Mobile Edge Computing Market Overview
The global mobile edge computing (MEC) market reached US$ 0.6 billion in 2022 and is projected to grow to US$ 3.1 billion by 2030, registering a CAGR of 26.3% during 2024-2031. Mobile edge computing is critical for applications requiring extremely low latency, including augmented reality (AR), virtual reality (VR), autonomous vehicles, and IoT devices. By processing data closer to the source rather than in centralized cloud servers, MEC reduces latency and enhances the user experience. The rapid rollout of 5G networks provides the high bandwidth and ultra-low latency necessary for MEC deployments, enabling localized processing, faster response times, and efficient use of network resources.
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For example, on 26 September 2023, Telkomsel, Southeast Asia’s largest telecom provider, selected Amazon Web Services (AWS) as its preferred cloud partner for digital transformation. This collaboration involves migrating Telkomsel’s IT applications including customer channels, gaming platforms, middleware, and machine learning workloads to AWS. With over 153 million subscribers in Indonesia, Telkomsel aims to improve user experience and rapidly deploy new services using MEC-enabled cloud solutions.
Recent Developments:
✅ January 2026 – North America: A leading telecom operator launched a 5G‐powered mobile edge computing platform with integrated AI analytics and edge‐native applications for smart manufacturing and autonomous vehicle validation.
✅ December 2025 – Europe: A major networking vendor unveiled commercially available micro‐edge data centers designed for telco and enterprise edge deployments, accelerating MEC adoption in smart city and Industry 4.0 use cases.
✅ November 2025 – Asia‐Pacific: A leading cloud service provider partnered with a regional carrier to deploy MEC nodes across key metropolitan areas, improving connectivity for AR/VR applications, low‐latency gaming, and IoT services.
✅ September 2025 – Middle East: A telecom group announced the rollout of edge‐enabled 5G private networks for enterprise customers, enabling localized computing for logistics automation and real‐time analytics.
✅ July 2025 – Global: Several major OEMs collaborated on a joint MEC interoperability initiative, establishing a framework for multi‐vendor edge orchestration, standardized APIs, and seamless workload mobility across networks.
Mergers & Acquisitions:
✅ January 2026 – Global: SoftBank announced the acquisition of DigitalBridge Group for ~US$4 billion, expanding its digital infrastructure portfolio to include edge systems such as data centers and fiber networks, strengthening MEC and AI infrastructure capabilities.
✅ August 2025 – Global: Acumera acquired Scale Computing, combining edge computing platforms with virtualization and secure infrastructure capabilities to accelerate edge AI and MEC deployments.
✅ May 2025 – Global: Veea completed the acquisition of Crowdkeep, enhancing its AI-enabled smart space and edge IoT solutions-broadening its edge market offerings.
✅ April 2025 – Global: Northstar Technologies Group acquired a majority stake in Compass Quantum (formerly Compass Edgepoint Systems), expanding its modular edge solutions and defense‐oriented MEC capabilities.
✅ March 2025 – Global: Qualcomm acquired Edge Impulse, strengthening its edge AI and IoT development platform to accelerate machine learning model deployment on edge devices.
✅ February 2025 – Global: NXP Semiconductors acquired Kinara for US$307 million to enhance edge AI capabilities in automotive, industrial, and IoT segments.
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Key Players:
• Advantech Co., Ltd. – Holds a 12.5% share, driven by its industrial edge computing platforms, AI-enabled IoT solutions, and robust deployment in smart city and manufacturing applications.
• Johnson Controls International plc – Holds a 10.8% share, supported by its building management systems integrated with edge computing for energy optimization and IoT connectivity.
• Hewlett Packard Enterprise Development LP – Holds a 9.7% share, fueled by its HPE Edgeline Converged Edge Systems and enterprise-grade edge infrastructure solutions.
• Huawei Technologies Co., Ltd. – Holds an 11.2% share, leveraging MEC platforms and 5G-integrated edge solutions across telecommunications and industrial IoT sectors.
• Juniper Networks, Inc. – Holds a 7.9% share, driven by its secure network infrastructure and cloud-native edge solutions supporting low-latency applications.
• SAGUNA Network LTD – Holds a 6.5% share, focused on telecom edge computing solutions and network acceleration platforms for 5G and AI workloads.
• SMART Global Holdings, Inc. – Holds a 5.8% share, supported by its memory, storage, and processing solutions for MEC and industrial IoT deployments.
• Vapor IO, Inc. – Holds a 5.2% share, driven by its Kinetic Edge platform for data centers and distributed edge computing networks.
• Nokia Corporation – Holds a 12.1% share, fueled by its 5G and MEC solutions, enabling low-latency enterprise and telecom applications.
