AI 슈퍼컴퓨팅 플랫폼 시장(2026-2032년) : 기술, 솔루션, 산업, 사용 사례별

Overview:

The AI supercomputing landscape is experiencing a massive transformation, fueled by the rise of generative AI, next-gen HBM, agentic workflows, and ultra-efficient, gigawatt-scale liquid-cooled infrastructure. This relentless push for raw computational power has ultimately forced a fundamental redesign of the physical environment, shifting the industry away from traditional air-cooled facilities toward highly efficient, liquid-cooled data centers.

Operating at an unprecedented gigawatt scale, these next-generation facilities are rapidly becoming the foundational backbone necessary to sustain the future of global artificial intelligence.

The market is undergoing explosive growth as artificial intelligence transitions from experimental technology to industrialized “AI factories” capable of training and deploying frontier-scale foundation models. These specialized platforms integrate high-density AI accelerators, ultra-high-speed interconnects, advanced memory systems, sophisticated orchestration software, and energy-efficient cooling solutions to deliver the massive computational power required for large-scale AI workloads.

The competitive landscape is highly dynamic, with NVIDIA maintaining strong dominance in accelerators and full-stack solutions, while AMD, Intel, hyperscaler custom silicon, and specialized players continue to challenge the status quo.

As organizations across industries increasingly view AI supercomputing as critical infrastructure rather than supporting technology, the market is expected to evolve from a hardware-centric focus toward greater emphasis on energy efficiency, software optimization, total cost of ownership, and sustainable operations by 2032.

This research provides a comprehensive analysis of the AI Supercomputing Platform Market from 2026 to 2032, segmented across multiple dimensions to offer a granular understanding of market dynamics.

This report covers the market by component (Hardware, Software, and Services), hardware sub-components (Processors/Compute, Storage, Memory, and Interconnects), processor types (GPU-Based, CPU-Based, TPU/ASIC-Based, FPGA-Based, Quantum-Enhanced, and Custom AI Accelerators), cooling technologies, computing architectures (Centralized, Modular Scale-Out, and Distributed), AI workload types, system scale (from below 100 PFLOPS to above 1 EFLOPS), deployment models (Cloud, On-Premise, and Hybrid), and key industry verticals.

Regional analysis includes detailed coverage of North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, along with focused insights on strategic groupings such as ASEAN, GCC, European Union, BRICS, G7, and NATO. This multi-layered segmentation enables stakeholders to identify high-growth opportunities, evaluate competitive dynamics, and make informed strategic decisions across the rapidly evolving AI supercomputing ecosystem.

Selection of Organizations Covered:

• Advanced Micro Devices, Inc.
• Amazon Web Services, Inc.
• Anthropic
• Apple
• Arista Networks
• Arm Ltd.
• Atos SE
• BlackRock
• BNY (Bank of New York Mellon)
• Bosch
• Bradesco
• Broadcom Inc. / Broadcom
• Cerebras Systems Inc. / Cerebras
• CERN
• Chinese Academy of Sciences
• Cisco Systems, Inc. / Cisco
• CoolIT
• Corintis
• CSC – IT Center for Science
• D1 Capital
• DDN (DataDirect Networks)
• DeepL
• Dell Technologies Inc. / Dell
• EcoDataCenter
• Eli Lilly and Company / Lilly
• Equinix
• EuroHPC Joint Undertaking
• Euronext Growth Paris
• Exor International
• FAIR (Fundamental AI Research) lab
• Fujitsu Limited / Fujitsu
• Goldman Sachs
• Google DeepMind / DeepMind
• Google LLC / Alphabet Inc. / Google Cloud
• Google Ventures
• Government, Defense, & Academic Institutions
• Graphcore
• GRC
• Groq Inc.
• Hewlett Packard Enterprise / Cray Inc.
• Hugging Face
• IBM Corporation
• Inflection
• Intel Corporation
• JMA Wireless
• JPMorgan
• Kalray
• Kenron Inc.
• Lambda
• Lawrence Livermore National Laboratory
• Lenovo
• LiquidStack
• Memorial Sloan-Kettering Cancer Center
• Meta Platforms, Inc.
• Micron Technology Inc.
• Microsoft Corporation
• MITRE
• Moloco
• NATO
• NEC Corporation / NEC
• NVIDIA Corporation / NVIDIA
• Oak Ridge National Laboratory / Oak Ridge National Labs
• OpenAI
• OptiCool
• Oracle Corporation / Oracle Cloud Infrastructure
• PEZY Group
• Red Hat
• SambaNova Systems Inc. / SAMBANOVA Systems
• Samsung Electronics Co., Ltd.
• Sequoia
• SK Hynix
• SoftBank Corp. / SoftBank
• Stanford University
• Sun Microsystems
• Super Micro Computer, Inc.
• Telecom Italia
• Tiger Global
• TSMC
• TurkuNLP group
• U.S. Department of Energy
• University of Florida
• University of Turku
• USPTO (United States Patent and Trademark Office)
• VAST Data
• Vertiv
• Walden International
• Wassenaar Arrangement
• xAI

