMPACT OF AI/GEN AI ON AI IN NETWORK MARKET 86
6.4.1 TOP USE CASES AND MARKET POTENTIAL 86
6.4.2 BEST PRACTICES IN AI IN NETWORK PROCESS 87
6.4.3 CASE STUDIES OF AI IMPLEMENTATION IN AI IN NETWORK MARKET 88
6.4.4 INTERCONNECTED ADJACENT ECOSYSTEM AND IMPACT ON MARKET PLAYERS 89
6.4.5 CLIENTS’ READINESS TO ADOPT GENERATIVE AI IN AI IN NETWORK 89
7 REGULATORY LANDSCAPE 90
7.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 90
7.2 INDUSTRY STANDARDS 94
8 CUSTOMER LANDSCAPE AND BUYING BEHAVIOR 96
8.1 DECISION-MAKING PROCESS 96
8.2 KEY STAKEHOLDERS INVOLVED IN BUYING PROCESS AND THEIR EVALUATION CRITERIA 97
8.2.1 KEY STAKEHOLDERS IN BUYING PROCESS 97
8.2.2 BUYING CRITERIA 98
8.3 ADOPTION BARRIERS AND INTERNAL CHALLENGES 99
8.4 UNMET NEEDS FROM VARIOUS END-USE INDUSTRIES 99
9 AI IN NETWORK MARKET, BY OFFERING 100
9.1 INTRODUCTION 101
9.1.1 OFFERING: AI IN NETWORK MARKET DRIVERS 101
9.2 SOLUTIONS 103
9.2.1 ENABLING INTELLIGENT, AUTOMATED, AND AUTONOMOUS NETWORK OPERATIONS 103
9.2.2 AI-DRIVEN NETWORK MANAGEMENT 105
9.2.2.1 Network monitoring & management 106
9.2.2.2 Network observability 106
9.2.2.3 DDI 107
9.2.2.4 Fault management 107
9.2.2.5 Performance management 107
9.2.3 AI-DRIVEN NETWORK OPTIMIZATION 108
9.2.3.1 Traffic optimization 109
9.2.3.2 Capacity optimization 109
9.2.3.3 Predictive performance analytics 109
9.2.3.4 Observability-driven optimization 110
9.2.4 AI-DRIVEN NETWORK SECURITY 110
9.2.4.1 Network policy & risk analytics 111
9.2.4.2 DNS security 111
9.2.4.3 Anomaly detection 112
9.2.4.4 Threat detection & response 112
9.2.5 AI-DRIVEN NETWORK AUTOMATION 112
9.2.5.1 Configuration automation 113
9.2.5.2 Provisioning automation 114
9.2.5.3 Policy automation 114
9.2.5.4 Closed-loop automation 114
9.2.5.5 DDI automation 115
9.2.6 AI-DRIVEN NETWORK ORCHESTRATION 115
9.2.6.1 Multi-domain network orchestration 116
9.2.6.2 Service orchestration 116
9.2.6.3 Intent-based orchestration 117
9.2.6.4 Autonomous network orchestration 117
9.2.7 AI-DRIVEN NETWORK PLANNING & DESIGN 117
9.2.7.1 Capacity planning & forecasting 118
9.2.7.2 Network architecture & topology design 119
9.2.7.3 Network simulation & digital twin 119
9.2.8 OTHER SOLUTIONS 119
9.3 SERVICES 120
9.3.1 ENABLING AI-DRIVEN NETWORK TRANSFORMATION AND AUTONOMOUS OPERATIONS 120
9.3.2 PROFESSIONAL SERVICES 122
9.3.2.1 Consulting & advisory 123
9.3.2.2 Integration & deployment 124
9.3.2.3 Support & maintenance 125
9.3.3 MANAGED SERVICES 126
10 AI IN NETWORK MARKET, BY NETWORK TYPE 128
10.1 INTRODUCTION 129
10.1.1 NETWORK TYPE: AI IN NETWORK MARKET DRIVERS 129
10.2 DATA CENTER NETWORKS 131
10.2.1 AI-DRIVEN OPTIMIZATION OF HIGH-PERFORMANCE INFRASTRUCTURE 131
10.3 CLOUD NETWORKS 132
10.3.1 AI-ENABLED MANAGEMENT OF DISTRIBUTED CLOUD INFRASTRUCTURE 132
