Summary

The Edge AI software market is projected to grow from USD 1.92 billion in 2024 to USD 7.19 billion by 2030, at a compound annual growth rate (CAGR) of 24.7% during the forecast period. The market is anticipated to grow due to Predictive maintenance powered by Edge AI is transforming industrial operations by enabling real-time monitoring and forecasting of equipment failures before they happen, Edge AI is enabling highly personalized experiences for consumers by processing data locally on devices like smartphones, wearables, and smart home systems and Smart grids and energy management systems are benefiting greatly from Edge AI’s ability to provide distributed intelligence. However, growth may be restrained by the complexity of deploying and managing machine learning models at the edge, the absence of standard protocols and interoperability between different Edge AI platforms, devices, and ecosystems can slow down adoption and the high initial investment required to build and scale Edge AI infrastructure can be prohibitive for some organizations.
“Edge AI Platform Solutions Leading the Market with Highest CAGR Growth”
Platform solutions are expected to register the highest CAGR growth in the Edge AI software market due to their ability to integrate diverse AI capabilities, streamline deployment, and support scalable applications across industries. These platforms enable seamless development, testing, and deployment of AI models on edge devices, reducing complexity and accelerating time-to-market. Future opportunities lie in leveraging these solutions for autonomous systems, advanced robotics, and distributed IoT ecosystems, where customizable platforms can address specific requirements for real-time analytics, data security, and interoperability, driving adoption across sectors like healthcare, automotive, and industrial automation.
“Predictive Maintenance and Robotics Automation Transforming Manufacturing with Edge AI”
During the forecast period, the manufacturing sector is anticipated to dominate the Edge AI software market, driven by its adoption for real-time quality control, predictive maintenance, and robotics automation. Edge AI enables manufacturers to process vast amounts of machine data locally, reducing latency and enhancing operational efficiency. Future opportunities include leveraging Edge AI for smart factory solutions, optimizing energy consumption, and enabling autonomous production lines. As manufacturers prioritize Industry 4.0 initiatives and demand localized intelligence for critical operations, the deployment of Edge AI software in this sector will continue to expand rapidly.
“Asia Pacific's rapid edge AI software market growth fueled by innovation and emerging technologies, while North America leads in market size”
Asia Pacific is projected to be the fastest-growing market for Edge AI software during the forecast period, driven by rapid industrialization, increasing adoption of IoT devices, and significant investments in smart city initiatives. The region's growing demand for localized data processing in sectors like manufacturing, retail, and telecommunications further boosts this trend. Meanwhile, North America holds the largest market share due to its early adoption of advanced technologies, strong presence of key players, and robust infrastructure supporting AI deployment. Future opportunities include expanding Edge AI applications in Asia Pacific’s emerging markets for autonomous systems and real-time analytics, while North America continues to innovate in areas like healthcare and defense with cutting-edge edge computing solutions.
Breakdown of primaries
In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the Edge AI software market.
 By Company: Tier I – 30%, Tier II – 40%, and Tier III – 30%
 By Designation: C-Level Executives – 35%, D-Level Executives – 25%, and others – 40%
 By Region: North America – 30%, Europe – 35%, Asia Pacific – 25%, Middle East & Africa – 5%, and Latin America – 5%
The report includes the study of key players offering edge AI software market. It profiles major vendors in the Edge AI software market. The major players in the Edge AI software market include Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), Gorilla Technologies (UK), Intel (US), VEEA (US), Infineon Technologies (German), Intent HQ (UK), Baidu (China), NVIDIA (US), Alibaba Group (Singapore), Bosch Global Software Technologies (India), Azion (US), Blaize (US), ClearBlade (US), Johnson Controls (US), Midokura (Japan), Latent AI (US), Axelera AI (Netherlands), Teraki (Germany), Ekkono (Sweden), Edge Impulse (US), Spectro Cloud (US), Barbara (Spain), Invision AI (US), Horizon Robotics (China), and Kneron (US).
