Edge Computing Market Outlook, 2029

Edge computing is revolutionizing the way businesses handle data, transforming industries by bringing computational power closer to where data is generated. This decentralized model offers numerous advantages, especially in an increasingly connected world where real-time data processing is becoming essential. With advancements in the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), edge computing is paving the way for faster, more efficient, and cost-effective systems. Edge computing refers to the practice of processing data closer to its source, rather than relying solely on centralized data centers.

This is done by using local edge devices or mini data centers that perform real-time processing and analysis of data. The concept is designed to overcome the latency issues that arise when data is sent to distant cloud servers for processing. Edge computing systems are particularly beneficial in scenarios where milliseconds matter, such as autonomous vehicles, smart cities, and industrial automation. The COVID-19 outbreak has boosted the use of data centers and edge computing. Moreover, as more of these technologies are adopted, investment in them is expected to fall considerably in the months ahead.

Businesses across many industry verticals are decreasing their expenditures or reducing their investments in enhancing servers and software to gain considerable cost reductions. There are a few outliers though, such as rising edge and IoT spending in the telecom and healthcare industries. Businesses use possibilities to respond to the present situation by providing new services. The telecommunications industry is making rapid progress in video conferencing software like Microsoft Teams and Zoom and is creating new solutions to meet the growing demand.

Edge computing has grown into a solution-specific technology, with special tools and architectures designed for specific use cases. Some use cases where the edge is expected to acquire a considerable share throughout the predicted time include next-generation CDNs, network function, 5G virtualization, and game streaming. This is the first phase toward a future wherein the edge becomes broadly available.

According to the research report, “Global Edge Computing Market Outlook, 2029” published by Bonafide Research, the market is anticipated to cross USD 48 Billion by 2029, increasing from USD 14.05 Billion in 2023. The market is expected to grow with a 23.45% CAGR from 2024 to 2029. The edge computing market is experiencing rapid growth, driven by several key factors. The exponential increase in IoT devices has led to a surge in the amount of data generated at the edge of networks. Processing this data in real time has become a necessity, especially in industries like healthcare, manufacturing, and transportation, where immediate insights can have a significant impact.

The need for low-latency and high-bandwidth applications is a critical driver. Applications such as augmented reality (AR), virtual reality (VR), and autonomous systems demand ultra-low latency, which is best achieved by localizing the computing process. This demand is helping to shape the growth of edge computing as more businesses adopt it to stay competitive in a fast-evolving technological landscape. Edge computing is finding applications across numerous industries, fundamentally changing how data is handled. In healthcare, edge computing enables real-time monitoring of patients through wearable devices, facilitating quicker response times and more accurate health assessments.

In manufacturing, smart factories leverage edge computing to streamline operations, optimize supply chains, and enable predictive maintenance. Another critical area where edge computing is making strides is in autonomous vehicles. These vehicles require massive amounts of data processing in real time to make split-second decisions. By deploying edge computing, these vehicles can reduce their dependency on distant data centers, ensuring they have the processing power they need right on board.

Market Drivers

• Proliferation of IoT Devices: The widespread adoption of Internet of Things (IoT) devices is a key driver of edge computing. As IoT devices generate massive amounts of data at the edge, it becomes impractical to send all this information to centralized cloud servers for processing. Edge computing allows for local processing, reducing the strain on cloud networks and ensuring faster decision-making and real-time insights. Industries such as manufacturing, healthcare, and agriculture are heavily benefiting from this shift.
• Need for Real-time Data Processing: In industries like autonomous vehicles, smart cities, and industrial automation, data processing speeds are critical. Edge computing offers low-latency solutions by processing data closer to its source, enabling instant decision-making. This is particularly vital for applications that require near-instantaneous responses, such as vehicle navigation systems, security surveillance, and predictive maintenance.

Market Challenges

• Security and Privacy Concerns: With edge computing decentralizing data processing across multiple devices, ensuring data security and privacy becomes a significant challenge. Many of the edge devices may not have the same robust security measures as centralized cloud servers, making them vulnerable to cyberattacks and data breaches. In sensitive industries like healthcare, finance, and critical infrastructure, safeguarding patient data, financial records, and operational data is paramount.
• Complexity of Network Management: Managing and coordinating a vast array of edge devices across various locations can be complex. Unlike cloud computing, which consolidates resources in a single data center, edge computing involves multiple distributed devices, often in remote or challenging environments. This decentralization can lead to issues in network connectivity, system maintenance, software updates, and performance monitoring, requiring sophisticated management tools and strategies.