10.4 WIRELESS NETWORKS 133
10.4.1 AI-DRIVEN OPTIMIZATION OF NEXT-GENERATION CONNECTIVITY 133
10.5 SOFTWARE-DEFINED WIDE AREA NETWORKS (SD-WAN) 134
10.5.1 AI-ENABLED INTELLIGENT TRAFFIC MANAGEMENT 134
10.6 CAMPUS NETWORKS 135
10.6.1 AI-DRIVEN NETWORK AUTOMATION AND PERFORMANCE MANAGEMENT 135
10.7 OTHER NETWORK TYPES 136
11 AI IN NETWORK MARKET, BY END USER 138
11.1 INTRODUCTION 139
11.1.1 END USER: AI IN NETWORK MARKET DRIVERS 139
11.2 SERVICE PROVIDERS 141
11.2.1 INCREASING ADOPTION OF AI TO ENABLE AUTONOMOUS AND INTELLIGENT NETWORK OPERATIONS 141
11.3 ENTERPRISES 142
11.3.1 GROWING DEPLOYMENT OF AI-DRIVEN NETWORKS TO ENHANCE OPERATIONAL EFFICIENCY, SECURITY, AND CONNECTIVITY 142
11.3.2 BFSI 144
11.3.3 HEALTHCARE 145
11.3.4 RETAIL & E-COMMERCE 146
11.3.5 MANUFACTURING 147
11.3.6 GOVERNMENT & DEFENSE 148
11.3.7 ENERGY & UTILITIES 149
11.3.8 OTHER ENTERPRISES 150
12 AI IN NETWORK MARKET, BY REGION 151
12.1 INTRODUCTION 152
12.2 NORTH AMERICA 153
12.2.1 NORTH AMERICA: AI IN NETWORK MARKET DRIVERS 153
12.2.2 US 158
12.2.2.1 Strong AI infrastructure investments driving autonomous and AI-native networks 158
12.2.3 CANADA 163
12.2.3.1 Sovereign AI infrastructure and 5G modernization supporting intelligent networks 163
12.3 EUROPE 167
12.3.1 EUROPE: AI IN NETWORK MARKET DRIVERS 167
12.3.2 UK 172
12.3.2.1 AI-enabled network automation and growing demand for intelligent connectivity 172
12.3.3 GERMANY 177
12.3.3.1 Industry 4.0 and autonomous network operations driving AI adoption 177
12.3.4 ITALY 181
12.3.4.1 5G modernization and industrial digitalization accelerating AI in networks 181
12.3.5 FRANCE 185
12.3.5.1 AI-native communications and digital sovereignty strengthening network intelligence 185
12.3.6 REST OF EUROPE 190
12.4 ASIA PACIFIC 190
12.4.1 ASIA PACIFIC: AI IN NETWORK MARKET DRIVERS 190
12.4.2 CHINA 196
12.4.2.1 Government-led AI integration and extensive 5G infrastructure driving autonomous networks 196
12.4.3 INDIA 200
12.4.3.1 Rapid 5G expansion and high data consumption fueling AI-driven network optimization 200
12.4.4 JAPAN 205
12.4.4.1 Advanced telecom infrastructure and AI automation supporting next-generation networks 205
12.4.5 REST OF ASIA PACIFIC 209
12.5 MIDDLE EAST & AFRICA 209
12.5.1 MIDDLE EAST & AFRICA: AI IN NETWORK MARKET DRIVERS 209
12.5.2 UAE 215
12.5.2.1 Sovereign AI and advanced 5G infrastructure accelerating AI-native network development 215
12.5.3 KSA 219
12.5.3.1 Vision 2030 and AI infrastructure investments driving intelligent connectivity 219
12.5.4 SOUTH AFRICA 223
12.5.4.1 5G Expansion and Digital Infrastructure Investment Supporting AI-Enabled Networks 223
12.5.5 REST OF MIDDLE EAST & AFRICA 227
12.6 LATIN AMERICA 228
