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APUs, CPUs, GPUs, FPGAs, AI MCUs, Discrete NPUs.
- Published: November 2026
- Pages: 245
- Tables: 100
- Figures: 36
Edge AI processors are semiconductor devices with dedicated hardware for running neural-network inference, and increasingly on-device adaptation, locally within end devices and edge systems rather than in centralized data centers. The category spans:
- application processors and SoCs with integrated neural processing units (NPUs)
- PC processors combining NPUs with large integrated GPUs
- ADAS and central-compute SoCs for vehicles
- GPU-centric modules for robots and edge servers
- FPGAs and adaptive SoCs
- AI microcontrollers with micro-NPUs
- discrete accelerators attached to a host processor
Local execution provides deterministic low latency for control loops and user interaction. It also keeps personal and sensor data on the device, removes backhaul and per-token cloud costs, and maintains operation without connectivity.
The market is shifting from compute-bound perception workloads, such as object detection, speech recognition and sensor fusion, to memory-bound generative workloads: language, vision-language and vision-language-action models. Token generation depends on DRAM capacity and bandwidth far more than on peak TOPS. As a result, memory envelopes, LPDDR5X and LPDDR6 interfaces, processing-in-memory and compute-in-memory architectures now define competitive performance. Flagship SoC designs have spread AI acceleration across NPUs, GPU matrix units and CPU matrix extensions such as Arm SME2. Lower precision (INT4, FP4 and quantization-aware sub-4-bit models) and sparsity deliver larger efficiency gains than process scaling alone.
Demand is broadening from smartphones and AI PCs into higher-value machines. Automotive architectures are consolidating ADAS, automated driving and cockpit functions onto central AI compute. Humanoids, mobile manipulators and autonomous mobile robots (AMRs) need robot-brain processors that run multimodal models within tight power budgets. Industrial, medical and IoT systems are adopting AI microcontrollers and crossover MCUs for always-on inference at milliwatt power.
Integrated processor vendors dominate the market because each new workload is first served by discrete accelerators and later absorbed into the host SoC. Microcontroller and analog incumbents are acquiring NPU, accelerator and toolchain specialists so they can own both real-time control and AI compute. A new generation of start-ups is commercializing:
- digital and analog compute-in-memory
- neuromorphic and event-driven processors
- dataflow architectures
- RISC-V vector and matrix cores
- chiplet-based edge SoCs
Process technology divides the market. Leading-edge nodes serve flagship, PC and automotive processors, while mature nodes with embedded non-volatile memory serve MCUs and sensor-level AI. Geopolitics is also creating increasingly separate Chinese and Western supply chains.
The Global Edge AI Processor Market 2027–2037 analyses the technologies, applications, supply chain and competitive dynamics of the processors that run AI inference at the edge: APUs and application SoCs, PC CPUs, GPUs, FPGAs, AI microcontrollers and discrete NPUs. The report introduces a memory-based segmentation of extreme, standard and generative edge AI. It reflects how DRAM capacity and bandwidth now determine which models a device can execute. The analysis covers:
- how architectures are evolving from SoC-integrated NPUs to compute-in-memory and neuromorphic designs
- the impact of generative and physical AI on processor requirements
- the strategies of incumbents and start-ups competing for design wins
Granular forecasts from 2021 to 2037 are built bottom-up from device shipments, AI penetration and processor pricing.
Report contents include:
- Market forecasts by market, application, processor type, edge AI level and region, covering revenue, units and average selling prices.
- Wafer demand by process node class, plus analysis of AI-attributable silicon content and bear, base and bull scenarios.
- End-use market analysis of twelve applications: smartphones, PCs, tablets, smart home, wearables and XR, automotive and robotaxis, robotics and physical AI, industrial and machine vision, smart cameras, edge infrastructure, medical devices, and retail and IoT.
- Technology analysis covering:
- integrated NPUs, CPU matrix extensions, edge GPUs, FPGAs, AI MCUs and xMCUs, and discrete accelerators
- digital and analog compute-in-memory and neuromorphic processors
- numerics and quantization, memory technologies, process nodes and chiplets
- software stacks and NPU IP licensing
- Technology roadmaps to 2037 for NPU performance, memory, process nodes and on-device model capability.