Market Trends

• Integration with 5G Networks: The rollout of 5G networks is a significant trend accelerating the adoption of edge computing. 5G’s ultra-low latency and high-bandwidth capabilities make it an ideal enabler for edge computing, particularly for applications requiring fast, real-time data processing, such as autonomous driving, AR/VR, and remote surgery. The synergy between 5G and edge computing is expected to drive innovations in multiple sectors by improving connectivity and data throughput.
• AI and Machine Learning at the Edge: The integration of AI and machine learning into edge computing devices is a growing trend. By embedding AI algorithms at the edge, businesses can perform complex data analysis locally, rather than relying on cloud computing for insights. This trend is particularly impactful in industries like manufacturing (for predictive maintenance), retail (for personalized customer experiences), and healthcare (for real-time diagnostics and monitoring). With edge devices becoming smarter, they can autonomously process and act on data, reducing the need for human intervention and optimizing operational efficiency.

Hardware is leading in the edge computing market due to the increasing demand for localized processing power and real-time data handling.

As edge computing relies on processing data closer to its source, the demand for specialized hardware to support this decentralized model is growing. Traditional cloud computing infrastructures rely heavily on centralized data centers, but edge computing shifts this responsibility to distributed devices that must have sufficient computational power, storage, and networking capabilities to handle complex tasks locally. This shift drives the need for advanced hardware, such as edge servers, gateways, and specialized processors (like GPUs and FPGAs) that can perform real-time analytics and decision-making without the latency associated with sending data to distant cloud servers.

As industries such as manufacturing, healthcare, transportation, and smart cities rely on these real-time capabilities for autonomous systems, predictive maintenance, remote monitoring, and more, the role of hardware becomes pivotal in ensuring reliable, scalable, and efficient edge computing deployments. Additionally, with the rise of IoT devices generating enormous amounts of data at the edge, powerful hardware solutions are essential to process, analyze, and store data locally, enhancing performance and reducing dependency on central cloud infrastructures. Thus, hardware is critical in enabling edge computing to meet the increasing demands for speed, security, and operational efficiency in a variety of sectors.

Industrial IoT (IIoT) is leading in the edge computing market due to its need for real-time data processing and operational efficiency.

The Industrial Internet of Things (IIoT) is driving the adoption of edge computing as it requires the ability to process vast amounts of data generated by connected devices and sensors in real time. In industries such as manufacturing, energy, and logistics, IIoT devices are continuously monitoring machinery, production lines, and critical infrastructure, producing enormous volumes of data that need immediate analysis and response. Edge computing provides the solution by allowing this data to be processed locally, reducing the latency that would occur if all data were sent to centralized cloud servers for analysis.

This is crucial for applications such as predictive maintenance, where equipment failures must be detected and addressed before they cause costly downtime. Edge computing also enables real-time optimization of production processes, supply chains, and operational performance, which are essential for maintaining competitive advantage in industries where efficiency and uptime are critical.

Additionally, edge computing improves security by reducing the need to transmit sensitive industrial data over the internet, minimizing vulnerabilities and protecting operational processes. As IIoT continues to grow, the need for localized, real-time data processing at the edge is becoming increasingly important, positioning edge computing as an essential technology for the continued evolution of industrial operations.

Large enterprises are leading in the edge computing market due to their need for scalable, high-performance solutions to manage massive data volumes and optimize operations across multiple locations.

Large enterprises are at the forefront of adopting edge computing because they generate and rely on vast amounts of data that must be processed quickly and efficiently to maintain operational competitiveness. These organizations typically have distributed operations, spanning multiple geographic locations, which necessitate the deployment of edge computing to localize data processing and reduce latency. In industries such as retail, healthcare, manufacturing, and finance, large enterprises use edge computing to enable real-time decision-making, improve operational efficiency, enhance customer experiences, and optimize supply chains.

For instance, in retail, edge computing allows enterprises to analyze customer behavior in real time, while in healthcare, it facilitates rapid patient monitoring and diagnostics. By processing data closer to the source, edge computing minimizes bandwidth usage, reduces reliance on central cloud infrastructure, and enables more secure, efficient systems.

Furthermore, large enterprises often have the resources and technical expertise required to deploy complex edge computing infrastructure across diverse environments, making them ideal candidates to lead the market. As these enterprises continue to embrace digital transformation and the Internet of Things (IoT), edge computing has become a critical component of their strategies, offering greater agility, scalability, and the ability to leverage AI and machine learning at the edge for enhanced business outcomes.

The industrial sector is leading in the edge computing market due to its need for real-time data processing and enhanced operational efficiency.

In the industrial sector, edge computing is becoming a critical technology because it addresses the demand for instant data analysis and decision-making, which are essential for maintaining productivity and minimizing downtime. Industries such as manufacturing, energy, transportation, and utilities generate massive volumes of data from machines, sensors, and other connected devices. This data, when processed in real time, can lead to significant operational improvements such as predictive maintenance, quality control, and optimization of manufacturing processes.