Research coverage
This research report categorizes the Edge AI software Market By offering (Software [By Type and By Deployment mode] and Services [Professional services and Managed services]), By data Modality (Visual data, Auditory data, Textual data, Spatial data, Temporal data and Multi-modal data), By Technology (Generative AI and Other AI [Machine learning, Natural language processing, Computer vision and Others]), By End Uses (Manufacturing, Smart cities, BFSI, Healthcare & life sciences, Energy & utilities, Telecommunication, Retail, Automotive, Transportation & logistics, Consumer electronics & devices and Other end uses [IT & ITeS, Education and Agriculture]), and By Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the Edge AI software market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, mergers and acquisitions, and recent developments associated with the Edge AI software market. Competitive analysis of upcoming startups in the Edge AI software market ecosystem is covered in this report.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall Edge AI software market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:
• Analysis of key drivers (increasing number of intelligent applications, rising use of IoT applications, increasing adoption of 5G network technology, exponential growth of data volume and network traffic), restraints (Bandwidth limitations resulting from the need for continuous data transfer and limited availability of AI experts), opportunities (growing deployment of TinyML, rising demand of autonomous and connected vehicles, emergence of transformative applications in various fields), and challenges (Need for optimization of edge AI standards, complexity of integrating diverse systems and lack of hardware standards).
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Edge AI software market.
• Market Development: Comprehensive information about lucrative markets – the report analyses the Edge AI software market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Edge AI software market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), IBM (US), Google (US), AWS (US), Nutanix (US), Synaptics (US), Gorilla Technologies (UK), Intel (US), VEEA (US), Infineon Technologies (Germany), Intent HQ (UK), Baidu (China), NVIDIA (US), Alibaba Group (Singapore), Bosch Global Software Technologies (India), Azion (US), Blaize (US), ClearBlade (US), Johnson Controls (US), Midokura (Japan), Latent AI (US), Axelera AI (Netherlands), Teraki (Germany), Ekkono (Sweden), Edge Impulse (US), Spectro Cloud (US), Barbara (Spain), Invision AI (US), Horizon Robotics (China), and Kneron (US), among others in the Edge AI software market. The report also helps stakeholders understand the pulse of the Edge AI software market and provides them with information on key market drivers, restraints, challenges, and opportunities.

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Table of Contents

1 INTRODUCTION 32
1.1 STUDY OBJECTIVES 32
1.2 MARKET DEFINITION 32
1.2.1 INCLUSIONS AND EXCLUSIONS 33
1.3 STUDY SCOPE 34
1.3.1 MARKETS COVERED 34