12.6.1 LATIN AMERICA: AI IN NETWORK MARKET DRIVERS 228
12.6.2 BRAZIL 233
12.6.2.1 5G densification and operator automation driving adoption of AI in network 233
12.6.3 MEXICO 237
12.6.3.1 5G expansion and industrial digitalization supporting intelligent network growth 237
12.6.4 REST OF LATIN AMERICA 241
13 COMPETITIVE LANDSCAPE 242
13.1 INTRODUCTION 242
13.2 KEY PLAYER COMPETITIVE STRATEGIES/RIGHT TO WIN, 2023–2026 242
13.3 MARKET SHARE ANALYSIS, 2025 244
13.4 REVENUE ANALYSIS, 2021–2025 248
13.5 BRAND/PRODUCT COMPARISON 249
13.6 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2025 250
13.6.1 STARS 250
13.6.2 EMERGING LEADERS 250
13.6.3 PERVASIVE PLAYERS 250
13.6.4 PARTICIPANTS 250
13.6.5 COMPANY FOOTPRINT: KEY PLAYERS, 2025 252
13.6.5.1 Company footprint 252
13.6.5.2 Region footprint 253
13.6.5.3 Offering footprint 254
13.6.5.4 Solution footprint 255
13.6.5.5 Service footprint 256
13.6.5.6 Network type footprint 257
13.6.5.7 End user footprint 258
13.7 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2025 259
13.7.1 PROGRESSIVE COMPANIES 259
13.7.2 RESPONSIVE COMPANIES 259
13.7.3 DYNAMIC COMPANIES 259
13.7.4 STARTING BLOCKS 259
13.7.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2025 261
13.7.5.1 Detailed list of key startups/SMEs 261
13.7.5.2 Competitive benchmarking of key startups/SMEs 262
13.8 COMPANY VALUATION AND FINANCIAL METRICS 262
13.9 COMPETITIVE SCENARIO 264
13.9.1 PRODUCT LAUNCHES/ENHANCEMENTS 264
13.9.2 DEALS 274
14 COMPANY PROFILES 281
14.1 MAJOR PLAYERS 281
14.1.1 CISCO 281
14.1.1.1 Business overview 281
14.1.1.2 Products/Solutions/Services offered 282
14.1.1.3 Recent developments 283
14.1.1.3.1 Product launches/enhancements 283
14.1.1.3.2 Deals 286
14.1.1.4 MnM view 287
14.1.1.4.1 Right to win 287
14.1.1.4.2 Strategic choices 287
14.1.1.4.3 Weaknesses and competitive threats 288
14.1.2 HPE 289
14.1.2.1 Business overview 289
14.1.2.2 Products/Solutions/Services offered 290
14.1.2.3 Recent developments 291
14.1.2.3.1 Product launches/enhancements 291
14.1.2.3.2 Deals 292
14.1.2.4 MnM view 293
14.1.2.4.1 Right to win 293
14.1.2.4.2 Strategic choices 293
14.1.2.4.3 Weaknesses and competitive threats 293
14.1.3 NOKIA 294
14.1.3.1 Business overview 294
14.1.3.2 Products/Solutions/Services offered 295
14.1.3.3 Recent developments 297
14.1.3.3.1 Product launches/enhancements 297
14.1.3.3.2 Deals 298
14.1.3.4 MnM view 300
14.1.3.4.1 Right to win 300
14.1.3.4.2 Strategic choices 300
14.1.3.4.3 Weaknesses and competitive threats 300
14.1.4 HUAWEI 301
14.1.4.1 Business overview 301
14.1.4.2 Products/Solutions/Services offered 302
14.1.4.3 Recent developments 303
14.1.4.3.1 Product launches/enhancements 303
14.1.4.3.2 Deals 305