By processing data locally, at the edge of the network, industrial operations can quickly identify issues, predict equipment failures before they occur, and make necessary adjustments to avoid costly disruptions. Edge computing also helps reduce latency and bandwidth dependency, which is especially important in critical systems where every millisecond matters. Furthermore, security is enhanced, as sensitive data does not need to be transmitted over long distances to centralized data centers, reducing the risk of data breaches.

The industrial sector’s need for continuous monitoring and efficiency, combined with the proliferation of IoT devices and the rise of smart factories, positions edge computing as a key enabler of digital transformation in these industries. As industrial companies embrace automation and AI-driven analytics, edge computing ensures that they can meet these demands while maintaining the flexibility, reliability, and speed needed to stay competitive in a rapidly evolving market.

North America is leading in the edge computing market due to its advanced technological infrastructure, high adoption of IoT, and strong investment in digital transformation across industries.

North America has emerged as a dominant player in the edge computing market due to its well-established technological ecosystem, which supports rapid innovation and large-scale adoption of cutting-edge technologies. The region benefits from a high concentration of leading tech companies, research institutions, and robust infrastructure, which facilitates the development and deployment of edge computing solutions. Industries in North America, particularly in sectors such as manufacturing, healthcare, retail, and automotive, have been quick to adopt IoT devices and automation technologies that generate vast amounts of data needing real-time processing.

As a result, edge computing enables these industries to process and analyze data closer to its source, reducing latency and optimizing operations. Additionally, North American businesses are heavily investing in digital transformation, with companies embracing artificial intelligence, machine learning, and big data analytics - technologies that are greatly enhanced by edge computing.

The region also benefits from significant government and private sector investments aimed at driving the growth of smart cities, autonomous systems, and advanced manufacturing. With this combination of infrastructure, innovation, and investment, North America is well-positioned to lead the edge computing market, as businesses continue to capitalize on the benefits of localized data processing and real-time analytics to enhance efficiency, security, and customer experience.

• In February 2024, AWS entered this agreement to help NTT DOCOMO deploy its nationwide 5G open radio access network (RAN) in Japan. With this development, AWS will continue to enable its truly cloud-native, sustainable, and AI-driven 5G networks. AWS is curious about its journey with NTT DOCOMO to deliver 5G Core and Open RAN with new levels of resiliency, energy efficiency, and enhanced customer experiences. (AWS has been working with CSPs for quite some time to develop solutions in advanced networking, silicon innovation, and edge services for 5G technology).
• In February 2024, Cisco collaborated with Intel. Cisco's innovation center, partners, and other vendors gained the opportunity to authenticate their 5G end devices and demonstration systems using Cisco's advanced Mobility Services Platform and Intel Mobile Edge Computing applications. Moreover, Cisco has collaborated with various radio access network (RAN) vendors to actualize innovative private 5G scenarios tailored for practical deployment in multiple industries.
• In January 2024, HPE acquired Juniper Networks to create the pathway for advanced networking solutions that bring cloud-native capabilities, AI management, and control for hybrid cloud environments when combined with HPE Aruba Networking. It is noteworthy in a related development that Juniper Networks launched its new security services architecture for edge data centers in October 2023.

Considered in this report

• Historic Year: 2018
• Base year: 2023
• Estimated year: 2024
• Forecast year: 2029

Aspects covered in this report

• Edge Computing Market with its value and forecast along with its segments
• Region & country wise Edge Computing market analysis
• Application wise Edge Computing distribution
• Various drivers and challenges
• On-going trends and developments
• Top profiled companies
• Strategic recommendation

By Component

• Hardware
• Software
• Service

By Application

• Industrial IoT
• Remote monitoring
• Content delivery
• AR/VR
• Others

By Enterprise Size

• Large enterprises
• SME

By End User

• Telecom & IT
• Industrial
• Retail
• Healthcare
• Others

The approach of the report:

This report consists of a combined approach of primary as well as secondary research. Initially, secondary research was used to get an understanding of the market and listing out the companies that are present in the market. The secondary research consists of third-party sources such as press releases, annual report of companies, analyzing the government generated reports and databases.

After gathering the data from secondary sources primary research was conducted by making telephonic interviews with the leading players about how the market is functioning and then conducted trade calls with dealers and distributors of the market. Post this we have started doing primary calls to consumers by equally segmenting consumers in regional aspects, tier aspects, age group, and gender. Once we have primary data with us we have started verifying the details obtained from secondary sources.

Intended audience

This report can be useful to industry consultants, manufacturers, suppliers, associations & organizations related to agriculture industry, government bodies and other stakeholders to align their market-centric strategies. In addition to marketing & presentations, it will also increase competitive knowledge about the industry.


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