1.3.2 YEARS CONSIDERED 35
1.4 CURRENCY CONSIDERED 35
1.5 STAKEHOLDERS 36
1.6 SUMMARY OF CHANGES 36
2 RESEARCH METHODOLOGY 38
2.1 RESEARCH DATA 38
2.1.1 SECONDARY DATA 39
2.1.2 PRIMARY DATA 39
2.1.2.1 Breakup of primary profiles 40
2.1.2.2 Key industry insights 41
2.2 MARKET BREAKUP AND DATA TRIANGULATION 42
2.3 MARKET SIZE ESTIMATION 43
2.3.1 TOP-DOWN APPROACH 43
2.3.2 BOTTOM-UP APPROACH 44
2.4 MARKET FORECAST 47
2.5 RESEARCH ASSUMPTIONS 48
2.6 RESEARCH LIMITATIONS 49
3 EXECUTIVE SUMMARY 50
4 PREMIUM INSIGHTS 58
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN EDGE AI SOFTWARE MARKET 58
4.2 EDGE AI SOFTWARE MARKET, BY TOP THREE END USES 58
4.3 EDGE AI SOFTWARE MARKET IN NORTH AMERICA, BY TOP THREE DATA MODALITY TYPES AND END USES 59
4.4 EDGE AI SOFTWARE MARKET, BY REGION 59
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS 60
5.1 INTRODUCTION 60
5.2 MARKET DYNAMICS 60
5.2.1 DRIVERS 60
5.2.1.1 Increasing number of intelligent applications 60
5.2.1.2 Exponential growth of data volume and network traffic 61
5.2.1.3 Rising use of IoT applications 61
5.2.1.4 Increasing adoption of 5G network technology 61
5.2.2 RESTRAINTS 62
5.2.2.1 Bandwidth limitations resulting from need for continuous data transfer 62
5.2.2.2 Limited availability of AI experts 62
5.2.3 OPPORTUNITIES 62
5.2.3.1 Growing deployment of TinyML 62
5.2.3.2 Rising demand for autonomous and connected vehicles 63
5.2.3.3 Emergence of transformative applications in various fields 63
5.2.4 CHALLENGES 63
5.2.4.1 Need for optimization of edge AI standards 63
5.2.4.2 Complexity of integrating diverse systems 64
5.2.4.3 Lack of hardware standards 64
5.3 IMPACT OF GENERATIVE AI ON EDGE AI SOFTWARE MARKET 65
5.3.1 TOP USE CASES AND MARKET POTENTIAL 65
5.3.1.1 Key use cases 65
5.3.1.1.1 Real-time Data Processing and Analysis 66
5.3.1.1.2 Predictive Maintenance 66
5.3.1.1.3 Anomaly Detection 66
5.3.1.1.4 Personalized User Experience 66
5.3.1.1.5 Enhanced Security & Fraud Detection 67
5.3.1.1.6 Scalable AI Models 67
5.4 EDGE AI SOFTWARE MARKET: EVOLUTION 68
5.5 ECOSYSTEM ANALYSIS 70
5.5.1 PLATFORM PROVIDERS 70
5.5.2 SDK PROVIDERS 70
5.5.3 FRAMEWORK & TOOLKIT PROVIDERS 71
5.5.4 SERVICE PROVIDERS 71
5.5.5 TECHNOLOGY PARTNERS/INTEGRATORS 71
5.5.6 END USERS 71
5.6 SUPPLY CHAIN ANALYSIS 72
5.7 INVESTMENT AND FUNDING SCENARIO 73
 
5.8 CASE STUDY ANALYSIS 75
5.8.1 CASE STUDY 1: LEVERAGING EDGE AI AND GEOSPATIAL ANALYTICS FOR ENHANCED RESPONSE AND RECOVERY 75
5.8.2 CASE STUDY 2: FACILITATING PREDICTIVE MAINTENANCE AND COST SAVINGS FOR PRINT SHOP 75
5.8.3 CASE STUDY 3: TRANSFORMING POWER DISTRIBUTION BY LEVERAGING EDGE AI IN VIRTUALIZED SUBSTATIONS 76
5.8.4 CASE STUDY 4: REVOLUTIONIZING INDUSTRIAL MONITORING WITH EKKONO'S EDGE AI VIRTUAL SENSORS 76
5.8.5 CASE STUDY 5: TRANSFORMING WAREHOUSE EFFICIENCY WITH AUTONOMOUS AI-DRIVEN INVENTORY MONITORING SOLUTIONS 77
5.9 TECHNOLOGY ANALYSIS 77
5.9.1 KEY TECHNOLOGIES 77
5.9.1.1 Edge computing 77
5.9.1.2 Machine Learning (ML) 77
5.9.1.3 Computer vision 78
5.9.1.4 Natural Language Processing (NLP) 78
5.9.2 COMPLEMENTARY TECHNOLOGIES 78
