Article originally published on Forbes.com. Image courtesy of Getty.
The need for fast, efficient and scalable data processing has never been greater. The dramatic growth we’ve seen in computing power, 5G networks, IoT devices and other data-intensive applications will only continue in the future. Nearly 328.77 million terabytes of data are generated every day. By 2025, global data creation is expected to surpass 180 zettabytes.
Existing data centers and cloud infrastructure are struggling to keep pace with the volume, speed and complexity of data without experiencing bandwidth and latency issues. Edge computing is an alternative approach that processes data closer to where it is generated, spreading out CPU, storage and memory across a large geographic network of points of presence—enabling faster response times and improved reliability and bandwidth.
In a 2023 Accenture survey of C-suite executives in 16 countries and 18 industries, 83% said that edge computing is critical to staying competitive, and 81% believed that delaying action on edge could prevent them from capitalizing on its full benefits. The companies with the most advanced edge adoption were four times more innovative, nine times more efficient and almost seven times more cost-effective.
Edge Computing In Action
Organizations in diverse sectors—including media, retail, e-commerce, manufacturing and gaming—can optimize their infrastructure and reduce latency with managed edge solutions. The following six edge computing use cases are transforming industries now.
1. SaaS And PaaS Performance
Most of the customers my company works with on network and infrastructure solutions are software-as-a-service (SaaS) or platform-as-a-service (PaaS) providers. It’s crucial for SaaS and PaaS companies to optimize performance for their customers, who expect fast load times and highly responsive applications.
Edge computing supports faster website and application performance by processing data closer to end users to reduce latency and avoid downtime. However, it can be difficult for companies to scale their platforms for global audiences—managing complex routing, supply chain logistics and import/export regulations in dozens of markets and currencies—only using internal resources. Many opt to work with partners to mitigate these challenges.
2. Edge AI
AI is growing at a remarkable pace. By 2030, the AI market is projected to reach $1.3 trillion, up from an estimated $214 billion in 2024. There are tremendous opportunities to combine edge computing and AI to generate immediate insights for decision-making and provide hyper-personalized user experiences. Companies can train AI models using large data sets, then deploy those models to run inferences at the edge, creating a fast, seamless experience for customers.
At the recent TechCrunch Disrupt conference, I met the leaders of a startup who are integrating AI with GPUs to produce personalized videos with prescription medication information. Instead of a pharmacist talking to a patient in person, the platform uses an AI-created video to provide specific instructions about the medication. The “person” featured in the video looks and speaks like a human, but because they are AI-generated, they can offer instruction in any language for a global audience.
More and more SaaS companies are approaching us to figure out the best ways to leverage AI technology and put AI chips at the edge. To do so, they need to efficiently distribute vast amounts of data with a robust network and significant computing power.
3. IoT Management
The amount of data generated by IoT devices is staggering. Trillions of data points are produced by everyday devices, such as smart home security systems, light bulbs and thermostats—and new devices are being released all the time. Edge computing offers localized processing for IoT devices, which facilitates real-time analytics and controls. But collecting and managing all of this information at the edge requires significant computing power. Providers need to invest heavily in hardware and network infrastructure to support this computing capacity in their platforms.
4.Personalization
Consumer expectations are higher than ever for the brands they interact with. According to McKinsey research, 71% of customers expect personalized interactions, and 76% feel frustrated when they don’t receive them.
Another startup at the Disrupt conference is integrating personalized recommendations into streaming video platforms. For example, if you sign into your Netflix account, the service will analyze your interests and viewing behavior to offer highly tailored suggestions, such as “the top five hour-long shows to watch this weekend to decompress.”
Customers increasingly expect these kinds of personalized experiences in retail and marketing. Brands can use edge computing to analyze user behavior in the moment to offer personalized content, ads and recommendations, but they must be prepared to process large volumes of data across a distributed edge network.
5. Infrastructure
Aging infrastructure in the U.S. poses health, safety and security risks. Edge computing has enormous potential to modernize decades-old infrastructure. Cities can use edge devices to optimize traffic flows at intersections, monitor air and water quality or identify potential maintenance concerns on bridges and roads—though leaders need to carefully consider the costs associated with hardware, data management, installation and maintenance.
6. Industrial Automation
Edge computing is driving major advancements in smart manufacturing environments. IoT devices, including temperature sensors, energy meters and camera systems, can collect real-time data from equipment and spaces to detect and prevent problems. By automating the analysis of continuously updated data at the edge, manufacturers can also optimize supply chain management and other processes, enhance quality control and predict when to schedule maintenance. Industrial automation can lead to significant cost- and time-saving improvements, but integration with legacy systems is a common obstacle. Manufacturers also need to maintain a consistent flow of data from industrial spaces to edge servers, which introduces operational challenges, especially in remote locations.
We’re in what feels like the gold rush of edge computing. It’s exciting to explore the possibilities, but it’s also important to take a clear-eyed view of what your company needs to be successful. Most organizations reach a point where they can’t manage the complexities of edge infrastructure internally, and they work with an external partner. If you take this route, look for a digital infrastructure partner that can meet your company’s specific needs, not just generic requirements. There is no one-size-fits-all approach. Edge technology is advancing rapidly, and you need a partner that can develop bespoke solutions for your goals.