Table of Contents

• 1.0 Executive Summary
• 1.1 Overview
• 1.2 CXO Perspective and Strategic Outlook
• 1.3 Market Segmentation & Coverage
• 1.4 Research Assumption & Limitation
• 1.5 Stakeholder Analysis
• 1.6 Research Methodology
  • 1.6.1 Primary vs. Secondary Research
  • 1.6.2 Forecasting Model
  • 1.6.3 Bottom-Up vs. Top-down Approach
  • 1.6.4 Data Validation
• 1.7 Research Objectives
• 1.8 Select Findings
• 2.0 Introduction
• 2.1 Understanding AI Supercomputing Platform and Key Features
  • 2.1.1 Key Features of AI Supercomputing Platforms
  • 2.1.2 General AI Computing vs. AI Supercomputing Platform
  • 2.1.3 High Performance Computing (HPC) vs. AI Supercomputing Platform
• 2.2 AI Supercomputing Platform Ecosystem Architecture, Technology Stack, and Ecosystem Maturity Model
  • 2.2.1 Ecosystem Architecture
  • 2.2.2 Technology Stack
  • 2.2.3 Ecosystem Maturity Model
• 2.3 Market Dynamic Analysis
  • 2.3.1 Market Growth Driver Analysis
  • 2.3.2 Market Restraints
  • 2.3.3 Market Opportunities
• 2.4 Value Chain Analysis
  • 2.4.1 Supercomputing Platform Providers
  • 2.4.2 Computing Hardware Manufacturer
  • 2.4.3 AI Companies
  • 2.4.4 IoT Companies
  • 2.4.5 Connectivity Providers
  • 2.4.6 Enterprises and Government
• 2.5 Regulatory Landscape Analysis
• 2.6 Patent Landscape Analysis
• 2.7 Porter's Five Forces Analysis
  • 2.7.1 Supplier Bargaining Power
  • 2.7.2 Buyer Bargaining Power
  • 2.7.3 Threat of Substitutes
  • 2.7.4 Threat of New Entrants
  • 2.7.5 Threat of Competitive Rivalry
• 2.8 Market Impact Analysis:
  • 2.8.1 Global vs. Regional
  • 2.8.2 Impact of Tariffs: United States vs. China vs. Germany vs. France
  • 2.8.3 Impact of Gen AI
  • 2.8.4 Impact of US-Iran War
• 2.9 Investment Paradigm Analysis
  • 2.9.1 R&D Expenditures Trend
  • 2.9.2 Mergers & Acquisitions Trends
  • 2.9.3 Joint Ventures Trend
  • 2.9.4 Return on Investment & Cost-Benefit Analysis
  • 2.9.5 Role of Venture Capital Firm
• 2.10 Distribution Channel Analysis
• 2.11 Pricing Trend Analysis
• 2.12 Key Industry Development
• 3.0 Technology and Application Analysis
• 3.1 AI Supercomputing Hardware Components and Processor Types
  • 3.1.1 Processors/Compute
    • 3.1.1.1 GPU-Based System
    • 3.1.1.2 CPU-Based System
    • 3.1.1.3 TPU / ASIC-Based System
    • 3.1.1.4 FPGA-Based System
    • 3.1.1.5 Quantum-Enhanced System
    • 3.1.1.6 Custom AI Chips/Accelerator
    • 3.1.1.7 Comparison among Processor/Compute Technologies
  • 3.1.2 Storage
  • 3.1.3 Memory
  • 3.1.4 Interconnects (ICs)
  • 3.1.5 Network Fabric
  • 3.1.6 Comparison among Hardware Components
• 3.2 AI Supercomputing Platform Software Type
  • 3.2.1 Low-Level System Software & Runtimes
  • 3.2.2 AI/ML Frameworks and Optimization Libraries
  • 3.2.3 Cluster Management, Orchestration & Scheduling
  • 3.2.4 MLOps, Monitoring & Workflow Tools
  • 3.2.5 Higher-Level Integrated Stacks & Platforms
  • 3.2.6 Comparison among Software Types
• 3.3 AI Supercomputing Cooling Technology
  • 3.3.1 Direct to Chip (D2C) liquid cooling