- Technology and commercial readiness assessments by technology, application and product.
- Market drivers and restraints: generative AI, the AI PC cycle, physical AI, regulation, memory supply and export controls.
- Supply chain and ecosystem analysis, including foundries, memory, module makers and China’s domestic ecosystem.
- Competitive landscape: supplier shares, strategic groups and the edge AI strategies of microcontroller leaders.
- Investment analysis of venture funding, M&A, IPOs and government programmes.
- Regional analysis of China, North America, Europe, Japan, South Korea, India and Southeast Asia.
- Outlook and recommendations: risk register, opportunity map and strategic recommendations.
- Company profiles of 114 edge AI processor developers, IP licensors and suppliers. Companies profiled include Acrab, Advanced Micro Devices (AMD), AheadComputing, Alibaba Group (T-Head), Alif Semiconductor, Allwinner Technology, Altera, Ambarella, Ambient Scientific, Ambiq Micro, Amlogic, Anaflash, Analog Devices (ADI), AnalogAI, Andes Technology, Apple, Arm Holdings, Axelera AI, Axera Semiconductor, Azimuth AI, Bestechnic, BigEndian Semiconductors, Black Sesame Technologies, Blaize, Blumind, BrainChip Holdings, Cadence Design Systems, Canaan (Kendryte), Ceva, Corerain Technologies, DEEPX, EdgeCortix, Efficient Computer, Efinix, EnCharge AI, Espressif Systems, Expedera, femtoAI (Femtosense), Gemesys, Google (Tensor and Coral NPU), Great Sky, GreenWaves Technologies, Hailo, Himax Technologies, HiSilicon (Huawei), Horizon Robotics, Houmo.ai, HrdWyr, HYFIX Spatial Intelligence, Hygon Information Technology, Imagination Technologies, Infineon Technologies, Innatera Nanosystems, Intel Corporation, Intellifusion, Inuitive, Kneron, Lattice Semiconductor....
Purchasers will receive the following:
- PDF report download/by email.
- Comprehensive Excel spreadsheet of all data.
- Mid-year Update
The Global Edge AI Processor Market 2027-2037
PDF + Excel Database. The Global Edge AI Processor Market 2027-2037
PDF + Excel Database + Print Edition. Payment methods: Visa, Mastercard, American Express, Paypal, Bank Transfer. To order by Bank Transfer (Invoice) select this option from the payment methods menu after adding to cart, or use the Request a quote/Pay by invoice button or contact info@futuremarketsinc.com
1 EXECUTIVE SUMMARY 13
- 1.1 Market at a Glance 13
- 1.2 Key Findings 14
- 1.3 Market by Application and Market Segment 15
- 1.4 Market by Processor Type 16
- 1.5 Edge AI Levels 16
- 1.6 Competitive Landscape in Brief 17
- 1.7 Technology and Commercial Readiness Summary 17
- 1.8 Ten Predictions for 2027–2037 18
- 1.9 Strategic Implications 18
2 INTRODUCTION, DEFINITIONS AND SCOPE 19
- 2.1 What Is Edge AI? 19
- 2.2 Why Edge AI Matters 19
- 2.3 Which Processors Run Edge AI 20
- 2.4 Edge AI Levels: a Memory-Based Segmentation 20
- 2.5 Market Definition and Scope 21
- 2.6 Relationship to Other Future Markets Reports 22
- 2.7 Research Methodology Overview 22
3 MARKET DRIVERS, TRENDS AND RESTRAINTS 23
- 3.1 Generative AI Moves onto the Device 23
- 3.2 The AI PC Cycle 23
- 3.3 Physical AI: Robots, Vehicles and Machines 23
- 3.4 Latency, Privacy, Bandwidth, Connectivity, Power and Cost 23
