As the first month of 2026 comes to a close, the Internet of Things stands on the brink of major change. IoT Insider asked some of the industry’s most forward-thinking experts to outline some of the key issues and trends they expect to shape the year ahead.
Nik Kairinos, CEO & Founder, AI research lab, Fountech AI:
In the world of IoT, there is the potential to leverage developments in AI to improve the speed, efficiency and innovation of operations in ways we’ve not yet imagined. As AI evolves, the challenge is to keep up with these changes and understand how they can best be leveraged to optimise outcomes.
The collaboration between AI and IoT is a key tenet of Industry 5.0. Building on Industry 4.0’s digital transformation that focuses on automation and efficiency, Industry 5.0 focuses on – amongst other things – human-machine collaboration, where technology and human creativity come together. Therefore, as AI advances towards AGI (Artificial General Intelligence) where AI gains human cognitive abilities and reflects human traits more closely, there is symbiosis in AI’s (and then AGIs) role alongside IoT in contributing to Industry 5.0.
As AI develops and becomes increasingly sophisticated, a significant trend is the development and improvement of predictive AI, which can now predict outcomes with high accuracy. Predictive AI can now use data to map potential outcomes and predict what will happen, giving a likelihood score for each.
This development has the potential to transform how organisations across a number of sectors operate – moving decisions from being reactive to proactive.
In an industrial setting, combining predictive AI and IoT has a number of applications. For example, it can make operations safer by analysing data from IoT sensors, understanding the data and highlighting when it indicates that something could be about to go wrong – such as a faulty manufacturing process or a safety concern – and even initialising the action to stop it. It can examine data to improve efficiency by identifying new, innovative approaches that save resources or speed up processes. It can also find patterns and links that may not have been foreseen and identify the best outcome before new approaches are even tested. And, of course, it can improve decision-making, giving more, reliable information propelling innovation with greater insight and surety.
As these two great technologies develop at pace, the task now is to enhance how AI and IoT work together to ensure we get the best out of both.
Vivek Shah, Senior Director of Advanced Technologies at data centre tech firm, Molex
Performance gains in AI processors have shifted the network bottleneck from compute to connectivity. The data centre’s network fabric—the high-speed communication infrastructure of switches, optics and cabling that connects processors, accelerators and memory—has now emerged as the critical constraint on scaling AI networks.
Today’s high-performance data centres rely on a patchwork of specialised interconnect technologies such as PCIe, NVLink, Ethernet and the emerging Compute Express Link (CXL). Each excels within its domain, but stitching these protocols together introduces latency, power inefficiencies and management complexity that limit overall system performance.
The specific limitations of each interconnect highlight the challenges of heterogeneous AI fabrics. NVLink delivers exceptional GPU-to-GPU bandwidth within a server but does not natively scale across nodes. Ethernet and InfiniBand provide the required rack-to-rack and cluster connectivity, yet their protocol stacks and CPU-driven data handling introduce significant software overhead and latency penalties compared to native GPU fabrics. PCIe and the emerging CXL standard offer versatility for peripherals and memory, but they function primarily as specialized extensions for specific tasks rather than high-bandwidth GPU communication.
The industry’s vision for solving the patchwork problem is the unified fabric: a design that converges multiple specialised protocols into a single, high-performance network for AI-critical data traffic. The guiding principle is radical simplification. Rather than maintaining separate domains for PCIe, NVLink and Ethernet, a unified fabric creates a flat, composable network that seamlessly carries compute, storage and memory traffic across the data centre. This architecture materializes the “SuperNode” concept, which treats the entire cluster as a dynamically reconfigurable resource pool. In this model, a GPU in one rack can directly access memory in another with minimal overhead; storage traffic is consolidated into the same high-performance fabric, and compute resources can be dynamically reconfigured to maximise utilisation.
Multiple major industry initiatives are advancing this vision. These range from specific vendor proposals like Huawei’s UB-Mesh, which aims for more than 10Tbps of bandwidth per ASIC with sub-microsecond latency, to broader collaborative efforts like the Ultra Ethernet Consortium. The tangible outcomes directly address the inefficiencies of the current patchwork approach: significantly lower latency accelerates large-scale AI training, simplified infrastructure reduces operational overhead and dynamic resource allocation minimizes idle or underutilised hardware.