5.9.2.1 Federated technologies 78
5.9.2.2 Cloud computing 78
5.9.2.3 Internet of Things (IoT) 78
5.9.3 ADJACENT TECHNOLOGIES 79
5.9.3.1 Big data analytics 79
5.9.3.2 Digital twins 79
5.9.3.3 Blockchain 79
5.10 REGULATORY LANDSCAPE 80
5.10.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 80
5.10.2 REGIONAL REGULATIONS 84
5.10.2.1 North America 84
5.10.2.1.1 SCR 17: Artificial Intelligence Bill – California, US 84
5.10.2.1.2 S1103: Artificial Intelligence Automated Decision Bill – Connecticut, US 84
5.10.2.1.3 National Artificial Intelligence Initiative Act (NAIIA) 85
5.10.2.1.4 Artificial Intelligence and Data Act (AIDA) – Canada 85
5.10.2.2 Europe 86
5.10.2.2.1 Artificial Intelligence Act (AIA) – European Union 86
5.10.2.2.2 General Data Protection Regulation – European Union 86
5.10.2.3 Asia Pacific 87
5.10.2.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services – China 87
5.10.2.3.2 National AI Strategy – Singapore 87
5.10.2.3.3 Hiroshima AI Process Comprehensive Policy Framework – Japan 88
 
5.10.2.4 Middle East & Africa 88
5.10.2.4.1 National Strategy for Artificial Intelligence – UAE 88
5.10.2.4.2 National Artificial Intelligence Strategy – Qatar 89
5.10.2.4.3 AI Ethics Principles and Guidelines – Dubai, UAE 89
5.10.2.5 Latin America 89
5.10.2.5.1 Declaration of Santiago – Chile 89
5.10.2.5.2 Brazilian Artificial Intelligence Strategy – Brazil 90
5.11 PATENT ANALYSIS 91
5.11.1 METHODOLOGY 91
5.11.2 PATENTS FILED, BY DOCUMENT TYPE 91
5.11.3 INNOVATION AND PATENT APPLICATIONS 92
5.12 PRICING ANALYSIS 95
5.12.1 INDICATIVE PRICING ANALYSIS OF EDGE AI SOFTWARE, BY DATA MODALITY 96
5.12.2 INDICATIVE PRICING ANALYSIS OF EDGE AI SOFTWARE, BY OFFERING 97
5.13 KEY CONFERENCES AND EVENTS, 2024–2025 97
5.14 PORTER’S FIVE FORCES ANALYSIS 99
5.14.1 THREAT OF NEW ENTRANTS 100
5.14.2 THREAT OF SUBSTITUTES 100
5.14.3 BARGAINING POWER OF SUPPLIERS 100
5.14.4 BARGAINING POWER OF BUYERS 100
5.14.5 INTENSITY OF COMPETITIVE RIVALRY 101
5.15 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 101
5.15.1 KEY TRENDS/DISRUPTIONS IMPACTING BUSINESS MODELS 101
5.16 KEY STAKEHOLDERS & BUYING CRITERIA 102
5.16.1 KEY STAKEHOLDERS IN BUYING PROCESS 102
5.16.2 BUYING CRITERIA 103
6 EDGE AI SOFTWARE MARKET, BY OFFERING 104
6.1 INTRODUCTION 105
6.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY OFFERING 105
6.2 SOFTWARE 107
6.2.1 RISING DEMAND ACROSS DIVERSE INDUSTRIES TO BOOST MARKET 107
6.2.2 BY TYPE 108
6.2.2.1 Platforms 109
6.2.2.2 Software development kits (SDKs) 110
6.2.2.3 Frameworks & toolkits 111
6.2.3 BY DEPLOYMENT MODE 112
6.2.3.1 Cloud 114
6.2.3.2 On-premises 115
 
6.3 SERVICES 116
6.3.1 RISING DEMAND FOR IMPLEMENTATION AND MAINTENANCE SUPPORT TO DRIVE MARKET 116
6.3.2 PROFESSIONAL SERVICES 118
6.3.2.1 Training & consulting 120
6.3.2.2 System integration & testing 121
6.3.2.3 Support & maintenance 122
6.3.3 MANAGED SERVICES 123
7 EDGE AI SOFTWARE MARKET, BY DATA MODALITY 124
7.1 INTRODUCTION 125
7.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY DATA MODALITY 125
7.2 VISUAL DATA 127
7.2.1 NEED FOR QUICK DECISION-MAKING TO DRIVE DEMAND 127
7.2.2 IMAGE DATA 128