- 3.5 Regulation and Standards 24
- 3.6 Restraints, Risks and Challenges 24
- 3.6.1 The 2026 memory shock 24
- 3.6.2 Software fragmentation 24
- 3.6.3 Geopolitics and export controls 24
- 3.6.4 Power, thermal and cost limits 25
4 EDGE AI PROCESSOR TECHNOLOGIES 26
- 4.1 Architecture Overview 26
- 4.2 SoC-Integrated NPUs in APUs 26
- 4.3 PC Processors with NPUs 27
- 4.4 GPUs and GPU-Centric SoCs at the Edge 28
- 4.5 FPGAs and Adaptive SoCs 28
- 4.6 AI Microcontrollers and xMCUs 28
- 4.7 Discrete NPUs and AI Accelerators 29
- 4.8 Novel Architectures: Compute-in-Memory, Analog and Neuromorphic 30
- 4.8.1 Digital SRAM compute-in-memory 30
- 4.8.2 Analog compute-in-memory 31
- 4.8.3 Neuromorphic processors 31
- 4.9 Numerics, Quantization and Sparsity 31
- 4.10 Memory for Edge AI 31
- 4.11 Process Nodes, Packaging and Chiplets 33
- 4.12 Software Stacks and Toolchains 33
- 4.13 NPU IP Licensing 33
- 4.14 Security and Safety 34
5 TECHNOLOGY ROADMAPS 2025–2037 35
- 5.1 How Edge AI Silicon Evolves: Discrete First, Then Integrated 35
- 5.2 Roadmap by Processor Type 35
- 5.3 NPU Performance and Efficiency Roadmap 36
- 5.4 Memory Roadmap 37
- 5.5 Process Node and Packaging Roadmap 37
- 5.6 Model and Workload Roadmap by Device Class 38
6 COMMERCIAL READINESS ASSESSMENT 40
- 6.1 Assessment Framework 40
- 6.2 Readiness by Technology 41
- 6.3 Readiness by Application 42
- 6.4 Readiness of Leading Products 43
- 6.5 Barriers to Commercialization 44
7 GLOBAL MARKET FORECASTS 2021–2037 45
- 7.1 Forecast Methodology and Key Assumptions 45
- 7.2 Total Market: Revenue, Units and ASP 45
- 7.3 Forecast by Market 47
- 7.4 Forecast by Application 48
- 7.5 Forecast by Processor Type 51
- 7.6 Forecast by Edge AI Level 53
- 7.7 Forecast by Region 56
- 7.8 Wafer Demand 59
- 7.9 Edge AI Processor Value versus AI-Attributable Content 61
- 7.10 Scenario Analysis 62
- 7.11 Reconciliation with Other Future Markets Reports and Third-Party Estimates 63
8 END-USE MARKETS 65
- 8.1 Overview of End-Use Markets 65
- 8.2 Smartphones 65
- 8.2.1 Market overview 66
- 8.2.2 Why 12 GB of DRAM, not NPU TOPS, gates generative AI 67
- 8.2.3 NPU die area in flagship APUs 68
- 8.2.4 Outlook 68
- 8.3 PCs: Laptops and Desktops 68
- 8.3.1 Market overview 68
- 8.3.2 NPU adoption in laptops, x86 versus Arm, and NPU versus GPU in desktops 69
- 8.4 Tablets 70
- 8.5 Smart Home and Consumer Devices 71
- 8.5.1 Market overview 71
- 8.6 Wearables and XR 73
- 8.6.1 Market overview 73
- 8.6.2 Where AI runs in smartwatches and smart glasses 74
- 8.7 Automotive and Robotaxis 75
- 8.7.1 Market overview 75
- 8.7.2 Compute tiers and the value ladder 76
- 8.7.3 Supplier landscape 77
- 8.7.4 Robotaxis 78
- 8.8 Robotics and Physical AI 78
- 8.8.1 Market overview 78
- 8.8.2 Compute inside physical AI systems 79
- 8.9 Industrial Automation and Machine Vision 81
- 8.9.1 Market overview 81
- 8.10 Smart Cameras, Video Analytics and Smart City 83
- 8.11 Edge Infrastructure: Edge Servers, Gateways and MEC 84
- 8.12 Medical and Healthcare Devices 85
- 8.13 Retail, Enterprise and Other IoT 86
- 8.14 Defence and Aerospace 87
9 SUPPLY CHAIN AND ECOSYSTEM 88
- 9.1 Value Chain Overview 88
- 9.2 Foundry and Manufacturing 88
- 9.3 Memory Supply 89
- 9.4 Module Makers, ODMs and Distribution 89
