“Edge AI Software Market” research report covering the span of 2024-2032 delves into both qualitative and quantitative aspects shaping the market’s trajectory. Offering insights into key drivers, constraints, opportunities, and challenges, it furnishes comprehensive statistical data on market leaders and revenue forecasts. Additionally, the report highlights revenue growth across regional and country-specific markets, supplemented by a thorough competitive analysis and detailed company profiles for the forecasted duration.
The Edge AI Software Market has emerged as a key player in the field of artificial intelligence, offering advanced solutions for processing and analyzing data at the edge of the network. Edge AI software enables devices such as smartphones, IoT devices, and edge servers to perform real-time data processing and inference without relying solely on cloud-based services. This capability has significant implications for various industries, including manufacturing, healthcare, automotive, retail, and telecommunications.
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Market Overview:
According to recent market research, the global edge AI software market was valued at USD 1,459.8 Million in 2021. The market is projected to witness substantial growth, reaching a value of USD 8,049.8 Million by the year 2027. The compound annual growth rate (CAGR) for the forecast period is estimated to be 35.9%. This rapid growth is attributed to the increasing adoption of edge computing technologies, rising demand for real-time analytics, and the proliferation of IoT devices generating vast amounts of data at the network edge.
Edge AI is the disposition of artificial intelligence applications in devices all over the physical world. The AI computation has to be done near the user at the edge of the network, near to the location of the data, rather than centrally in a cloud computing facility or even a private data center. The market is set to boom at a double-digit growth rate owing to the increased advancements in AI-powered IoT in smart applications. The increased use of edge AI software in the 5G network industry also fuels the growth rate of the market.
On the other hand, the data privacy compliance standards are not proper in all regions which hamper the market growth to a limited extent. Moreover, AI and machine learning continue to develop, yet many AI disruptors lack the capacity to process complex AI, machine learning algorithms. Thus, such elements hinder the market growth.
Growth Influencers:
Advancements in AI-powered IoT (Internet of Things) for Intelligent Systems and Smart Applications
The extensive implementation of the Internet of Things has powered the detonation of big data. With the swift ability to amass data in every aspect of a business, the edge AI software are playing a prominent role. The AI-powered IoT software are used from industrial sensors, robots, to smart cameras. Thus, the increasing advancements fuel the market growth.
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Use of Edge AI computing in 5G network
The edge AI software aids numerous end use industries. Using such a top-notch software for 5G networking purposes decreased costs and provides faster insights. It also offers effective data control and a streamlined operation. The 5G network permits establishing data centers at edge modules, and implementing industry-specific networks aided by virtualization and software-defined networking principles in a single environment. 5G coupled with IoT offers stable and secured connectivity, which increases the preference rate of this market considerably.
Market Drivers:
Several factors are driving the growth of the global edge AI software market:
- Rising Demand for Real-time Analytics: With the growing volume and velocity of data generated by IoT devices, there is a growing need for real-time analytics capabilities at the edge of the network. Edge AI software enables devices to process and analyze data locally, allowing for faster decision-making and response times in critical applications such as autonomous vehicles, industrial automation, and healthcare monitoring.
- Advancements in Edge Computing Technologies: Technological advancements in edge computing, including improvements in processing power, memory capacity, and connectivity, have paved the way for the deployment of AI algorithms directly on edge devices. This has expanded the scope of edge AI applications across various industries, driving the demand for edge AI software solutions.
- Cost and Bandwidth Efficiency: Edge AI software offers cost and bandwidth efficiencies by reducing the need to transmit large volumes of raw data to centralized cloud servers for processing. By performing data processing and inference locally, edge devices can optimize bandwidth usage and minimize latency, resulting in faster response times and reduced operational costs.
Competitive Landscape:
The global edge AI software market is characterized by intense competition among key players, including IBM Corporation, Microsoft Corporation, Google LLC, Intel Corporation, and NVIDIA Corporation. These companies are actively investing in research and development initiatives to enhance their edge AI software offerings, expand their market presence, and gain a competitive edge in the rapidly evolving landscape of edge computing and artificial intelligence.
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The global edge AI software market is populated by several key players striving for market dominance. These players include:
- Anagog Ltd.
- Alef Edge, Inc.
- Amazon Web Services (AWS)
- Bragi.Com
- Azion Technologies
- Chaos Prime, Inc.
- Foghorn Systems, Inc.
- Clearblade, Inc.
- IBM
- Gorilla Technology Group, Inc.
- Imagimob
- TACT.AI
- Nutanix
- Microsoft
- Sixsq Sarl
- Synaptics
- Octonion
- TIBCO Software
- Veea Inc
Among others.
These key players collectively hold approximately 25% to 30% of the market share. To maintain their competitive edge, these companies engage in various strategic initiatives such as collaborations, product launches, mergers, acquisitions, and expansions.
Market Segmentation:
The global edge AI software market can be segmented based on several parameters, including deployment model, application, end-user, and geography. Common deployment models include on-premises edge AI software and cloud-based edge AI software. Applications of edge AI software span a wide range of use cases, including video analytics, predictive maintenance, anomaly detection, natural language processing, and autonomous navigation. End-users encompass industries such as manufacturing, healthcare, transportation, retail, energy, and telecommunications.
