For organizations expanding their operations globally in 2026, the focus is no longer on technology adoption itself, but on technology’s ability to enable faster, safer, and more predictable growth. M247 Global clients need digital infrastructures that deliver consistent performance, ultra-low latency, and seamless scalability—regardless of region or service complexity.
In this context, frictionless, low-latency data transport, optimized parallel processing, and the integration of AI directly into critical business processes—from data centers to factories, warehouses, and distributed ecosystems—become decisive factors for competitiveness. More and more organizations are moving away from “one-size-fits-all” cloud models, shifting instead toward platforms and infrastructures tailored to their industry, applications, and performance requirements.
Drawing on the most relevant international analyses and reports, we have synthesized the key technology trends that, from M247 Global’s perspective, will have the greatest impact in 2026 on how companies achieve their business objectives, scale digital services globally, and deliver fast, secure, and reliable experiences to their customers.
- Confidential computing secures data during processing
According to Gartner’s Top 10 Strategic Technology Trends for 2026, confidential computing is set to become a cornerstone of IT security. This technology relies on hardware-based Trusted Execution Environments (TEEs) - isolated and hardware-secured environments in which data can be processed without the risk of unauthorized access, not even by cloud service providers.
Driven by increasingly strict data privacy regulations, data localization requirements, and the rapid adoption of AI, confidential computing enables the secure execution of sensitive workloads in infrastructures traditionally considered untrusted. Gartner estimates that by 2029, 75% of processing carried out in such environments will be secured through confidential computing.
- Parallel processing taken to the next level with neuromorphic computing
Neuromorphic computing is a brain-inspired technology that uses circuits designed to mimic neurons and synapses, processing data through spiking neural networks (SNNs) that activate only when relevant information is detected (event-driven processing). Unlike CPUs and GPUs, which separate memory from processing, neuromorphic chips integrate these components, enabling highly efficient parallel processing, low power consumption, and ultra-fast response times. According to Juniper Research, neuromorphic technology will see widespread adoption in 2026, making it possible to overcome the bottlenecks of current AI systems.
- Ambient AI & Physical AI
Forbes predicts that Ambient Artificial Intelligence will transform the way we interact with technology by seamlessly embedding AI into everyday digital experiences. Operating continuously in the background—through sensors and devices in smart homes, wearables, or video cameras—Ambient AI perceives its surroundings, understands context, and anticipates user needs, enabling technology to adapt to people, rather than the other way around.
At the same time, Gartner is placing strong emphasis this year on Physical AI, which has already brought artificial intelligence into the real world through robots, drones, vehicles, and smart devices capable of making decisions and taking action. In BMW factories, vehicles are already moving autonomously along production routes spanning several kilometers.
These systems combine sensors, actuators, and AI models to automate physical tasks, translating the productivity gains of digital AI into real-world environments. By 2028, five of the top ten AI vendors will offer Physical AI products, and 80% of warehouses will rely on robotics or automation, according to Gartner estimates.
- “One-size-fits-all” clouds are no longer enough. Organizations are turning to Industry Cloud Platforms
In 2026, large organizations will move beyond generic cloud models and increasingly adopt Industry Cloud Platforms (ICPs)—end-to-end vertical solutions that combine infrastructure, applications, and data, tailored to the specific requirements of each industry. As a result, we will see a growing number of platforms designed specifically for sectors such as healthcare, finance, life sciences, gambling, or gaming, featuring industry-specific data models and preconfigured compliance settings.
Gartner predicts that by the end of this year, 70% of large enterprises will have adopted Industry Cloud Platforms—up significantly from just 15% in 2023.
- The rise of AI factories. Deloitte: “AI has grown up.”
In 2025, the European Union invested €200 billion in 19 AI factories, making it no surprise that Deloitte expects this trend to continue dominating the global landscape in the years ahead. According to MIT Sloan Management Review, we will see a growing number of “all-in” adopters building AI factories and dedicated infrastructure—particularly in cases where companies use AI primarily to power their own processes, rather than to sell AI as a product.
Deloitte defines AI factories as integrated ecosystems purpose-built for AI processing, combining:
- Dedicated AI processors (GPUs with high-bandwidth memory and CPUs optimized for AI orchestration)
- Advanced data pipelines that rapidly prepare data for AI models
- High-performance networks that minimize latency and enable GPU-to-GPU communication
- Algorithm libraries optimized for specific business objectives
- Unified orchestration platforms for managing multimodal AI workflows
Over the next 5 to 20 years, as new computing technologies mature, data centers will need to adapt and integrate increasingly specialized tools for dedicated applications, according to the same Deloitte analysis.
- Geopatriation
Geopatriation refers to the relocation of workloads from global hyperscale clouds to local or sovereign environments. The goal? Reducing geopolitical risk. This strategy includes redeploying workloads to sovereign cloud regions or bringing them back on-premises. The trend is driven primarily by geopolitical instability and increasingly stringent regulations. By 2030, 75% of companies will geopatriate their critical workloads, with a strong focus on prioritizing protection for high-risk assets, according to Gartner.
- The rise of microfluidic cooling
In 2026, microfluidic cooling is emerging as the standout next-generation cooling solution for AI chips. The technology uses microchannels etched directly into the chip, through which a cooling liquid circulates, removing heat directly at the source. The result: GPUs and AI processors cooled up to three times more efficiently than with traditional cooling systems—an essential capability for modern data centers and compute-intensive applications such as IoT data analytics.
- Zero-Trust Edge (ZTE)
Forbes also predicts that the rapid expansion of smart IoT devices and the shift toward remote and hybrid work will drive the widespread adoption of the Zero-Trust Edge concept. Security will no longer be concentrated solely in the cloud but will be integrated directly into devices at the edge of the network—from industrial equipment to smartphones—where data is created and accessed. In 2026, the focus will shift to real-time identity verification and minimizing the risk of man-in-the-middle attacks through continuous protection applied exactly where the risk occurs.
2026 is shaping up to be a transformative year, marked by the deployment of domain-specific AI agents and the promotion of digital provenance practices to ensure software and AI content transparency and integrity. We also anticipate significant developments in technologies such as Small Modular Reactors (SMRs), post-quantum cryptography, and AI supercomputing platforms. In this complex landscape, M247 Global reaffirms its commitment to bringing the most relevant cutting-edge technologies closer to its clients through continuous investment and innovative solutions.