7.2.3 VIDEO DATA 128
7.3 AUDITORY DATA 128
7.3.1 INCREASING REQUIREMENT FOR SPEEDY RECOGNITION OF AUDITORY SIGNALS TO BOOST MARKET 128
7.3.2 AUDIO DATA 129
7.3.3 AUDIO SENSOR DATA 130
7.4 TEXTUAL DATA 130
7.4.1 NEED FOR QUICK RESPONSE TO TEXT DATA TO DRIVE MARKET 130
7.4.2 STRUCTURED TEXT DATA 131
7.4.3 UNSTRUCTURED TEXT DATA 131
7.4.4 SEMI-STRUCTURED TEXT DATA 132
7.5 SPATIAL DATA 132
7.5.1 GROWING ADOPTION OF LOCATION-BASED APPLICATIONS TO PROPEL MARKET 132
7.5.2 GEOSPATIAL DATA 133
7.5.3 LOCATION SENSON DATA 134
7.6 TEMPORAL DATA 134
7.6.1 RISING REQUIREMENT FOR PREDICTIVE MAINTENANCE TO BOOST MARKET 134
7.6.2 TIME-SERIES DATA 135
7.6.3 ENVIRONMENTAL SENSOR DATA 136
7.7 MULTIMODAL DATA 136
7.7.1 INCREASING NEED TO COMBINE INFORMATION FROM VARIOUS SOURCES TO DRIVE DEMAND 136
7.7.2 MULTIMODAL FUSION 137
7.7.3 CROSS-MODAL FUSION 138
 
8 EDGE AI SOFTWARE MARKET, BY TECHNOLOGY 139
8.1 INTRODUCTION 140
8.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY TECHNOLOGY 140
8.2 GENERATIVE AI 142
8.2.1 INCREASING NEED FOR CONTENT CREATION AT LOCAL LEVEL TO DRIVE MARKET 142
8.3 OTHER AI 143
8.3.1 ABILITY TO FACILITATE QUICK DECISION-MAKING TO DRIVE DEMAND 143
8.3.2 MACHINE LEARNING 145
8.3.2.1 Supervised learning 146
8.3.2.2 Unsupervised learning 146
8.3.2.3 Reinforcement learning 146
8.3.3 NATURAL LANGUAGE PROCESSING 147
8.3.4 COMPUTER VISION 148
8.3.5 OTHER TECHNOLOGIES 149
9 EDGE AI SOFTWARE MARKET, BY END USE 150
9.1 INTRODUCTION 151
9.1.1 DRIVERS: EDGE AI SOFTWARE MARKET, BY END USE 151
9.2 MANUFACTURING 153
9.2.1 ABILITY TO ENHANCE OVERALL PRODUCTIVITY TO DRIVE MARKET 153
9.2.2 INDUSTRIAL AUTOMATION 154
9.2.3 PREDICTIVE MAINTENANCE 155
9.2.4 QUALITY CONTROL 155
9.2.5 YIELD OPTIMIZATION 155
9.2.6 CONDITION & PRECISION MONITORING 156
9.3 HEALTHCARE & LIFE SCIENCES 156
9.3.1 NEED FOR QUICK DATA ANALYSIS TO BOOST DEMAND 156
9.3.2 REMOTE PATIENT MONITORING 157
9.3.3 MEDICAL IMAGING 158
9.3.4 HOSPITAL MANAGEMENT SYSTEMS 158
9.3.5 REAL-TIME HEALTH DATA ANALYTICS 158
9.3.6 PERSONALIZED MEDICINE 159
9.4 ENERGY & UTILITIES 159
9.4.1 GROWING ADOPTION TO IMPROVE OPERATIONAL EFFICIENCY TO FUEL MARKET 159
9.4.2 SMART GRIDS 160
9.4.3 RENEWABLE ENERGY MANAGEMENT 161
9.4.4 ASSET MONITORING & OPTIMIZATION 161
9.4.5 ENERGY DISTRIBUTION AUTOMATION 161
9.4.6 PREDICTIVE ENERGY DEMAND FORECASTING 162
 
9.5 TELECOMMUNICATION 162
9.5.1 NEED TO OPTIMIZE NETWORK PERFORMANCE TO DRIVE DEMAND 162
9.5.2 5G INFRASTRUCTURE 163
9.5.3 REAL-TIME NETWORK MONITORING 164
9.5.4 SUBSCRIBER DATA ANALYTICS 164
9.5.5 AUTOMATED CALL ROUTING 164
9.6 RETAIL 165
9.6.1 INCREASING DEMAND FOR PERSONALIZED SHOPPING EXPERIENCES TO DRIVE MARKET 165
9.6.2 IN-STORE ANALYTICS 166
9.6.3 SMART CHECKOUTS 166
9.6.4 CUSTOMER BEHAVIOR ANALYSIS 166
9.6.5 INVENTORY MANAGEMENT 167
9.6.6 PERSONALIZED PROMOTIONS & OFFERS 167
9.7 AUTOMOTIVE 167
9.7.1 INCREASING DEMAND FOR CONNECTED VEHICLES TO DRIVE MARKET 167
9.7.2 AUTONOMOUS AND SEMI-AUTONOMOUS VEHICLES 168
9.7.3 ADVANCED DRIVER-ASSISTANCE SYSTEMS (ADAS) 169
9.7.4 DRIVER MONITORING SYSTEMS 169
9.7.5 IN-VEHICLE INFOTAINMENT SYSTEMS 169