- 9.5 Software and Developer Ecosystems 89
- 9.6 China's Edge AI Processor Ecosystem 90
10 COMPETITIVE LANDSCAPE AND MARKET SHARES 91
- 10.1 Market Structure 91
- 10.2 Leaders by Application 92
- 10.3 Strategic Groups 93
- 10.4 MCU Leaders: Buy, License or Build 93
- 10.5 Competitive Positioning 94
- 10.6 Market Share Outlook 95
11 INVESTMENT, FUNDING AND M&A 96
- 11.1 Venture Funding for Edge AI Processor Start-ups 96
- 11.2 Mergers and Acquisitions 101
- 11.3 Public Listings 102
- 11.4 Government Programmes 102
12 REGIONAL MARKET ANALYSIS 103
- 12.1 Regional Overview 103
- 12.2 China 103
- 12.3 North America 103
- 12.4 Europe 103
- 12.5 Japan 103
- 12.6 South Korea 103
- 12.7 Rest of Asia-Pacific 105
- 12.8 Rest of World 105
13 MARKET OUTLOOK, RISKS AND RECOMMENDATIONS 106
- 13.1 Outlook 2027–2037 106
- 13.2 Key Risks 106
- 13.3 Opportunities 107
- 13.4 Recommendations 107
- 13.4.1 For processor vendors 107
- 13.4.2 For MCU and embedded vendors 107
- 13.4.3 For start-ups 107
- 13.4.4 For OEMs 107
- 13.4.5 For investors 107
14 COMPANY PROFILES 108 (114 compay profiles)
15 RESEARCH METHODOLOGY 233
- 15.1 Objectives and Scope 233
- 15.2 Market Definition and Allocation Rules 233
- 15.3 Primary and Secondary Research 233
- 15.4 Forecast Approach 233
- 15.5 Conventions and Limitations 233
16 GLOSSARY OF TERMS AND ABBREVIATIONS 234
17 REFERENCES 235
LIST OF TABLES
- Table 1. Headline Forecast Summary, Global Edge AI Processor Market 13
- Table 2. Market Share of Edge AI Processor Revenue, Selected Years (%) 15
- Table 3. Strategic Implications by Stakeholder 18
- Table 4. The Edge Continuum and Typical AI Processors 19
- Table 5. Drivers of On-Device Versus Cloud Execution 19
- Table 6. Edge AI Processor Types Covered in This Report 20
- Table 7. Edge AI Levels Used in This Report 21
- Table 8. Market Definition: What Is Counted 21
- Table 9. Edge AI Adoption Drivers: Impact Assessment, 2027–2037 23
- Table 10. Market Restraints: Impact Assessment 25
- Table 11. Comparison of Edge AI Processor Architectures 26
- Table 12. Flagship Smartphone APUs and Their AI Engines, 2025–2026 27
- Table 13. AI PC Processor Platforms, 2025–2026 27
- Table 14. Selected AI Microcontrollers and xMCUs, 2024–2026 29
- Table 15. Discrete Edge AI Accelerators: Comparison, 2026 29
- Table 16. Relative Efficiency of Numeric Formats for Edge Inference 31
- Table 17. Memory Technologies for Edge AI Processors 32
- Table 18. Process Node Mix of Edge AI Processor Wafer Demand, 2025 and 2037 (Thousand 300 mm Wafers) 33
- Table 19. Licensable Edge NPU and AI Processor IP, 2026 34
- Table 20. The Absorption Cycle: Edge AI Workloads Moving from Discrete to Integrated Silicon 35
- Table 21. Edge AI Processor Technology Roadmap by Processor Type, 2025–2037 35
- Table 22. Edge AI Processor Performance Roadmap by Device Class (Future Markets Projections) 36
- Table 23. Edge AI Memory Roadmap, 2025–2037 37
- Table 24. Process Node Roadmap for Edge AI Processors 37
- Table 25. On-Device Model Capability Roadmap by Device Class 38
- Table 26. Commercial Readiness Level Definitions 40
- Table 27. Technology and Commercial Readiness of Edge AI Processor Technologies, 2026 41
- Table 28. Commercial Readiness of Edge AI by Application, 2026 and 2031 42