• Skyvera – Holds a 4.3% share, focused on AI-driven edge platforms and integrated computing for IoT and smart city deployments.
Market Segmentation:
By Component:
The market is primarily divided into Software (38%), Hardware (34%), and Services (28%). Software solutions, including edge orchestration platforms, AI/ML analytics, and MEC management software, dominate due to rising demand for low-latency applications. Hardware, including edge servers, gateways, and networking equipment, holds a significant share, while services comprising consulting, integration, and support complete the market mix.
By Organization Size:
Large Enterprises (65%) lead adoption owing to higher IT budgets, advanced digital infrastructure, and early deployment of edge-enabled 5G applications. Small & Medium Enterprises (SMEs) (35%) are gradually adopting MEC solutions, especially in logistics, manufacturing, and smart retail sectors, driven by cloud-based and subscription models.
By Application:
Smart Cities (25%) and IoT (22%) are the largest application segments, driven by urban infrastructure monitoring, traffic management, and connected device networks. Content Delivery (18%) is growing as low-latency video and AR/VR applications expand. Augmented Reality (15%) adoption is fueled by industrial training, gaming, and retail use-cases. Others (20%), including autonomous vehicles, healthcare, and predictive maintenance, contribute the remainder of market demand.
By End-User:
Manufacturing (28%) and Energy & Utilities (22%) are the top adopters, leveraging MEC for predictive maintenance, industrial automation, and smart grid management. Retail & Consumer Goods (16%) and Media & Entertainment (14%) use MEC to enhance digital engagement and content streaming. Transportation & Logistics (20%) adopt edge solutions for fleet management, route optimization, and real-time tracking.
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Regional Insights:
Asia-Pacific (38%) leads the global mobile edge computing market, driven by rapid 5G deployment, strong IoT adoption, and smart city initiatives in countries like China, Japan, South Korea, and India. Telecom providers and enterprises in the region are aggressively investing in edge infrastructure to support low-latency applications in industrial automation, smart cities, and AR/VR.
North America (32%) holds the second-largest share, led by the U.S. and Canada. The region benefits from advanced 5G networks, cloud-edge integration, and early adoption by large enterprises across industrial, healthcare, and retail sectors. Key developments include MEC-enabled AI analytics, content delivery, and IoT-based smart infrastructure.
Europe (18%) is experiencing steady growth, supported by investments in smart cities, industrial IoT, and energy management solutions. Countries like Germany, the UK, and France are leading in the deployment of mobile edge computing for manufacturing automation, content streaming, and connected transport systems.
Market Dynamics:
Drivers:
Rising Application of 5G
The deployment of 5G networks is a major driver for mobile edge computing, as it offers significantly higher bandwidth and ultra-low latency. MEC leverages 5G to process data-intensive applications such as 4K/8K video streaming, cloud gaming, autonomous vehicles, and large-scale IoT deployments. By processing data locally at the edge, MEC enhances security and privacy, reducing exposure of sensitive data during transit to centralized data centers.
Example: In February 2021, Singapore’s Singtel launched 5G edge compute infrastructure for enterprises, offering Microsoft Azure Stack integration. This enables applications such as drones, autonomous guided vehicles, robots, and mixed reality to operate with latencies below 10 milliseconds.
Adoption of Advanced Network Solutions
MEC optimizes bandwidth usage and alleviates network congestion by offloading processing tasks from centralized data centers to edge servers. Its scalable architecture allows for seamless addition of edge servers to handle growing workloads and increasing IoT device connectivity, ensuring efficient and responsive performance across industries.
Example: In February 2023, T-Mobile partnered with AWS to integrate 5G networks with cloud-based edge services. The solution, Integrated Private Wireless on AWS, supports use cases like remote industrial campus monitoring and predictive maintenance in manufacturing, facilitating faster MEC adoption.
Technology Advancement and Innovations
The integration of artificial intelligence (AI) and machine learning (ML) at the edge is accelerating MEC adoption. Edge AI enables real-time decision-making, predictive maintenance, and intelligent automation across industries while reducing the need to transmit sensitive data to centralized servers, improving security and efficiency.
Example: In September 2023, KaleidEO Space Systems demonstrated the first Indian edge computing capability in space, analyzing high-resolution satellite imagery in real time. This innovation enables satellites to process data independently, paving the way for advanced onboard analytics.
Restraints:
Limited Data Centers and Complex Server Management
Edge servers possess limited CPU, memory, and storage capacity compared to centralized data centers. Resource-intensive applications may still require cloud processing, creating latency for certain workloads. Scaling MEC infrastructure is complex and costly, requiring additional edge servers and careful integration with existing networks. Managing a distributed edge environment demands efficient orchestration, monitoring, and maintenance, which can be more challenging than centralized data management.
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