  • 3.3.2 Air cooling
  • 3.3.3 Immersion cooling
  • 3.3.4 Rear Door Heat Exchangers (RDHx)
  • 3.3.5 Emerging & Advanced Cooling Techniques
    • 3.3.5.1 Microfluidics & Microjet Impingement
    • 3.3.5.2 Underwater Data Centers
    • 3.3.5.3 Waste Heat Reuse
  • 3.3.6 Comparison among Cooling Technology
  • 3.3.7 Average Selling Price (ASP) of Cooling Technologies
• 3.4 AI Supercomputing Compute Architecture
  • 3.4.1 Centralized AI supercomputers
  • 3.4.2 Modular scale out AI clusters
  • 3.4.3 Distributed AI supercomputers
  • 3.4.4 Comparison among Compute Architecture Type
• 3.5 AI Supercomputing AI Workload
  • 3.5.1 Machine Learning and Deep Learning
  • 3.5.2 AI Training
  • 3.5.3 AI Inference
  • 3.5.4 Hybrid Workloads
  • 3.5.5 Comparison among AI Workload Types
• 3.6 AI Supercomputing Platform System Scale
  • 3.6.1 Below 100 PFLOPS
  • 3.6.2 100 PFLOPS to 500 PFLOPS
  • 3.6.3 500 PFLOPS to 1 EFLOPS
  • 3.6.4 Above 1 EFLOPS
  • 3.6.5 Comparison among AI Supercomputing Platform System Scale
• 3.7 AI Supercomputing Application Analysis
  • 3.7.1 AI model training
  • 3.7.2 AI inference
  • 3.7.3 Scientific research
  • 3.7.4 Drug discovery
  • 3.7.5 Autonomous systems
  • 3.7.6 Cybersecurity
  • 3.7.7 Climate and weather modeling
  • 3.7.8 Comparative Analysis of Key Applications
• 3.8 Case Study Analysis
  • 3.8.1 Lilly partners with NVIDIA to build AI Supercomputer for Medicine Discovery
  • 3.8.2 LUMI supercomputer AI Model Training Case
  • 3.8.3 Samsung AI Megafactory Case
  • 3.8.4 Moloco Ad Serving Platform Case with Google Cloud’s AI Hypercomputer
  • 3.8.5 US Lux AI Supercomputer case at Oak Ridge National Labs
  • 3.8.6 xAI colossus AI supercomputer Training Case
  • 3.8.7 NVIDIA SuperPOD deployments Case
  • 3.8.8 Lambda Hyperscaler clusters Case
  • 3.8.9 Memorial Sloan-Kettering Cancer Center and IBM Watsons Case
  • 3.8.10 Bradesco and IBM AI-enabled Computer System Case
  • 3.8.11 Exor International Collaboration Case with with Intel, Telecom Italia (TIM), and JMA wireless
• 3.9 AI Supercomputing Application in Industry Vertical
  • 3.9.1 Cloud & Hyperscale Providers
  • 3.9.2 Government & Defense
  • 3.9.3 Research & Academia
  • 3.9.4 Healthcare & Life Sciences
  • 3.9.5 Telecom & IT Services
  • 3.9.6 Finance & Banking
  • 3.9.7 Commercial
  • 3.9.8 Comparison of Applications among Industry Vertical
• 3.10 AI Supercomputing Regional Adoption Trend Analysis
  • 3.10.1 North America
  • 3.10.2 Europe
  • 3.10.3 Asia Pacific (APAC)
  • 3.10.4 Latin America
  • 3.10.5 Middle East & Africa (MEA)
  • 3.10.6 ASEAN
  • 3.10.7 GCC
  • 3.10.8 European Union
  • 3.10.9 BRICS
  • 3.10.10 G7
  • 3.10.11 NATO
  • 3.10.12 Comparison of Adoption Trend among Region
• 4.0 AI Supercomputing Company Analysis
• 4.1 Competitive Landscape Analysis
  • 4.1.1 Market Positioning Matrix
  • 4.1.2 Vendor Landscape Analysis
  • 4.1.3 Key Strategies Adopted by Market Players
  • 4.1.4 List of Suppliers vs. Buyers
• 4.2 Vendor Market Share Analysis
• 4.3 Vendor Analysis
  • 4.3.1 NVIDIA Corporation