9.8 TRANSPORTATION & LOGISTICS 170
9.8.1 ABILITY TO STREAMLINE OPERATIONS TO FUEL DEMAND 170
9.8.2 FLEET MANAGEMENT 171
9.8.3 ROUTE OPTIMIZATION 171
9.8.4 LOGISTICS AUTOMATION 172
9.8.5 TRAFFIC PATTERN ANALYSIS 172
9.8.6 SUPPLY CHAIN OPTIMIZATION 172
9.9 SMART CITIES 173
9.9.1 GROWING PRESSURE ON INFRASTRUCTURE AND PUBLIC SERVICES TO DRIVE DEMAND 173
9.9.2 TRAFFIC MANAGEMENT 174
9.9.3 WASTE MANAGEMENT 174
9.9.4 ENVIRONMENTAL MONITORING 174
9.9.5 SURVEILLANCE & SECURITY 175
9.9.6 EMERGENCY RESPONSE SYSTEMS 175
9.10 BFSI 175
9.10.1 RISING REQUIREMENT FOR FRAUD DETECTION AND PREVENTION TO PROPEL MARKET 175
9.10.2 FRAUD DETECTION & PREVENTION 176
9.10.3 AUTOMATED TRADING SYSTEMS 177
9.10.4 CUSTOMER SENTIMENT ANALYSIS 177
9.10.5 COMPLIANCE & REGULATORY REPORTING 177
 
9.11 CONSUMER ELECTRONICS & DEVICES 178
9.11.1 INCREASING DEMAND FOR FASTER RESPONSE TIMES TO FUEL MARKET 178
9.11.2 SMARTPHONES & TABLETS 179
9.11.3 WEARABLE DEVICES 179
9.11.4 SMART CAMERAS & SECURITY DEVICES 179
9.11.5 AUGMENTED & VIRTUAL REALITY (AR/VR) HEADSETS 180
9.11.6 CONSUMER DRONES 180
9.11.7 HOME APPLIANCES 180
9.11.8 OTHER DEVICES 181
9.12 OTHER END USES 181
10 EDGE AI SOFTWARE MARKET, BY REGION 183
10.1 INTRODUCTION 184
10.2 NORTH AMERICA 186
10.2.1 DRIVERS: EDGE AI SOFTWARE MARKET IN NORTH AMERICA 186
10.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK 187
10.2.3 US 195
10.2.3.1 Increasing government initiatives to propel market 195
10.2.4 CANADA 195
10.2.4.1 Collaborative efforts by government and private sector to drive market 195
10.3 EUROPE 196
10.3.1 DRIVERS: EDGE AI SOFTWARE MARKET IN EUROPE 196
10.3.2 EUROPE: MACROECONOMIC OUTLOOK 196
10.3.3 UK 203
10.3.3.1 Government support for research and development to fuel market 203
10.3.4 FRANCE 204
10.3.4.1 Increasing focus on real-time data processing to drive demand 204
10.3.5 GERMANY 204
10.3.5.1 Introduction of innovation hubs and collaborative platforms to boost market 204
10.3.6 ITALY 205
10.3.6.1 Rising focus on research activities to drive market 205
10.3.7 SPAIN 205
10.3.7.1 Government initiatives and private sector investments to drive market 205
10.3.8 REST OF EUROPE 206
10.4 ASIA PACIFIC 206
10.4.1 DRIVERS: EDGE AI SOFTWARE MARKET IN ASIA PACIFIC 207
10.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK 207
10.4.3 CHINA 215
10.4.3.1 Government support for AI-related research to drive market 215
10.4.4 JAPAN 215
10.4.4.1 Focus on infrastructure enhancement to boost demand 215
10.4.5 INDIA 216
10.4.5.1 Government focus on innovation to drive market 216
10.4.6 AUSTRALIA & NEW ZEALAND 216
10.4.6.1 Partnerships to leverage edge computing capabilities to boost demand 216
10.4.7 ASEAN COUNTRIES 217
10.4.7.1 Increasing government focus on responsible AI adoption to fuel market 217
10.4.8 REST OF ASIA PACIFIC 217
10.5 MIDDLE EAST & AFRICA 218
10.5.1 DRIVERS: EDGE AI SOFTWARE MARKET IN MIDDLE EAST & AFRICA 218
10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 218
10.5.3 MIDDLE EAST 226
10.5.3.1 Saudi Arabia 226
10.5.3.1.1 Growing demand for real-time data processing to fuel market 226
10.5.3.2 UAE 227