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Segments Overview:
By Component:
The global edge AI software market is segmented into components, data sources, applications, and end-users.
By Component:
- Software
- Software Tools
- Platform
- Services
- Training and Consulting Services
- System Integration and Testing
- Support and Maintenance
The software segment dominated the market with over 80% share in 2021. Within the software segment, the platform sub-segment is expected to create an opportunity exceeding USD 3,500 Million from 2021 to 2027.
By Data Source:
- Biometric Data
- Mobile Data
- Sensor Data
- Speech Recognition
- Video and Image Recognition
Biometric data is forecasted to exhibit the highest growth rate of 36.6%, while sensor data captured the largest market share of over 25% in 2021.
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By Application:
- Access Control
- Autonomous Vehicles
- Energy Management
- Predictive Maintenance
- Remote Monitoring
- Telemetry
- Video Surveillance
- Others
Energy management led the market with over 20% share in 2021. Conversely, remote monitoring is expected to present an opportunity surpassing USD 900 Million between 2021 and 2027.
By End Users:
- Advanced Industries
- Banking and Insurance
- Chemicals and Agriculture
- Consumer
- Cross-Vertical
- Energy and Materials
- Healthcare
- Infrastructure
- Media and Entertainment
- Public Sector and Utilities
- Retail
- Travel, Transport and Logistics
The healthcare segment experienced the highest growth rate of 37.2%. Meanwhile, the travel, transport, and logistics segment held the largest market share of over 20% in 2021.
Regional Overview:
The global edge AI software market is categorized into North America, Europe, Asia Pacific, Middle East & Africa, and South America.
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The Asia-Pacific region dominated with over 35% market share in 2021 due to extensive technological developments. Additionally, other regions such as North America, APAC, and Middle East and Africa are expected to witness significant growth rates.
Regional Analysis:
Geographically, the global edge AI software market is segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa. North America currently dominates the market, driven by the presence of leading technology companies, robust infrastructure, and early adoption of edge computing technologies. However, the Asia Pacific region is expected to witness significant growth during the forecast period, fueled by rapid urbanization, increasing internet penetration, and government initiatives to promote digital transformation.
Table of Content:
- Introduction
- Study Assumptions
- Scope of the Study
- Research Methodology
- Executive Summary
- Market Dynamics
- Market Drivers
- Market Restraints
- Industry Attractiveness – Porter’s Five Forces Analysis
- Market Segmentation
- Competitive Landscape
- Vendor Market Share
- Company Profiles
- Market Opportunities and Future Trends
- Industrial Chain, Downstream Buyers, and Sourcing Strategy
- Marketing Strategy Analysis
………Continued…!
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The global edge AI software market report provides insights on the below pointers:
- Market Penetration: Provides comprehensive information on the market offered by the prominent players
- Market Development: The report offers detailed information about lucrative emerging markets and analyzes penetration across mature segments of the markets
- Market Diversification: Provides in-depth information about untapped geographies, recent developments, and investments
- Competitive Landscape Assessment: Mergers & acquisitions, certifications, product launches in the global edge AI software market have been provided in this research report. In addition, the report also emphasizes the SWOT analysis of the leading players.
- Product Development & Innovation: The report provides intelligent insights on future technologies, R&D activities, and breakthrough product developments
- Pricing Analysis: Pricing analysis of various metals and other components used in the manufacturing
- Manufacturing Cost Analysis: Cost-share of various components in edge AI software
Investment by Key Players
o IBM
o Microsoft
o Apple
Regulatory Landscape
o The Personal Information Protection and Electronic Documents Act (PIPEDA)
o General Data Protection Regulation
o European Committee for Standardization
o Personal Data Protection Act
o Cloud Computing Framework
The global edge AI software market report answers questions such as:
- What is the market size and forecast of the global edge AI software market?
- What are the inhibiting factors and impact of COVID-19 on the global edge AI software market during the assessment period?
- Which are the products/segments/areas to invest in over the assessment period in the global edge AI software market?
- What is the competitive strategic window for opportunities in the global edge AI software market?
- What are the technology trends and regulatory frameworks in the global edge AI software market?
- What is the market share of the leading players in the global edge AI software market?
- What modes and strategic moves are considered favorable for entering the global edge AI software market?
The Main Goals of the Report Are:
- To examine and project the size of the market sector.
- To research the major players globally, including their SWOT analysis, market value, and market share.
- To identify, describe, and project market based on type, end use, and geography.
- To analyze the market advantages, challenges, risks, and constraints in the world’s major regions.
- To identify key trends and factors that are promoting or inhibiting market growth.
- To determine the high-growth segments to assess the market prospects for stakeholders.
- To evaluate each submarket carefully in terms of its own growth pattern and market contribution.
- To understand market dynamics, agreements, growth, and the introduction of new products as competitive advances.
- To strategically identify the major players and thoroughly examine their expansion plans.
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