The global edge computing market is projected to grow from $46.7 billion in 2026 to $328 billion by 2033. This is driven by increasing demand for real-time analytics, low-latency processing, AI-enabled workloads, and connected devices.
For technology leaders, that growth reflects a broader shift in how enterprise systems operate. Businesses are generating more data than ever. And increasingly, that data needs to be processed where it is created rather than routed back to a centralized environment. As a result, edge computing is becoming an important part of modern technology strategies.
Let’s take a closer look at the edge computing benefits driving adoption, where organizations are putting it to work, and what the future may hold as edge computing infrastructure continues to expand.
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What Is Edge Computing?
Edge computing is a distributed computing approach that processes data closer to where it is generated. These sites could include manufacturing facilities, retail locations, healthcare offices, connected devices, or remote sites.
Traditionally, data is sent to a centralized cloud platform or data center for processing and analysis. Edge computing moves some of that processing closer to the source, allowing organizations to analyze information, trigger actions, and support decision-making in near real time.
Edge computing infrastructure can take many forms, including:
- Local servers
- On-premises technology environments
- Connected devices
- Edge data centers
This infrastructure places computing resources closer to where data is generated. These environments help organizations process information locally while supporting broader cloud, AI, and enterprise technology strategies.
Edge Computing vs Cloud Computing
A common misconception is that organizations must choose between edge computing and cloud computing. In practice, most businesses benefit from both.
Cloud computing remains critical for large-scale storage, application hosting, advanced analytics, and enterprise-wide visibility.
Edge computing complements those capabilities by handling workloads that benefit from local processing and faster response times.
For many organizations, the future isn’t edge computing versus cloud computing. Rather, it’s a hybrid model where cloud and edge technologies work together to support business goals.
Edge Computing Benefits for Modern Enterprises
Organizations are adopting edge computing for a simple reason: some business decisions can’t afford unnecessary delays.
As connected devices, sensors, cameras, and applications generate more data, sending everything to a centralized location for analysis can create bottlenecks. Edge computing helps organizations process information closer to operations, improving responsiveness and efficiency.
Some of the most significant edge computing benefits include:
- Faster access to data and operational insights
- Reduced latency for critical applications
- Improved support for AI and real-time analytics
- Better use of network bandwidth
- Greater resilience in distributed environments
- Enhanced control over sensitive data processing
The rise of AI is also increasing interest in edge computing. Gartner notes that AI is actually accelerating edge computing adoption because more innovations interact directly with the physical world through connected devices, machines, and operational environments.
That shift is pushing organizations to rethink where computing happens. This is particularly true for use cases that depend on real-time insights, automation, and rapid responses to changing conditions.
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Who Is Using Edge Computing and What Are They Using It For?
Edge computing is no longer limited to one industry. Today, organizations are finding practical ways to bring computing closer to where work happens. While the use cases differ across industries, the goal is typically the same: putting technology closer to the moment where business decisions need to happen.
Here are a few of the industries utilizing edge computing today.
Manufacturing
Manufacturing remains one of the most established edge computing environments. Companies use edge computing to support predictive maintenance, machine monitoring, quality control, and automation initiatives.
For example, sensors and connected equipment can analyze performance locally and identify signs of wear or operational issues before downtime occurs. Edge AI capabilities can also support cost efficiency and real-time inspection processes that improve consistency while reducing delays.
Healthcare
Healthcare organizations are increasingly using edge computing to support remote patient monitoring, connected medical devices, diagnostics, and clinical imaging.
In many cases, processing data closer to the point of care helps provide faster insights while limiting the need to transfer sensitive information across networks. That combination of responsiveness and privacy can be particularly valuable in healthcare environments where speed and reliability matter.
Retail
Retail organizations are leveraging edge computing to improve inventory visibility, shopper experiences, analytics, and fraud detection efforts.
Connected cameras, sensors, and smart devices can process information locally to provide real-time insights into store activity, stock levels, and customer behavior. As retailers modernize store operations, many are also using edge computing to support advanced in-store applications and create more intelligent retail environments that can respond to operational and customer needs in real time.
Instead of waiting for information to travel through multiple systems, retailers can respond more quickly to operational challenges and opportunities.
Future Forecast with the Rise of Edge Computing
As organizations continue investing in connected devices, AI initiatives, automation, and distributed operations, the future of edge computing appears increasingly tied to the future of enterprise technology itself.
Industry forecasts point to continued growth as organizations expand edge computing infrastructure alongside cloud investments. Growth drivers include AI-enabled workloads, IoT adoption, industrial automation, connected healthcare, smart infrastructure, and rising demand for real-time analytics.
The advantages attracting organizations today are likely to remain relevant in the years ahead:
- Faster decision-making and response times
- Reduced latency for mission-critical applications
- Stronger support for AI and real-time analytics
- Improved operational resilience
- More efficient bandwidth usage
- Greater flexibility for distributed technology environments
At the same time, implementing and managing edge environments requires new expertise. Teams with skills in AI, cybersecurity, distributed computing, networking, infrastructure orchestration, and real-time analytics are increasingly important as edge deployments grow.
The organizations that see the greatest value from edge computing will be the ones that combine technology investments with the right people, processes, and operating models.
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Building Teams for the Next Generation of Technology
Edge computing is helping organizations move technology closer to where decisions happen, creating opportunities for faster operations, more responsive systems, and smarter use of data.
Organizations exploring edge computing need strong talent, technical expertise, and delivery capabilities to support cloud and edge environments, AI initiatives, cybersecurity priorities, modernization efforts, and long-term strategy.
Whether you’re scaling technology operations or preparing for the next wave of digital transformation, having the right mix of technology professionals, consulting support, and AI expertise can help turn emerging opportunities into measurable business outcomes. Insight Global helps organizations build those capabilities through talent, consulting, and AI-focused support designed to meet evolving business needs.
Contact our experts today to start the conversation about your company’s tech needs.
by Celine Pham 
by Emilie Skaug