10.5.3.2.1 Focus on digital transformation to drive demand 227
10.5.3.3 Turkey 227
10.5.3.3.1 Industry-academic research partnerships to boost market 227
10.5.3.4 Qatar 228
10.5.3.4.1 Increasing adoption of IoT devices to drive demand 228
10.5.3.5 Rest of Middle East 228
10.5.4 AFRICA 228
10.6 LATIN AMERICA 229
10.6.1 DRIVERS: EDGE AI SOFTWARE MARKET IN LATIN AMERICA 229
10.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK 229
10.6.3 BRAZIL 236
10.6.3.1 Rising adoption of edge computing across sectors to drive market 236
10.6.4 MEXICO 237
10.6.4.1 Government support for digital transformation to fuel market 237
10.6.5 ARGENTINA 237
10.6.5.1 Increasing investment in digital infrastructure to drive demand 237
10.6.6 REST OF LATIN AMERICA 238
11 COMPETITIVE LANDSCAPE 239
11.1 OVERVIEW 239
11.2 KEY PLAYERS STRATEGIES/RIGHT TO WIN, 2023–2024 239
11.3 REVENUE ANALYSIS 241
11.4 MARKET SHARE ANALYSIS, 2023 242
11.4.1 MARKET RANKING ANALYSIS 243
 
11.5 BRAND/PRODUCT COMPARISON 244
11.5.1 BRAND/PRODUCT COMPARISON, BY OFFERING 244
11.5.2 BRAND/PRODUCT COMPARISON, BY DATA MODALITY 246
11.6 COMPANY VALUATION AND FINANCIAL METRICS 247
11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 248
11.7.1 STARS 248
11.7.2 EMERGING LEADERS 248
11.7.3 PERVASIVE PLAYERS 248
11.7.4 PARTICIPANTS 249
11.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023 250
11.7.5.1 Company footprint 250
11.7.5.2 Region footprint 251
11.7.5.3 Offering footprint 252
11.7.5.4 Technology footprint 253
11.7.5.5 End use footprint 254
11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 255
11.8.1 PROGRESSIVE COMPANIES 255
11.8.2 RESPONSIVE COMPANIES 255
11.8.3 DYNAMIC COMPANIES 255
11.8.4 STARTING BLOCKS 255
11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024 257
11.8.5.1 Detailed list of key startups/SMEs 257
11.8.5.2 Competitive benchmarking of key startups/SMEs 258
11.9 COMPETITIVE SCENARIO AND TRENDS 259
11.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS 259
11.9.2 DEALS 263
12 COMPANY PROFILES 269
12.1 INTRODUCTION 269
12.1.1 MICROSOFT 270
12.1.1.1 Business overview 270
12.1.1.2 Products offered 271
12.1.1.3 Recent developments 272
12.1.1.3.1 Product launches and enhancements 272
12.1.1.3.2 Deals 273
12.1.1.4 MnM view 274
12.1.1.4.1 Right to win 274
12.1.1.4.2 Strategic choices 274
12.1.1.4.3 Weaknesses and competitive threats 274
 
12.1.2 IBM 275
12.1.2.1 Business overview 275
12.1.2.2 Products offered 276
12.1.2.3 Recent developments 277
12.1.2.3.1 Product launches and enhancements 277
12.1.2.3.2 Deals 278
12.1.2.4 MnM view 279
12.1.2.4.1 Right to win 279
12.1.2.4.2 Strategic choices 279
12.1.2.4.3 Weaknesses and competitive threats 279
12.1.3 GOOGLE 280
12.1.3.1 Business overview 280
12.1.3.2 Products offered 281
12.1.3.3 Recent developments 283
12.1.3.3.1 Product launches and enhancements 283
12.1.3.3.2 Deals 284
12.1.3.4 MnM view 284
12.1.3.4.1 Right to win 284
12.1.3.4.2 Strategic choices 284
12.1.3.4.3 Weaknesses and competitive threats 284
12.1.4 AWS 285
12.1.4.1 Business overview 285
12.1.4.2 Products offered 286
12.1.4.3 Recent developments 287
12.1.4.3.1 Product launches and enhancements 287