    • 4.3.1.1 Company Overview
    • 4.3.1.2 Financial Overview
    • 4.3.1.3 Product & Offerings
    • 4.3.1.4 Key Market Strategy
    • 4.3.1.5 SWOT Analysis
  • 4.3.2 Intel Corporation
    • 4.3.2.1 Company Overview
    • 4.3.2.2 Financial Overview
    • 4.3.2.3 Product & Offerings
    • 4.3.2.4 Key Market Strategy
    • 4.3.2.5 SWOT Analysis
  • 4.3.3 Advanced Micro Devices, Inc.
    • 4.3.3.1 Company Overview
    • 4.3.3.2 Financial Overview
    • 4.3.3.3 Product & Offerings
    • 4.3.3.4 Key Market Strategy
    • 4.3.3.5 SWOT Analysis
  • 4.3.4 IBM Corporation
    • 4.3.4.1 Company Overview
    • 4.3.4.2 Financial Overview
    • 4.3.4.3 Product & Offering
    • 4.3.4.4 Key Market Strategy
    • 4.3.4.5 SWOT Analysis
  • 4.3.5 Hewlett Packard Enterprise
    • 4.3.5.1 Company Overview
    • 4.3.5.2 Financial Overview
    • 4.3.5.3 Product & Offering
    • 4.3.5.4 Key Market Strategy
    • 4.3.5.5 SWOT Analysis
  • 4.3.6 Dell Technologies Inc.
    • 4.3.6.1 Company Overview
    • 4.3.6.2 Financial Overview
    • 4.3.6.3 Product & Offering
    • 4.3.6.4 Key Market Strategy
    • 4.3.6.5 SWOT Analysis
  • 4.3.7 Microsoft Corporation
    • 4.3.7.1 Company Overview
    • 4.3.7.2 Financial Overview
    • 4.3.7.3 Product & Offering
    • 4.3.7.4 Key Market Strategy
    • 4.3.7.5 SWOT Analysis
  • 4.3.8 Amazon Web Services, Inc.
    • 4.3.8.1 Company Overview
    • 4.3.8.2 Financial Overview
    • 4.3.8.3 Product & Offering
    • 4.3.8.4 Key Market Strategy
    • 4.3.8.5 SWOT Analysis
  • 4.3.9 Google LLC (Alphabet Inc.)
    • 4.3.9.1 Company Overview
    • 4.3.9.2 Financial Overview
    • 4.3.9.3 Product & Offering
    • 4.3.9.4 Key Market Strategy
    • 4.3.9.5 SWOT Analysis
  • 4.3.10 Oracle Corporation
    • 4.3.10.1 Company Overview
    • 4.3.10.2 Financial Overview
    • 4.3.10.3 Product & Offering
    • 4.3.10.4 Key Market Strategy
    • 4.3.10.5 SWOT Analysis
  • 4.3.11 Fujitsu Limited
    • 4.3.11.1 Company Overview
    • 4.3.11.2 Financial Overview
    • 4.3.11.3 Product & Offering
    • 4.3.11.4 Key Market Strategy
    • 4.3.11.5 SWOT Analysis
  • 4.3.12 Huawei Technologies Co., Ltd.
    • 4.3.12.1 Company Overview
    • 4.3.12.2 Financial Overview
    • 4.3.12.3 Product & Offering
    • 4.3.12.4 Key Market Strategy
    • 4.3.12.5 SWOT Analysis
  • 4.3.13 NEC Corporation
    • 4.3.13.1 Company Overview
    • 4.3.13.2 Financial Overview
    • 4.3.13.3 Product & Offering
    • 4.3.13.4 Key Market Strategy
    • 4.3.13.5 SWOT Analysis
  • 4.3.14 Cray Inc. (HPE)
    • 4.3.14.1 Company Overview
    • 4.3.14.2 Financial Overview
    • 4.3.14.3 Product & Offering
    • 4.3.14.4 Key Market Strategy
    • 4.3.14.5 SWOT Analysis
  • 4.3.15 Atos SE
    • 4.3.15.1 Company Overview
    • 4.3.15.2 Financial Overview
    • 4.3.15.3 Product & Offering
    • 4.3.15.4 Key Market Strategy
    • 4.3.15.5 SWOT Analysis
  • 4.3.16 Arm Ltd.
    • 4.3.16.1 Company Overview
    • 4.3.16.2 Financial Overview
    • 4.3.16.3 Product & Offering
    • 4.3.16.4 Key Market Strategy
    • 4.3.16.5 SWOT Analysis
