AI is getting smarter, faster, and more human – but it can’t thrive without a network that keeps up. Emotion AI, ambulances that connect doctors on the move, factories that run themselves – these innovations all depend on split-second data exchange. In 2026, the story of AI won’t just be about intelligence, explains Ivo Ivanov, CEO of DE-CIX. It will be about the underlying infrastructure that enables it.
The hype around AI has been building for years, but if there’s one thing we’ve learned it’s that the term “AI” no longer refers to a single technology. Banks are preparing to roll out emotionally intelligent assistants that can sense frustration or hesitation in a customer’s voice. Ambulances are being linked to AI-controlled traffic systems and fitted with real-time sensors that can allow doctors to diagnose and intervene remotely. And on factory floors, AI agents are moving from simply assisting human operators: They are now capable of running entire production chains independently, making critical decisions along the way. What links these revolutionary developments across diverse industries is not just smarter algorithms, but the ability to move and process massive amounts of data at speed – securely, reliably, and wherever it’s needed.
But therein lies the challenge. According to Gartner’s 2025 Hype Cycle, technologies like agentic AI, multimodal generative AI, and open source LLMs have passed the “innovation trigger” stage and are now firmly in the “peak of inflated expectations.” Before the technology fully matures, we must now pass through the “trough of disillusionment” and the “slope of enlightenment.”
And this is where the real story of 2026 lies. The success of technologies like Emotion AI, remote healthcare, AI-assisted traffic controls, and autonomous micro-factories will be determined less by their software and more by the networks that carry their data. In other words, the technology itself won’t be the bottleneck – connectivity will be. These next-generation services demand ultra-low latency, global reach, and infrastructure that can integrate fiber, mobile, and satellite seamlessly. That’s why 2026 will be the year when infrastructure becomes the decisive factor in determining whether AI delivers on its promise.
Here are some of the breakthroughs and challenges we can expect to see in the coming years:
Trend 1: The Regulatory Paradox of “Emotion AI”
Financial services may well become the unlikely proving ground for emotionally adaptive AI in 2026. A new generation of digital assistants promises to pick up on hesitation, stress, or frustration in a customer’s voice and respond with greater empathy and consistency than current systems. Instead of a neutral bot responding to prompts, these algorithms will be able to adapt their approach based on a customer’s mood, vastly improving the digital user experience.
According to analysts, the Emotion AI market will grow to $9 billion by 2030, while the US Open Banking rule, which was finalized last year and is set to come into effect soon, will require banks to share account data securely through standardized APIs. Together, these shifts will open the door to a tidal wave of innovation, from personalized financial advice to embedded banking services delivered seamlessly within third-party platforms. For banks, fintechs, and consumers alike, this combination promises services that are faster, more flexible, and more intuitive than ever before.
But there will also be tension. The EU’s AI Act classifies Emotion AI as a “high-risk” technology, subjecting it to strict compliance and oversight. This will create something of a paradox: the volume of sensitive data being generated is exploding, but the freedom to use it appears to be narrowing. Handling financial, biometric, and emotional data will therefore require sovereign, compliant infrastructure that guarantees privacy, security, and control at every step. Without it, banks may fall foul of regulation or compromise consumer trust at the very moment these technologies start to mature.
Trend 2: Remote Healthcare and “Live” Ambulances
Healthcare has been a bedrock of AI innovation for years, and in 2026 that trend will continue with life-saving applications that operate in real-time across entire cities. Ambulances equipped with advanced cameras and sensors will stream high-resolution video and patient data directly to hospital specialists, allowing doctors to start collating patient data, carry out diagnostics, and guide paramedics through complex procedures before a patient even arrives. Trials are also underway in cities such as Chennai, where AI-controlled traffic lights are able to prioritize emergency vehicles, ensuring ambulances reach hospitals faster and with clearer routes.
However, turning pilots such as these into large-scale programs will demand a radical upgrade of digital infrastructure. Governments and hospitals are already looking to expand beyond test cases, fueling market growth in the 5G healthcare sector from $95 billion in 2024 to more than $362 billion by 2030. Delivering this use-case will require not only robust 5G and Beyond-5G (B5G) networks, but also the integration of low-Earth orbit (LEO) satellites to extend coverage and ensure it’s available wherever an emergency vehicle happens to be. Lives will depend on the split-second performance of this connectivity infrastructure.
Trend 3: Agentic AI and Autonomous Micro-Factories
Next year, manufacturing will become the new stage for showcasing how agentic AI can manage entire industrial ecosystems. Instead of simply automating routine tasks, AI agents are now able to analyze, predict, and act across full-scale production chains, from predictive maintenance and quality assurance to logistics and scheduling. One of the most disruptive applications will be AI-enabled 3D printing, which allows companies to mass-produce customized goods with unprecedented speed and precision. This runs parallel with the trend toward re-shoring production, as businesses seek to reduce reliance on fragile global supply chains and rising transport costs. Hyper-localized “micro-factories,” designed to operate autonomously near customer bases, may be the key to delivering goods faster while lowering carbon footprints.
And the implications for agentic AI even extend beyond our planet. With it’s Olympus Project, NASA is already experimenting with autonomous 3D printing facilities for moon-based production, capable of building landing pads and habitats from lunar regolith – a futuristic but telling example of how agentic AI can decouple production from traditional supply chains altogether. To achieve such a feat, data must be processed and exchanged instantly across entire geographies, which is currently still a challenge on earth. But if we take the necessary steps at home, the moon may soon follow. Micro-factories only work if they are tightly integrated with cloud services, edge computing, and interconnection platforms capable of scaling alongside the AI-driven supply chain.
What digital infrastructure is needed to support AI-powered industry revolutions?
Use cases like these demand low-latency connectivity to AI models and cloud services, the integration of different network technologies, and the exchange of sensitive data between partners along sector-specific or business model-based value chains. Whether in the health sector, manufacturing, or financial services, existing network architectures and infrastructure will not be sufficient to allow the coming AI-powered products and services to enjoy excellent performance wherever users are located.
As businesses push capabilities closer to data sources, micro data centers will proliferate across urban and industrial landscapes. Orchestration of fiber, mobile, and satellite networks in an interconnected mesh will be essential to ensure reach everywhere. Innovative interconnection solutions at Internet Exchanges – from peering with many different networks to exclusive private environments of selected partners – give companies sovereignty, control, and high-performance connectivity for every AI use case.
But there is an emerging solution in the deployment of AI Internet Exchanges (AI-IXs). Secure access to AI and cloud workloads for training and inference through DE-CIX’s recently launched AI-IX concept can be combined with the capability to build bespoke closed user groups separated from the public Internet. Innovative interconnection solutions offer companies in every sector control over their data pathways and compliant, high-performance data transfer for every use case. Interconnection innovation will impact the bottom line for AI and data driven business models in 2026.
As emotionally adaptive AI, connected ambulances, and autonomous micro-factories continue their ascent in 2026, demand for AI infrastructure and high-performance interconnection will only continue to grow. AI workloads deeply embedded into infrastructure through distributed, virtualized GPU clusters, and low-latency interconnects will fuel the connectivity needed to turn these proofs of concept into full-fledged applications that can benefit everybody, everywhere, all of the time. Make no mistake, connectivity is the new economy and latency is its most important currency.