The industry is already talking about 6G in the same breath as autonomous factories, digital twins, and AI-native networks—years before a single commercial network goes live. If that sounds familiar, it should: 5G followed the same script, promising sweeping transformation long before the business models to support it ever materialized. This time, with pre-commercial 6G deployments potentially arriving as early as 2028 and the cost of building next-generation infrastructure higher than ever, the industry may not get a second chance to get the sequencing right.
We sat down with Stephen Douglas, Head of Market Strategy at Spirent, a Keysight company, to unpack what it will actually take to turn 6G from a technical milestone into a commercial one. Douglas argues that the standards decisions being made right now—covering everything from AI-specific performance metrics to how sensing and precision timing get built into the network—will determine which capabilities operators can actually sell, and which ones become another generation of expensive infrastructure in search of a business case. From token-based economics to a 6G-powered “network time as a service,” Douglas lays out where he believes the real money will be made, and why the industry needs to define value before it defines the radio.
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VMblog: With 6G timelines accelerating and pre-commercial deployments expected as early as 2028, how do we avoid building technology first and searching for business value later?
Stephen Douglas: By starting from the value and working back to the technology, which is the opposite of how we usually do it. The industry has a habit of building the network and then asking what it’s for, and 6G is arriving too fast and costing too much to run that play again.
Take for example 3GPP’s TR 22.870 catalogue of over 161 potential 6G use cases. While TR 22.870 gives confidence that the industry has created a comprehensive requirements catalogue, it is not a demand-side business case. Over the next year a market-demand filter needs applied to assess their quantifiable value to the market, the markets willingness to pay, their day one deploy-ability, their global scale, and their incremental value compared to 5G-Advanced. This should allow the industry to identify a smaller number of high demand and investable uses cases which have the greatest potential for success on day one.
A useful shift I’ve seen is operators starting to think in the same economic units as their customers. For AI traffic, that unit is the token. Tokens are becoming the currency of AI, and increasingly the proxy for where economic value actually gets created, because AI usage is moving to consumption-based pricing on the number of tokens a model processes. If an operator wants a share of that, it has to speak that language, not just move packets and hope value attaches itself later.
That’s a discipline more than a technology. It means asking, for any new capability, what a customer would pay for and how you’d prove you delivered it, before you build it. And it means being able to measure and control delivery in terms the customer recognizes, token cost optimization, first response time, stream smoothness, service stability, optimal routing, rather than generic network management and statistics that don’t map to anything they care about. Build the control, measurement and the commercial model alongside the technology, not after it.
VMblog: 6G is already being marketed and discussed years ahead of any deployed network. What’s the risk of repeating 5G’s hype cycle, and how should the industry calibrate expectations this time around?
Douglas: The risk is real, that 6G repeats the same mistake. 5G was an important technological leap, but the public narrative often jumped too quickly from faster mobile broadband to autonomous factories, remote surgery, smart cities, and entirely new business models. Many of those outcomes depended on things outside the 5G system and standards. 6G faces the same danger, only amplified by bigger language around AI-native networks, sensing, spectrum, digital twins, and terrestrial, aerial, and satellite integration. The industry needs to calibrate expectations by being precise about what is research, what is being standardized, what has been proven in trials, and what can be deployed economically. 6G should be positioned less as a magic generational leap and more as a continuous architectural evolution toward intelligent, energy-aware, resilient, and software-driven networks. The promise is real, but credibility will depend on tying every claim to measurable capabilities, operational readiness, and use cases that can survive outside the lab.
VMblog: Looking back at the 5G era, what is the most important lesson the industry should carry forward as it defines the commercial model for 6G?
Douglas: Monetization can’t be an afterthought. 5G delivered the technical goods and then spent years hunting for the business case, and a lot of that hunting happened after the capital was already spent. The lesson is to design the commercial model in parallel with the network, not once it’s live.