  • 4.3.17 Cerebras Systems
    • 4.3.17.1 Company Overview
    • 4.3.17.2 Financial Overview
    • 4.3.17.3 Product & Offering
    • 4.3.17.4 Key Market Strategy
    • 4.3.17.5 SWOT Analysis
  • 4.3.18 Graphcore
    • 4.3.18.1 Company Overview
    • 4.3.18.2 Financial Overview
    • 4.3.18.3 Product & Offering
    • 4.3.18.4 Key Market Strategy
    • 4.3.18.5 SWOT Analysis
  • 4.3.19 Groq Inc.
    • 4.3.19.1 Company Overview
    • 4.3.19.2 Financial Overview
    • 4.3.19.3 Product & Offering
    • 4.3.19.4 Key Market Strategy
    • 4.3.19.5 SWOT Analysis
  • 4.3.20 Lenovo
    • 4.3.20.1 Company Overview
    • 4.3.20.2 Financial Overview
    • 4.3.20.3 Product & Offering
    • 4.3.20.4 Key Market Strategy
    • 4.3.20.5 SWOT Analysis
  • 4.3.21 Supermicro
    • 4.3.21.1 Company Overview
    • 4.3.21.2 Financial Overview
    • 4.3.21.3 Product & Offering
    • 4.3.21.4 Key Market Strategy
    • 4.3.21.5 SWOT Analysis
  • 4.3.22 Samsung Electronics
    • 4.3.22.1 Company Overview
    • 4.3.22.2 Financial Overview
    • 4.3.22.3 Product & Offering
    • 4.3.22.4 Key Market Strategy
    • 4.3.22.5 SWOT Analysis
  • 4.3.23 Micron Technology Inc.
    • 4.3.23.1 Company Overview
    • 4.3.23.2 Financial Overview
    • 4.3.23.3 Product & Offering
    • 4.3.23.4 Key Market Strategy
    • 4.3.23.5 SWOT Analysis
  • 4.3.24 Meta Platform Inc.
    • 4.3.24.1 Company Overview
    • 4.3.24.2 Financial Overview
    • 4.3.24.3 Product & Offering
    • 4.3.24.4 Key Market Strategy
    • 4.3.24.5 SWOT Analysis
  • 4.3.25 PEZY Group
    • 4.3.25.1 Company Overview
    • 4.3.25.2 Financial Overview
    • 4.3.25.3 Product & Offering
    • 4.3.25.4 Key Market Strategy
    • 4.3.25.5 SWOT Analysis
  • 4.3.26 TESLA
    • 4.3.26.1 Company Overview
    • 4.3.26.2 Financial Overview
    • 4.3.26.3 Product & Offering
    • 4.3.26.4 Key Market Strategy
    • 4.3.26.5 SWOT Analysis
  • 4.3.27 Mediatek Inc.
    • 4.3.27.1 Company Overview
    • 4.3.27.2 Financial Overview
    • 4.3.27.3 Product & Offering
    • 4.3.27.4 Key Market Strategy
    • 4.3.27.5 SWOT Analysis
  • 4.3.28 SAMBANOVA Systems Inc.
    • 4.3.28.1 Company Overview
    • 4.3.28.2 Financial Overview
    • 4.3.28.3 Product & Offering
    • 4.3.28.4 Key Market Strategy
    • 4.3.28.5 SWOT Analysis
  • 4.3.29 Kalray
    • 4.3.29.1 Company Overview
    • 4.3.29.2 Financial Overview
    • 4.3.29.3 Product & Offering
    • 4.3.29.4 Key Market Strategy
    • 4.3.29.5 SWOT Analysis
  • 4.3.30 Kenron Inc.
    • 4.3.30.1 Company Overview
    • 4.3.30.2 Financial Overview
    • 4.3.30.3 Product & Offering
    • 4.3.30.4 Key Market Strategy
    • 4.3.30.5 SWOT Analysis
  • 4.3.31 TSMC
    • 4.3.31.1 Company Overview
    • 4.3.31.2 Financial Overview
    • 4.3.31.3 Product & Offering
    • 4.3.31.4 Key Market Strategy
    • 4.3.31.5 SWOT Analysis
  • 4.3.32 Broadcom Inc.
    • 4.3.32.1 Company Overview
    • 4.3.32.2 Financial Overview
    • 4.3.32.3 Product & Offering
    • 4.3.32.4 Key Market Strategy
    • 4.3.32.5 SWOT Analysis
  • 4.3.33 Cisco Systems, Inc.
