- 5G carries data about the physical world; 6G will allow the network to sense, understand and act upon it
- Singapore’s National University Health System shows what 5G healthcare can do now — and why the future includes 6G
- The defining 6G application will be the orchestration of sensors, robots and specialist AIs into one holistic, responsive system
ERICSSON INDUSTRY ANALYST EVENT 2026, BOSTON — There is a lot of skepticism about 6G, much of it inherited from carriers’ disappointment with 5G.
And therein lies the paradox. While 5G and 6G emerge from the same global mobile standards machinery, that is where the similarity stops.
5G was designed primarily as a communications network. 6G is beginning to look more like a distributed system for observing, understanding and eventually acting upon the physical world.
Put more simply: 5G carries data about the physical world. 6G will sense, understand and act upon it.
Yet the industry still compares mobile generations using the same old checklist: higher speeds, lower latency, more devices, better reliability. That checklist invariably ends with the same question: what is the killer application that will make carriers a lot of money?
Judged that way, 6G sounds like a more expensive version of 5G, arriving just as operators are wondering how they will make money from the network they have already built.
But 6G is not defined by any of those old criteria. Nor is there likely to be a killer application comparable to mobile video. The real change is architectural.
5G connects sensors. With integrated sensing and communications, 6G will make the radio network part of the sensing system.
5G transports information generated by applications. 6G will help combine multiple applications and AI models around a shared objective.
5G offers network slices and quality-of-service controls. 6G will dynamically assign performance to individual machines, robots and AI agents.
5G is cloud-native. 6G will be AI-native.
And while 5G can report the location of a connected device, 6G could combine positioning, radio sensing and AI to understand what is happening around it. The transformative power lies in those fusions of previously siloed capabilities.
An intelligent fabric
This came into focus at Ericsson’s analyst event in Boston today. Ericsson CTO Erik Ekudden described the future network as an “intelligent fabric” that must do “so much more than just passing traffic.” That includes hosting AI inference and adding capabilities such as sensing and precise positioning. He was describing an operational layer for the physical economy — part of the wider battle to control the gateway to the autonomous economy.
Healthcare offers one of the clearest early examples.
Dr Yujia Gao, a consultant surgeon and Center Director at Singapore’s National University Health System, explained how his hospital is already using enterprise 5G infrastructure with a healthcare network slice for applications that would have sounded improbable a decade ago. One converts patients’ CT and MRI scans into three-dimensional holographic images that surgeons can examine through mixed-reality headsets during an operation. Gao said the system has reduced surgical times by as much as 30% in some procedures and eliminated certain steps entirely.
The hospital is also experimenting with autonomous mobile robots, edge and cloud AI, medical education applications and hospital-at-home services. Mobile teams visiting patients have been moved from an ordinary consumer network onto the hospital’s enterprise 5G infrastructure.
These applications also expose the limit of today’s network. The imaging system performs one function. The logistics robot performs another. Patient wearables, security cameras, doors, infusion pumps and clinical applications still occupy separate technology stacks. They communicate over an advanced, reliable pipe that delivers their data predictably and securely. But it remains a pipe.
It does not yet combine those functions into a common understanding of the hospital.
Gao said healthcare has spent the past decade building “stacks and silos of AI capabilities.” His goal is to turn the network into “the AI fabric of the entire healthcare cluster.”
Imagine what that means in practice.
A hospital network detects that a patient has fallen without waiting for a wearable alarm. It identifies the patient, checks their medical history and live physiological data, alerts the nearest qualified clinician, clears a route for an autonomous medical cart and gives the responding team access to the appropriate diagnostic AI.
If a stroke is suspected, it could bring together patient monitoring, imaging, staff location, robotic assistance and specialist platforms such as Viz.ai or RapidAI.
No single application performs that function. It emerges from multiple sensors, machines and AI models working together.
Many of the individual elements can run over 5G. Connecting thousands of them into continuous, reliable and potentially life-critical closed loops requires something more: greater uplink capacity, precise positioning, integrated radio sensing, distributed computing and a network capable of adjusting itself as conditions change. Even 6G cannot create that system by itself. Applications, robots and AI agents will need a standardized way to request network capabilities.
They will need APIs.
A diagnostic AI may request guaranteed uplink capacity to receive medical images. A surgical robot may require ultra-reliable connectivity for a defined period. An emergency application may need to locate the nearest clinician and override lower-priority traffic. The API communicates that requirement, confirms authorization and invokes the necessary network capabilities.
Strategy meets market demand
This is where Ericsson’s strategy meets a genuine market need. Through Aduna, the network API company it created with major international carriers, Ericsson is trying to establish a common gateway through which applications can reach capabilities across multiple networks.
Today’s network APIs perform fairly bland functions such as number verification, fraud prevention and connectivity on demand. The same architecture could eventually allow robots and AI agents to request guaranteed performance, location, sensing, identity, security and edge-compute resources in real time.
When I asked Gao whether this convergence is where 6G becomes necessary, he agreed. Healthcare will need “AI integration, not just information integration,” he said. The network will have to “make sense of the AI on top of the AI.”
The industry is looking for a single application to justify 6G. The larger opportunity is the orchestration of many applications—robots, sensors, vehicles, digital twins and specialist AI systems — into one responsive system.
6G will provide the nervous system. APIs will determine who can use it, what they can ask of it and what they are permitted to make it do.
The phone will still be connected to 6G. It just won’t be the reason 6G exists.
Stephen M. Saunders MBE is a communications analyst and USPTO-registered inventor examining how digital infrastructure — 5G, cloud and AI — is reshaping industry, power and society, as well as underpinning the emerging, ubiquitous global digital economy. As anchor of FNTV and a longtime industry insider, he focuses less on growth narratives and more on execution, risk and how hyperscale technology is distorting markets, governance and society at scale.
Opinion pieces from industry experts, analysts or our editorial staff do not represent the opinions of Fierce Network.