- Table 29. Commercial Status of Selected Edge AI Processor Products, Q4 2026 43
- Table 30. Barriers to Commercial Adoption and Expected Resolution 44
- Table 31. Key Forecast Assumptions 45
- Table 32. Global Edge AI Processor Revenue, Shipments and Blended ASP, 2021–2037 45
- Table 33. Edge AI Processor Revenue by Market, 2021–2037 (US$ Billions) 47
- Table 34. Edge AI Processor Revenue by Application, 2021–2037 (US$ Billions) 48
- Table 35. Edge AI Processor Shipments by Application, 2021–2037 (Million Units) 50
- Table 36. Average Selling Price of Edge AI Processors by Application, 2021–2037 (US$ per Unit) 51
- Table 37. Edge AI Processor Revenue by Processor Type, 2021–2037 (US$ Billions) 51
- Table 38. Edge AI Processor Revenue by Application and Processor Type, 2030 (US$ Billions) 52
- Table 39. Edge AI Processor Revenue by Edge AI Level, 2021–2037 (US$ Billions) 53
- Table 40. Edge AI Processor Shipments by Edge AI Level, 2021–2037 (Million Units) 54
- Table 41. Edge AI Level Mix by Application, Share of Revenue, 2025 and 2037 (%) 56
- Table 42. Edge AI Processor Revenue by Region, 2021–2037 (US$ Billions) 56
- Table 43. Edge AI Processor Revenue by Application and Region, 2030 (US$ Billions) 58
- Table 44. Edge AI Processor Wafer Demand by Process Node Class, 2021–2037 (Thousand 300 mm Wafer Starts) 59
- Table 45. Edge AI Processor Wafer Demand by Application, 2021–2037 (Thousand 300 mm Wafer Starts) 60
- Table 46. Edge AI Processor Value versus AI-Attributable Silicon Value, 2021–2037 61
- Table 47. Edge AI Processor Market Scenarios, 2026–2037 (US$ Billions) 62
- Table 48. Scenario Drivers and Assumptions 63
- Table 49. Comparison of Edge AI Market Estimates 63
- Table 50. End-Use Market Summary, 2025 and 2037 65
- Table 51. Smartphones: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 66
- Table 52. Smartphone DRAM and Edge AI Capability by Price Tier, 2026 67
- Table 53. Indicative Die Area Allocation of Flagship Smartphone APUs (% of Die) 68
- Table 54. Smartphones: Revenue by Processor Type, 2025–2037 (US$ Billions) 68
- Table 55. PCs (laptops & desktops): Edge AI Processor Shipments, ASP and Revenue, 2021–2037 68
- Table 56. AI PC Processor Market Structure, 2025 and 2030 (Share of AI PC Processor Revenue, Estimated) 70
- Table 57. PCs (laptops & desktops): Revenue by Processor Type, 2025–2037 (US$ Billions) 70
- Table 58. Tablets: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 70
- Table 59. Smart home & consumer devices: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 71
- Table 60. Edge AI in Home Consumer Devices: Applications and Processors 72
- Table 61. Smart home & consumer devices: Revenue by Processor Type, 2025–2037 (US$ Billions) 73
- Table 62. Wearables & XR: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 73
- Table 63. Edge AI Processors in Smartwatches, Smart Glasses and XR Headsets, 2023–2026 74
- Table 64. Wearables & XR: Revenue by Processor Type, 2025–2037 (US$ Billions) 75
- Table 65. Automotive (ADAS/AD & cockpit): Edge AI Processor Shipments, ASP and Revenue, 2021–2037 75
- Table 66. Automotive AI Compute Requirements and Processor Value by Automation Level 76
- Table 67. Leading Automotive AI SoCs, 2025–2026 77
