In our 2025 predictions post, we attempted to look ahead to the year and contemplate what might happen in edge compute environments. Overall, we did pretty well, and we feel like edge computing had a big year of progress. Feel free to grade us on your own. We had a lot of fun with this, so we thought we’d take another crack at predictions for 2026. So without further adieu, here are our thoughts about the state of edge computing in the year ahead.
Edge AI will be a gateway for new edge deployments
Shocker, but people are interested in AI at the edge. What will that mean? We don’t know, but we predict that companies will deploy early-stage solutions using Large Language Models (LLMs) and Small Language Models (SLMs) this year.
Interestingly enough, we don’t believe that AI at the edge is particularly special. It is another tool in the toolbox for deploying useful software in a purposeful manner into meaningful environments.
Generalization — the use of a single intelligent model for many purposes — seems to be the dream that is being chased. While generalization is a great goal, we encourage edge architects to continue to consider the full range of solutions to business problems; in many cases, you may just need a tiny regression or image classification model that doesn’t require a cluster of GPUs. When considering language models, we continue to encourage general experimentation but production deployment of the smallest models possible. Things are changing rapidly, and it is not the right time for massive infrastructure investments. AI forward hardware solutions may be one option to consider (slot available but no card yet).
We strongly believe that the foundation for doing edge AI well is the same as the foundation for doing edge well in general. We also predict that some companies will hand-wave at the edge foundation, chase AI, and deal with challenges and instabilities as a result.
Connectivity will fade as a key constraint
Edge compute environments have historically been defined by their constraints, including things like harsh environmental conditions, small physical space, absence of technical support personnel, latency and bandwidth challenges, and unreliable connectivity.
While many of these constraints remain, we believe 2026 is the year when “unreliable connectivity” fades as a defining constraint at the edge. This is driven by solutions like Starlink that bring high (enough) bandwidth and connectivity to nearly all parts of the planet with a tenable cost profile. This could be used as a backup to a traditional connection, or as the primary in previously completely disconnected locations. That is not to say all edge sites will immediately benefit, but mostly available, high-speed connections should be a design goal in most new edge deployments. Connectivity solutions are worth a closer look from edge architects.
We do expect some confusion to emerge as architects and software developers figure out when to harness this connection and when to operate in a more traditional-to-the-edge “assume you could be disconnected” mode. Building quality systems that balance these paradigms will still be tough, but we at Edge Monsters will continue to share what we learn, so follow along!
The miniaturization trend continues
In 2025, we predicted that we would see increased miniaturization of computing devices, and indeed we did. One of the noteworthy devices of the year was the Nvidia DGX Spark. While not the fastest device for inference, it shows the trend of miniaturization is alive and well, bringing Grace Blackwell GPUs to a desktop or edge-friendly form factor. We expect to see this trend continue in 2026.
Containers and Kubernetes continue to reign supreme
In 2025, we predicted some competition for Kubernetes while also anticipating that the friction in harnessing it for edge deployments would continue to diminish. We believe those predictions came true. While there are bespoke deployments of Docker Swarm or proprietary container management platforms, Kube continues to dominate the landscape. The new contender on the scene is the WASM ecosystem, but it has yet to achieve mass adoption at the edge.
In 2026, we expect containers to remain the artifact of choice, largely due to developer familiarity and proven orchestration capabilities in Kube. Is there really a problem to solve here, or are we good for a while?
As we noted in some of our blog posts this year, there are a huge number of commercial vendors in the Kubernetes space for observability, devex platforms, and the newly emerging AI ops. We expect to see consolidation here, so pick your horse-to-ride carefully.
Finally, we expect a continued exodus from the virtual machine paradigm, driven by continued pricing pressures from VMware/Broadcom. We are interested to see where Proxmox goes and how KVM adoption continues.
On WASM specifically, we continue to love the vision and the dream, but observe that organizations still find it difficult to make the jump and get started. We are interested to see how this ecosystem develops this year and will be cheering for more progress.
Rising hardware costs will slow, but not stop, edge progress
While we remain bullish about the future of the edge, the cost paradigm we’ve observed in Q4 of 2025 and Q1 of 2026 has us concerned about edge deployments. The massive demand for memory and other components necessary for the massive datacenter build-out underway in the US is driving costs higher across the computing industry.
Faster, better, cheaper is not happening — and we don’t expect it to happen in 2026. Existing edge deployments are likely to see delayed refreshes in many organizations, and new deployments will have to factor in the higher costs to their business cases. This is one we’ll continue to watch throughout the year, but it will likely have a meaningful impact on the uptick in edge deployments.
Edge adoption will inch forward slowly, and then all at once
Years into the edge computing journey, we think the idea of deploying on-prem infrastructure at the edge is still a little clouded by the cloud or hampered by legacy (often OT) constraints. Organizations are still waking up to the opportunity in front of them. The first adopters have typically been in retail, manufacturing, and national defense.
2026 is likely to be a year of incremental growth for the industry, complicated by several factors such as economic uncertainty and rising hardware costs. We continue to believe an edge awakening awaits in the years to come.
2026 will be marked by uncertainty
2026 will be marked by a lot of uncertainty. Tariffs, interest rates, AI boom or bust, political tensions, inflation, supply and demand dynamics with hardware, and other such factors will make 2026 a challenging year. This will complicate edge business cases and make long-term bets challenging.
Despite the headwinds, we’re genuinely excited about where edge computing is headed. The foundations are stronger than ever, the talent is sharper, and the use cases are more compelling. AI is pulling new organizations into the conversation, connectivity constraints are fading, and the industry keeps proving that real, production-grade deployments are possible at scale. We’ll be watching 2026 closely and sharing everything we learn along the way.
The Edge Monsters: Jim Beyers, Colin Breck, Brian Chambers, Tilly Gilbert, Michael Henry, Michael Maxey, Chris Milliet, Erik Nordmark, Joe Pearson, Jim Teal, & Dillon TenBrink.
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