    • 4.3.33.1 Company Overview
    • 4.3.33.2 Financial Overview
    • 4.3.33.3 Product & Offering
    • 4.3.33.4 Key Market Strategy
    • 4.3.33.5 SWOT Analysis
  • 4.3.34 OpenAI
    • 4.3.34.1 Company Overview
    • 4.3.34.2 Financial Overview
    • 4.3.34.3 Product & Offering
    • 4.3.34.4 Key Market Strategy
    • 4.3.34.5 SWOT Analysis
  • 4.3.35 xAI
    • 4.3.35.1 Company Overview
    • 4.3.35.2 Financial Overview
    • 4.3.35.3 Product & Offering
    • 4.3.35.4 Key Market Strategy
    • 4.3.35.5 SWOT Analysis
• 5.0 Market Analysis and Forecasts 2026 –
• 5.1 Global AI Supercomputing Platform Market 2026 –
• 5.2 Global AI Supercomputing Platform Market by Technology 2026 –
  • 5.2.1 Global AI Supercomputing Platform Market by Hardware Component 2026 –
    • 5.2.1.1 Global AI Supercomputing Platform Market by Processor/Compute Type 2026 –
  • 5.2.2 Global AI Supercomputing Platform Market by Software Type 2026 –
  • 5.2.3 Global AI Supercomputing Platform Market by Services Type 2026 –
  • 5.2.4 Global AI Supercomputing Platform Market by Cooling Technology 2026 –
    • 5.2.4.1 Global AI Supercomputing Platform Market by Emerging & Advanced Cooling Techniques 2026 –
• 5.3 Global AI Supercomputing Platform Market by Compute Architecture 2026 –
• 5.4 Global AI Supercomputing Platform Market by AI Workload Type 2026 –
• 5.5 Global AI Supercomputing Platform Market by System Scale 2026 –
• 5.6 Global AI Supercomputing Platform Market by Deployment Model 2026 –
• 5.7 Global AI Supercomputing Platform Market by Organization Size 2026 –
• 5.8 Global AI Supercomputing Platform Market by Application 2026 –
• 5.9 Global AI Supercomputing Platform Market by Industry Vertical 2026 –
• 5.10 Global AI Supercomputing Platform Market by Region 2026 –
  • 5.10.1 North America AI Supercomputing Platform Market by Country 2026 –
  • 5.10.2 Europe AI Supercomputing Platform Market by Country 2026 –
  • 5.10.3 APAC AI Supercomputing Platform Market by Country 2026 –
  • 5.10.4 Latin America AI Supercomputing Platform Market by Country 2026 –
  • 5.10.5 MEA AI Supercomputing Platform Market by Region 2026 –
    • 5.10.5.1 Middle East AI Supercomputing Platform Market by Country 2026 –
    • 5.10.5.2 Africa AI Supercomputing Platform Market by Country 2026 –
• 5.11 Global AI Supercomputing Platform Market by Group 2026 –
• 6.0 Conclusions and Recommendations
• 6.1 Advertisers and Media Companies
• 6.2 Artificial Intelligence Providers
• 6.3 Automotive Companies
• 6.4 Broadband Infrastructure Providers
• 6.5 Communication Service Providers
• 6.6 Quantum Computing Companies
• 6.7 Data Analytics Providers
• 6.8 Immersive Technology (AR, VR, and MR) Providers
• 6.9 Networking Equipment Providers
• 6.10 Networking Security Providers
• 6.11 Semiconductor Companies
• 6.12 IoT Suppliers and Service Providers
• 6.13 Software Providers
• 6.14 Smart City System Integrators
• 6.15 Automation System Providers
• 6.16 Social Media Companies
• 6.17 Workplace Solution Providers
• 6.18 Enterprise and Government