- Table 68. Automotive (ADAS/AD & cockpit): Revenue by Processor Type, 2025–2037 (US$ Billions) 78
- Table 69. Robotics & physical AI: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 78
- Table 70. Compute Inside Physical AI Systems, 2026 79
- Table 71. Robotics Compute Platforms, 2025–2026 80
- Table 72. Robotics & physical AI: Revenue by Processor Type, 2025–2037 (US$ Billions) 80
- Table 73. Industrial automation & machine vision: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 81
- Table 74. Industrial Edge AI Workloads and Processor Requirements 82
- Table 75. Industrial automation & machine vision: Revenue by Processor Type, 2025–2037 (US$ Billions) 82
- Table 76. Smart cameras & video analytics: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 83
- Table 77. Edge infrastructure (servers, gateways, MEC): Edge AI Processor Shipments, ASP and Revenue, 2021–2037 84
- Table 78. Edge infrastructure (servers, gateways, MEC): Revenue by Processor Type, 2025–2037 (US$ Billions) 85
- Table 79. Medical & healthcare devices: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 86
- Table 80. Retail, enterprise & other IoT: Edge AI Processor Shipments, ASP and Revenue, 2021–2037 86
- Table 81. Edge AI Processor Value Chain and Key Suppliers 88
- Table 82. Foundry Positioning for Edge AI Processors 88
- Table 83. Edge AI Software Ecosystems by Supplier 89
- Table 84. Edge AI Processor Revenue by Supplier, 2025 (US$ Billions, Estimated) 91
- Table 85. Leading Edge AI Processor Suppliers by Application, 2025 92
- Table 86. Strategic Groups in the Edge AI Processor Market 93
- Table 87. Edge AI Strategies of Leading MCU and Embedded Suppliers 94
- Table 88. Competitive Positioning of Leading Edge AI Processor Suppliers 94
- Table 89. Estimated Edge AI Processor Market Shares, 2025 and 2031 95
- Table 90. Disclosed Funding Rounds for Edge and Embedded AI Processor Companies, Q4 2024–Q3 2026 96
- Table 91. Edge AI Processor M&A, 2023–2026 101
- Table 92. Listed Edge AI Processor Pure-Plays and Recent IPOs 102
- Table 93. Government Programmes Supporting Edge AI Processors 102
- Table 94. Edge AI Processor Revenue by Region, 2021–2037 (US$ Billions) 103
- Table 95. Regional Roles in the Edge AI Processor Value Chain 103
- Table 96. Base-Case Milestones, 2027–2037 106
- Table 97. Risk Register (Probability and Impact) 106
- Table 98. Opportunity Map, 2027–2037 107
- Table 99. Companies Profiled in This Report 108
- Table 100. Glossary of Terms and Abbreviations 234
LIST OF FIGURES
- Figure 1. Global Edge AI Processor Revenue, 2021–2037 (US$ Billions) and Annual Growth 14
- Figure 2. Edge AI Processor Revenue by Market, 2021–2037 (US$ Billions) 15
- Figure 3. Processor Type Share of Edge AI Processor Revenue, 2025, 2031 and 2037 (%) 16
- Figure 4. Edge AI Processor Market Share by Supplier, 2025 (%) 17
- Figure 5. Typical Memory Envelope Available to AI by Device Class, 2026 (GB, Log Scale) 21
- Figure 6. Edge AI Processor Efficiency Landscape: Vendor Peak TOPS versus Rated Power, Selected Products 2024–2026 30
- Figure 7. On-Device LLM Decode Rate as a Function of Memory Bandwidth and Model Size 32
- Figure 8. Edge NPU Peak Performance Roadmap by Device Class, 2017–2037 (Vendor Peak TOPS, Log Scale) 36