That is where 5G-Advanced becomes strategically important. It is not simply another incremental release of 5G. It is a bridge between current network investments and the service models expected to define the 6G era. The most progressive operators are already using 5G-Advanced capabilities to test new business models, build ecosystem confidence and give enterprise customers a credible roadmap from today’s services to tomorrow’s 6G-native platforms.
Take for example Integrated sensing and communication, or ISAC, is the clearest example of a 6G capability that can create value before 6G arrives. The idea is that the same radio network that connects users and devices can also sense and interpret the physical environment, detecting presence, movement, and location from the way signals reflect and change.
Some operators are already building early versions of this with 5G-Advanced assets they already own. Existing massive MIMO radios, wider channels, sensor fusion, neighboring-cell information, and AI-based signal analysis can be combined into basic multi-static sensing, where the network reads reflections across several radio points rather than a single transmitter and receiver. That’s enough to infer and classify objects for real uses today: drone detection around airports and sensitive sites, perimeter monitoring for critical infrastructure, water-leak detection, traffic flow, crowd density, public safety. These don’t need high-resolution sensing on day one. They need dependable detection and integration with the systems a customer already runs.
The 6G upgrade path is where it gets interesting commercially. Native 6G ISAC should benefit from larger bandwidths, higher frequencies, denser antenna arrays, and AI-native signal processing, which together move the capability from coarse presence and movement detection toward high-resolution localization, 3D mapping, and in some cases material characterization. So, the play is straightforward: sell the first sensing services now, learn which industries actually pay for situational awareness, prove the operational model, and offer those same customers a migration path to richer 6G sensing later. That turns ISAC from a research topic into a staged commercial roadmap
VMblog: Many of the foundational 6G standards are being defined now. What decisions made over the next 12–18 months will have the biggest impact on future monetization opportunities?
Douglas: A few, and they’re not all radio.
The first is the migration architecture, how operators actually move from 5G to 6G and what it costs them in hardware. That decision has been outstanding for over a year, and it shapes the economics of everything that follows. You can’t build a confident business case on a transition path that isn’t defined yet.
The second set is less visible but matters just as much for monetization: how we define and standardize the metrics for AI services. Traditional KPIs, latency, jitter, loss, throughput, availability, are still necessary but no longer sufficient for interactive AI. The new ones the ecosystem is working on now, things like time to first token, deterministic reliability, energy per token, precise time and position synchronization, are what will let operators write and enforce SLAs for AI traffic. Whoever shapes those definitions shapes what’s sellable. Get them defined in an implementation-aware way and operators have a basis for differentiated, monetizable services. Get them wrong or leave them vague and you’re back to selling generic connectivity.
The third is making sure these capabilities are testable before they’re deployed, which is the unglamorous decision that determines whether any of the above survives contact with a real network.
VMblog: Beyond pure connectivity speed, which specific industries or use cases do you think will be the first to generate real commercial return from 6G — and why those first?
Douglas: The first real commercial returns from 6G are likely to come from industries where advanced connectivity, combined with AI compute, and sensing directly improve operations. This includes transportation, smart-cities, low-altitude economy, logistics, energy utilities, and defense. These sectors have measurable pain points around automation, robotics, remote operations, worker safety, asset tracking, machine vision, and environmental awareness. They will move first because 6G can potentially do more than connect machines, it can help networks sense location, motion, blockage, occupancy, equipment condition, and changes in the physical environment, turning the network into part of the operational nervous system.
A second early return could come from 6G acting as a distributed AI computational and sensing grid. Instead of only connecting devices to centralized clouds, 6G could link devices, edge sites, network infrastructure, sensors, and regional cloud resources into a real-time fabric for AI inference, integrated sensing, robotics, digital twins, autonomous systems, and predictive maintenance. That creates value where decisions must be made close to where data is generated, and it gives operators a path to monetize more than bandwidth by selling trusted edge compute, sensing intelligence, data movement, low-latency automation, and service-level guarantees.
VMblog: What is one emerging 6G opportunity that you believe is underestimated today but could become a major source of value over the next decade?
Douglas: While a sellable fabric for AI is the most likely major source of value, I personally think there are a few hidden capabilities in 6G such as “network time as a service” which could be a real 6G killer capability.
