Tech companies have been on a tear in recent years, particularly due to the rise of AI. However, other segments within the tech sector might warrant your attention, like cloud computing, particularly edge computing. Edge computing differs from cloud computing in that it brings computing power to where the data is created. Since data does not have to travel a lot, it can be processed much quicker compared to centralized computing, like Amazon Web Services (AWS). The amount of data being created is growing at an exponential rate as more devices are being connected to the internet. Edge computing makes things easier as data is processed close to where it is made.
The Edge Computing Area is Likely to Get a Push
The edge computing market is expected to get a big push from the rise of artificial intelligence (AI), with total spending projected to reach $380 billion by 2028, according to a new IDC report. Businesses are expected to gradually move away from traditional on-site hardware and instead put more money into cloud-based infrastructure-as-a-service (IaaS) solutions that support AI workloads at the edge. IDC estimates that global spending on edge computing will hit $261 billion in 2025, and that number is expected to grow by nearly 14% each year. The main driver behind this surge is the increasing demand for powerful systems that can handle AI tasks.
According to Alexandra Rotaru of IDC, the Internet of Things (IoT) still leads as the top use case for edge computing, but AI, augmented reality (AR), virtual reality (VR), robotics, and drones are quickly catching up. “IoT is still the biggest, but AI and AR are growing fast. In about a year, AI may become the fastest-growing area,” Rotaru said. Right now, most of the spending is going into on-premises setups—things like servers and storage systems—to meet current needs. Rotaru noted that even though it’s already a large market, there’s still room for growth because this infrastructure is so important.
IDC’s report looked at many industries and found that the biggest edge spending will come from retail, manufacturing, transportation, utilities, and finance. These sectors continue to invest in technology despite economic uncertainties. Rotaru added that recent surveys show businesses are more optimistic about IT spending in 2025 than they were for 2024. This confidence matches findings from a PwC Global AI Study, which reported that most business leaders see AI as a major advantage and are either using it or planning to adopt it soon.
While companies are currently focused on buying hardware, IDC expects many to shift toward cloud and service-provider-based IaaS as time goes on. This opens the door for cloud companies to capitalize on their existing infrastructure. Rotaru said this shift is happening because cloud providers are becoming more capable of handling AI workloads at scale.
A team of software engineers at desks working on code for a cutting-edge cloud computing solution.
Our Methodology
We reviewed edge computing ETFs to compile a preliminary list of stocks and then selected the ones that were the most popular among elite hedge funds, as of Q4 2024.
At Insider Monkey we are obsessed with the stocks that hedge funds pile into. The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 373.4% since May 2014, beating its benchmark by 218 percentage points (see more details here).
13 Best Edge Computing Stocks to Buy According to Hedge Funds
13. Fastly, Inc. (NYSE:FSLY)
Number of Hedge Fund holders: 27
Today, businesses depend a lot on giving people smooth and fast online experiences. Fastly, Inc. (NYSE:FSLY) helps them do this with its edge cloud platform, which sends digital content quickly and safely to users. This helps websites and apps load faster and work better. The company does more than regular content delivery networks (CDNs). It also includes security tools, real-time data handling and lets developers run code right near the user, instead of far away in a central server. This is great for things like shopping, streaming, or live videos where fast response times are important.
While Fastly, Inc. (NYSE:FSLY) is a long-term prospect, according to analysts, the stock is facing short-term headwinds. The company closed out 2024, reporting a record fourth-quarter 2024 revenue of $140.6 million. This exceeded its guidance range of $136 million to $140 million. However, it represented a paltry 2% growth, both year over year and quarter over quarter. That said, the company saw better-than-expected seasonal traffic, along with market-share gains at the year-end. For the fiscal year 2024, the company generated revenue of $544 million, representing 7% year-over-year growth. On March 20, Oppenheimer resumed its ‘Perform’ rating on the stock, highlighting operational hurdles that could limit its near-term performance.
12. Ambarella, Inc. (NASDAQ:AMBA)
Number of Hedge Fund holders: 32
Ambarella, Inc. (NASDAQ:AMBA) makes software and low-power AI-chips for edge devices like sensors. Its technology enables real-time functions such as object recognition and video analysis while conserving power and bandwidth. The company’s technology is applied in automotive cameras, security systems, drones, robots, industrial machines, and consumer cameras. Their radar software enhances the accuracy and efficiency of existing radar chips, improving performance in mobility solutions. By processing data on devices (vs. cloud), Ambarella’s edge AI reduces delays, boosts efficiency, and enhances privacy.
On March 31, Ambarella, Inc. (NASDAQ:AMBA) announced significant developments in edge generative AI technology. The company shipped 30 million cumulative edge AI systems on chip. These developments highlight its leading position as a supplier of edge AI systems on chip. It also underscores the company’s ability to enable scalable high performance and a vision of AI applications across edge inference CVflow. Its latest 3.0 AI SoC portfolios should be able to support GenAI models from 0.5 to 34 billion parameters.