14.1.4.3.3 Other developments 306
14.1.4.4 MnM view 306
14.1.4.4.1 Right to win 306
14.1.4.4.2 Strategic choices 306
14.1.4.4.3 Weaknesses and competitive threats 307
14.1.5 ERICSSON 308
14.1.5.1 Business overview 308
14.1.5.2 Products/Solutions/Services offered 309
14.1.5.3 Recent developments 311
14.1.5.3.1 Product launches/enhancements 311
14.1.5.3.2 Deals 311
14.1.5.3.3 Other developments 313
14.1.5.4 MnM view 313
14.1.5.4.1 Right to win 313
14.1.5.4.2 Strategic choices 313
14.1.5.4.3 Weaknesses and competitive threats 314
14.1.6 ARISTA NETWORKS 315
14.1.6.1 Business overview 315
14.1.6.2 Products/Solutions/Services offered 316
14.1.6.3 Recent developments 317
14.1.6.3.1 Product launches/enhancements 317
14.1.6.3.2 Deals 318
14.1.7 NVIDIA 319
14.1.7.1 Business overview 319
14.1.7.2 Products/Solutions/Services offered 320
14.1.7.3 Recent developments 321
14.1.7.3.1 Product launches/enhancements 321
14.1.7.3.2 Deals 322
14.1.8 DYNATRACE 324
14.1.8.1 Business overview 324
14.1.8.2 Products/Solutions/Services offered 326
14.1.9 IBM 327
14.1.9.1 Business overview 327
14.1.9.2 Products/Solutions/Services offered 328
14.1.9.3 Recent developments 329
14.1.9.3.1 Product launches/enhancements 329
14.1.9.3.2 Deals 329
14.1.10 INFOBLOX 330
14.1.10.1 Business overview 330
14.1.10.2 Products/Solutions/Services offered 330
14.1.10.3 Recent developments 332
14.1.10.3.1 Product launches/enhancements 332
14.1.10.3.2 Deals 333
14.2 OTHER PLAYERS 334
14.2.1 BROADCOM 334
14.2.2 FUJITSU 335
14.2.3 DELL TECHNOLOGIES 336
14.2.4 NEC 337
14.2.5 A10 NETWORKS 338
14.2.6 SCIENCELOGIC 339
14.2.7 CIENA 340
14.2.8 EXTREME NETWORKS 341
14.2.9 EFFICIENTIP 342
14.2.10 RIVERBED 343
14.2.11 NETSCOUT 344
14.2.12 SOLARWINDS 345
14.2.13 NETBRAIN 346
14.2.14 MANAGEENGINE 347
14.2.15 VIAVI 348
14.3 SMES/STARTUPS 349
14.3.1 FORWARD NETWORKS 349
14.3.2 BLUECAT NETWORKS 350
14.3.3 VERSA NETWORKS 351
14.3.4 SELECTOR 352
14.3.5 AVIZ NETWORKS 353
14.3.6 NILE 354
14.3.7 NETBOX LABS 355
14.3.8 CELONA 356
14.3.9 SHABODI 357
14.3.10 A5G NETWORKS 358
15 RESEARCH METHODOLOGY 359
15.1 RESEARCH DATA 359
15.1.1 SECONDARY DATA 360
15.1.2 PRIMARY DATA 360
15.1.2.1 Primary interviews with experts 361
15.1.2.2 Breakdown of primary profiles 361
15.1.2.3 Key data from primary sources 362
15.1.2.4 Key industry insights 362
15.2 MARKET BREAKUP AND DATA TRIANGULATION 363
15.3 MARKET SIZE ESTIMATION 363
15.3.1 TOP-DOWN APPROACH 365
15.3.2 BOTTOM-UP APPROACH 366
15.4 MARKET FORECAST 367
15.4.1 FACTOR ANALYSIS 367
15.5 RESEARCH ASSUMPTIONS 367
15.6 RESEARCH LIMITATIONS 367
16 APPENDIX 368
16.1 DISCUSSION GUIDE 368
16.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 372
16.3 CUSTOMIZATION OPTIONS 374
16.4 RELATED REPORTS 374
16.5 AUTHOR DETAILS 375