While the unified fabric represents a powerful architectural concept, its realisation shifts the primary engineering challenges to the physical layer, introducing a new class of demands across the entire interconnect path. At the on-chip I/O level, the massive bandwidth requirements are driving the adoption of co-packaged optics (CPO), where optical transceivers are integrated directly adjacent to the processor. This approach, while improving data throughput and energy efficiency, introduces new challenges in thermal management, power delivery and serviceability.
Cyrus Vantoch-Wood, Founder at venture studio, Insurgent
- Civilisational prototyping becomes a global mandate:The world is no longer content with abstract climate pledges. In 2026, companies will be judged by the prototypes they build to keep civilisation functioning. Local energy loops. Adaptive logistics. This is not the territory of futurists. It becomes the baseline expectation of serious businesses.
- Cognitive design takes the wheel:Craft is not dying; it is evolving. The next era combines the human hand with the machine mind. Artisans will shape materials and experiences with the intuition of centuries, while cognitive systems do the heavy lifting behind the scenes: optimising carbon pathways, simulating supply chain stress, predicting failure points, and refining materials at the molecular level. The premium shifts from nostalgia to intelligence.
- Contextual intelligence overtakes artificial intelligence:AI becomes background infrastructure, not the headline act. The competitive edge moves from brute processing power to contextual intelligence: systems that understand nuance, culture, geography, psychology, and ecological constraints. Companies that build dumb AI will collapse under their own hype.
Kenta Yasukawa is CTO and co-founder of Soracom
The true internet of connected things will begin to emerge. Humanoids, talked about and demonstrated in prototype form for years, will likely enter mass production and be offered for sale during 2026. Self-driving robotaxis from Waymo, Zoox, Tesla, and others will be hitting the road soon in greater numbers. These robotaxis, humanoids, and even some basic industrial robots depend heavily on connectivity to keep their AI models updated and collect more real-world data to train models further.
Images and Video will become the new input data of IoT. In 2026, video will become foundational for a new generation of IoT applications. This next phase of IoT is not about connecting more sensors but rather about extracting more meaning from audio visual information. Multi-modal AI models are capable of extracting meaning from image, video, and audio. By using camera devices as eyes and ears of AI, a great variety of use cases that were previously impossible will be possible. Connectivity, in this context, will serve as spine and nerves for AI.
Satellite-to-cellular services will create a highly competitive market for hybrid IoT connectivity. With many more satellites going into orbit and an increasing number of partnerships between satellite and cellular companies, a new, increasingly competitive landscape will quickly emerge in 2026. The many partnerships between satellite and cellular firms already announced should be followed by more in 2026, along with more commercial launches of hybrid services. As a result, providers will start to grow offerings beyond emergency services, expand hybrid satellite-cellular IoT coverage to new markets, and strive to develop better pricing and more focused solutions addressing the unique needs of customers in different industries.
eSIM that finally works as expected. 2026 is poised to mark the beginning of a new era for seamless global cellular connectivity. After years of cautious anticipation, the SGP.32 standard’s maturity, paired with more cooperative carrier ecosystems, will turn theoretical into operational. Enterprises are ready to move past fragmented regional profiles toward a single, manageable global identity for devices that roam between cellular, LPWAN, and satellite networks.
IoT will show us the way beyond the AI bubble. There will always be commentators debating whether AI is the next industrial revolution or just the next bubble. But step back from the headlines, and what’s clear is that AI hasn’t yet reached anywhere near its true potential, and neither has IoT. The original promise of IoT was never just about connecting devices; it was a vision of everything cooperating, sensing, and acting together to make the world work better. That vision remains largely unrealised, waiting for the missing piece. 2026 is the year that changes.
2026 will not be the year of flying cars or techno-utopian daydreams. It will be the year of grown-up innovation. What follows is not a list of trends. It is a set of fault lines that will define how companies survive, how capital flows, and how culture decides what it values next.
This article originally appeared in the February issue of IoT Insider.