6G network-time-as-a-service is trusted precision time delivered by the network. Synchronized time, phase and frequency made available to devices, robots, sensors, vehicles, edge workloads and AI systems.
Its value is assurance, not just accuracy.
Why could it become a killer capability? – because time becomes a precise, trusted, and traceable asset delivered over the mobile network to a high demand global market.
6G is targeting timing as an integrated network capability, not just an add-on, aiming at microsecond-class synchronization as a baseline target for industrial, grid and local-area deployments scenarios, and sub-microsecond / nanosecond-class ambition for the most demanding use cases such as motion control, smart grid phase measurement, cooperative robotics and high-precision sensing.
Technical work is also underway in IEEE to integrate PTP/TSN with industrial Ethernet, for precision time synchronization plus deterministic networking for time-critical, low-latency systems, positioning 6G as part of the enterprise timing fabric rather than a standalone wireless island.
The ambition is for 6G to offer trusted and assured precision time, even in places where other timing including satellite timing is weak or unavailable. The network could expose time with measurable assurance – that includes accuracy, traceability, clock confidence, resilience status and policy control.
This would allow industries to coordinate distributed systems with far greater confidence, supporting use cases such as autonomous factories, smart grids, transport systems, financial timestamping, digital twins, sensing networks and AI-driven control.
Instead of every enterprise engineering its own timing fabric, an operator could offer to expose timing quality, synchronization status, assurance, and subscription-controlled clock service.
And, in addition to selling Premium timing SLAs operators could offer API-exposed timing assurance. This turns “time” from an invisible network utility into something applications can query, verify and pay for.
Operators could also package timing into higher-value solutions for things like grid phase measurement, robotic coordination, drone corridors, broadcast media production synchronization.
And if you consider national resilient-timing programs like eLoran or the UK’s National Timing Centre (NTC), operators could also work with these programs to offer “system of systems” solutions for mission critical industries. Here operators would fuse national resilient-time sources as upstream references, then distribute assured time over and alongside 6G time.
VMblog: If we’re sitting here in 2030 looking back, what would have to happen between now and then for us to say that 6G was a commercial success, not just a technical achievement?
Douglas: If we are sitting in 2030 looking back, we should probably treat that year as an early starting line for mainstream commercial 6G, not the point where the full ROI story is already proven. By then, success would mean the industry has moved beyond lab demonstrations and has credible early deployments, stable standards, available devices, usable spectrum, and a clear path to scaling. The first signs of commercial success would likely come from operators proving that 6G can carry more traffic without a proportional rise in energy cost, use AI-native operations to reduce complexity and outages, and support enterprise use cases in sectors like manufacturing, logistics, energy, healthcare, transportation, and defense where the ROI is measurable.
The bigger commercial test will play out over the years after 2030. For 6G to be more than a technical achievement, it has to create value for both enterprises and consumers. Enterprises need lower downtime, safer automation, better sensing, private-network performance, and new service revenue. Consumers need more than “faster phones”. They need better coverage, more reliable experiences in crowded areas, lower latency for immersive applications, AI glasses or spatial computing that actually work outside controlled demos, and services that feel meaningfully different from late-stage 5G. If 6G can improve network economics for operators while enabling applications people and businesses are willing to pay for, then it becomes a commercial success over the longer horizon, not just another impressive radio upgrade.
6G could also become commercially important if it demonstrates it can support turning the network into a distributed AI computational grid. Instead of treating AI compute as something that only happens in centralized cloud data centers or on individual devices, 6G could connect device, edge, regional cloud, and network resources into a more dynamic compute fabric. That could allow operators to support low-latency AI inference, model optimization, sensing-assisted services, robotics, autonomous systems, and enterprise AI workloads closer to where data is created. If operators can expose those capabilities through trusted APIs, service-level guarantees, and secure edge platforms, 6G may unlock new AI revenues beyond connectivity, selling distributed intelligence, compute proximity, data movement, and real-time decision support.
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