- Figure 9. Edge AI Adoption Curves by Device Category, 2021–2037 (% of Shipments, Future Markets Estimates) 39
- Figure 10. Technology Readiness Level Outlook for Edge AI Processor Technologies, 2025–2037 41
- Figure 11. Edge AI Processor Unit Shipments by Application, 2021–2037 (Million Units) 46
- Figure 12. Blended Average Selling Price of Edge AI Processors, 2021–2037 (US$) 47
- Figure 13. Edge AI Processor Revenue by Application, 2021–2037 (US$ Billions) 49
- Figure 14. Application Share of Edge AI Processor Revenue, 2025, 2031 and 2037 (%) 49
- Figure 15. Edge AI Processor Revenue CAGR by Application, 2027–2037 (%) 50
- Figure 16. Edge AI Processor Revenue by Processor Type, 2021–2037 (US$ Billions) 52
- Figure 17. Edge AI Processor Revenue by Edge AI Level, 2021–2037 (US$ Billions) 55
- Figure 18. Edge AI Processor Shipments by Edge AI Level, 2021–2037 (Million Units) 55
- Figure 19. Edge AI Processor Revenue by Region, 2021–2037 (US$ Billions) 57
- Figure 20. Edge AI Processor Revenue CAGR by Region, 2027–2037 (%) 58
- Figure 21. Edge AI Processor Wafer Demand by Process Node, 2021–2037 (Thousand 300 mm Wafers) 60
- Figure 22. Edge AI Processor Wafer Demand by Application, 2025 and 2037 (Thousand 300 mm Wafers) 61
- Figure 23. Edge AI Processor Value versus AI-Attributable Silicon Value, 2021–2037 (US$ Billions) 62
- Figure 24. Edge AI Processor Market Scenarios: Bear, Base and Bull, 2021–2037 (US$ Billions) 63
- Figure 25. Smartphones: Edge AI Processor Revenue and Unit Shipments, 2021–2037 67
- Figure 26. PCs (laptops & desktops): Edge AI Processor Revenue and Unit Shipments, 2021–2037 69
- Figure 27. Tablets: Edge AI Processor Revenue and Unit Shipments, 2021–2037 71
- Figure 28. Smart home & consumer devices: Edge AI Processor Revenue and Unit Shipments, 2021–2037 72
- Figure 29. Wearables & XR: Edge AI Processor Revenue and Unit Shipments, 2021–2037 74
- Figure 30. Automotive (ADAS/AD & cockpit): Edge AI Processor Revenue and Unit Shipments, 2021–2037 76
- Figure 31. Robotics & physical AI: Edge AI Processor Revenue and Unit Shipments, 2021–2037 79
- Figure 32. Industrial automation & machine vision: Edge AI Processor Revenue and Unit Shipments, 2021–2037 82
- Figure 33. Smart cameras & video analytics: Edge AI Processor Revenue and Unit Shipments, 2021–2037 84
- Figure 34. Edge infrastructure (servers, gateways, MEC): Edge AI Processor Revenue and Unit Shipments, 2021–2037 85
- Figure 35. Leading Edge AI Processor Suppliers by Revenue, 2025 (US$ Billions, Estimated) 92
- Figure 36. Disclosed Funding for Edge and Embedded AI Processor Start-ups by Quarter, Q4 2024–Q3 2026 (US$ Millions) 96
Purchasers will receive the following:
- PDF report download/by email.
- Comprehensive Excel spreadsheet of all data.
- Mid-year Update
The Global Edge AI Processor Market 2027-2037
PDF + Excel Database. The Global Edge AI Processor Market 2027-2037
PDF + Excel Database + Print Edition. Payment methods: Visa, Mastercard, American Express, Paypal, Bank Transfer. To order by Bank Transfer (Invoice) select this option from the payment methods menu after adding to cart, or use the Request a quote/Pay by invoice button or contact info@futuremarketsinc.com