12.1.4.3.2 Deals 288
12.1.4.4 MnM view 288
12.1.4.4.1 Right to win 288
12.1.4.4.2 Strategic choices 289
12.1.4.4.3 Weaknesses and competitive threats 289
12.1.5 NUTANIX 290
12.1.5.1 Business overview 290
12.1.5.2 Products offered 291
12.1.5.3 Recent developments 292
12.1.5.3.1 Product launches and enhancements 292
12.1.5.3.2 Deals 293
12.1.5.4 MnM view 293
12.1.5.4.1 Right to win 293
12.1.5.4.2 Strategic choices 293
12.1.5.4.3 Weaknesses and competitive threats 294
 
12.1.6 SYNAPTICS 295
12.1.6.1 Business overview 295
12.1.6.2 Products offered 296
12.1.6.3 Recent developments 297
12.1.6.3.1 Product launches and enhancements 297
12.1.6.3.2 Deals 297
12.1.7 GORILLA TECHNOLOGIES 298
12.1.7.1 Business overview 298
12.1.7.2 Products offered 299
12.1.7.3 Recent developments 300
12.1.7.3.1 Deals 300
12.1.8 INFINEON TECHNOLOGIES 301
12.1.8.1 Business overview 301
12.1.8.2 Products offered 302
12.1.8.3 Recent developments 303
12.1.8.3.1 Product launches and enhancements 303
12.1.8.3.2 Deals 303
12.1.9 INTEL 304
12.1.9.1 Business overview 304
12.1.9.2 Products offered 305
12.1.9.3 Recent developments 306
12.1.9.3.1 Product launches and enhancements 306
12.1.9.3.2 Deals 306
12.1.10 VEEA 308
12.1.10.1 Business overview 308
12.1.10.2 Products offered 308
12.1.10.3 Recent developments 309
12.1.10.3.1 Deals 309
12.2 OTHER PLAYERS 310
12.2.1 INTENT HQ 310
12.2.2 BAIDU 310
12.2.3 NVIDIA 311
12.2.4 ALIBABA CLOUD 311
12.2.5 BOSCH GLOBAL SOFTWARE TECHNOLOGIES 312
12.2.6 AZION 313
12.2.7 BLAIZE 314
12.2.8 CLEARBLADE 314
12.2.9 JOHNSON CONTROLS 315
12.2.10 MIDOKURA 315
 
12.3 STARTUP/SME PROFILES 316
12.3.1 AXELERA AI 316
12.3.1.1 Business overview 316
12.3.1.2 Products offered 316
12.3.1.3 Recent developments 317
12.3.1.3.1 Deals 317
12.3.2 EDGE IMPULSE 318
12.3.2.1 Business overview 318
12.3.2.2 Products offered 318
12.3.2.3 Recent developments 319
12.3.2.3.1 Deals 319
12.3.3 LATENT AI 320
12.3.4 TERAKI 320
12.3.5 EKKONO 321
12.3.6 SPECTRO CLOUD 321
12.3.7 BARBARA 322
12.3.8 INVISION AI 322
12.3.9 HORIZON ROBOTICS 323
12.3.10 KNERON 323
13 ADJACENT AND RELATED MARKETS 324
13.1 INTRODUCTION 324
13.2 EDGE COMPUTING MARKET - GLOBAL FORECAST TO 2029 324
13.2.1 MARKET DEFINITION 324
13.2.2 MARKET OVERVIEW 324
13.2.2.1 Edge computing market, by component 324
13.2.2.2 Edge computing market, by organization size 325
13.2.2.3 Edge computing market, by application 326
13.2.2.4 Edge computing market, by vertical 326
13.2.2.5 Edge computing market, by region 327
13.3 ARTIFICIAL INTELLIGENCE (AI) MARKET - GLOBAL FORECAST TO 2030 328
13.3.1 MARKET DEFINITION 328
13.3.2 MARKET OVERVIEW 329
13.3.2.1 Artificial intelligence market, by offering 329
13.3.2.2 Artificial intelligence market, by technology 330
13.3.2.3 Artificial intelligence market, by business function 331
13.3.2.4 Artificial intelligence market, by vertical 332
13.3.2.5 Artificial intelligence market, by region 333
 
14 APPENDIX 335
14.1 DISCUSSION GUIDE 335
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 341
14.3 CUSTOMIZATION OPTIONS 343
14.4 RELATED REPORTS 343
14.5 AUTHOR DETAILS 344