Ericsson Says the Telco Edge Was Too Early

Ericsson has put a name to the failure of the last edge computing cycle. Joe Constantine, the company's Americas chief strategy and technology officer, told Fierce Network in a piece published by Diana Goovaerts on 21 August that mobile edge computing was early rather than wrong, and his summary of what went wrong is short. "Ten years ago, MEC was a supply side concept." What has changed, in his account, is that a demand driver has arrived. "We have AI inferencing. It's the growth opportunity, an application that MEC did not have at the time. So, if you look at this, we believe that the industry, the technology and the market is vastly different today from 10 years ago." He supports the traffic case with Ericsson's own forecasts, that global mobile traffic will triple between 2023 and 2029 with AI as the key driver, and that uplink traffic will grow 10 times by 2035. He argues the network has changed too, from best effort connectivity to 5G built for time-critical communication and capable of 15 millisecond latency and "five nines of reliability." Fierce notes in the same piece that TM Forum's chief executive has told it that operators should not bet the farm on the edge.

The diagnosis is correct and it is unusual to hear it from a vendor

Supply side concept is the right post-mortem, and it is the shortest accurate description of that decade anyone has offered on the record. Operators built edge capacity because they had property, power and a latency story, then went looking for someone who wanted it. The platforms worked. The buyers did not appear. When I wrote about a fully programmable multi-access edge platform in November 2018, the services I could name were faster file uploads, console games without a console, and editing a document without downloading it. Those were real improvements to existing experiences. None of them was a business that an enterprise procurement department was going to sign for. Inference is a materially better answer than that, because it is a workload with a measurable cost that somebody is already paying somewhere else. That is a genuine change in the argument and it should be credited before anything else is said about it.

15 milliseconds is a central office number

The interesting discipline in Constantine's case is that his own numbers settle the location question, and they settle it away from the radio. A 15 millisecond budget is a loose one. It is comfortably met from a metro exchange or a mobile switching office serving hundreds of sites, and it does not require compute at the tower. That matters because the edge conversation still routinely conflates two very different capital programmes. Putting accelerators in a few hundred central offices is a brownfield project on estate that is already zoned, powered, cooled, fibred and physically secured. Putting them at tens of thousands of cell sites is a different business with a different power bill, a different maintenance model and a different landlord. I have argued on the AI Grid that deployment starts at central offices and mobile switching offices for exactly these reasons, and the 2018 platform was built into the central office for the same ones. Nothing in the Ericsson case contradicts that. If 15 milliseconds is the requirement, the requirement is an exchange.

The economic claim is asserted rather than costed

"Routing all this traffic to a centralized cloud isn't just only slow, it's economically not even sustainable" is the load-bearing sentence of the whole argument, and it arrives without a number attached. There is no published cost per inference at a telco edge site set against the same inference in a hyperscale region, at comparable utilisation, including the operator's power, cooling, refresh and remote-hands costs. Until that comparison exists, the economic case for distribution rests on the intuition that moving bits is expensive and moving them less must therefore be cheaper. That intuition ignores utilisation, which is what actually decides the economics of accelerators. A central region runs its fleet hot across many customers and time zones. A metro edge site runs a smaller fleet against local demand that peaks and troughs. The traffic forecasts are also Ericsson's own, published in its Mobility Report, and a 10 times uplink projection reaching to 2035 is a forecast rather than an observation. It should be read as one.

Physical AI names a use case, not a counterparty

Asked what actually requires the edge, Constantine points to robotics and physical AI. "Any system that moves, so drones, vehicles, humanoids, robots talking to other robots, all these will become an autonomous system that needs a network to think with it." His example is an autonomous car whose onboard sensors can see what is in front of it but not around the corner, with network sensing supplying the rest. The technical case is sound. The commercial case has the same shape as the one that failed. A drone fleet, a warehouse robot estate and a vehicle platform are owned by companies that are not the operator, and the thing being sold to them is not raw compute, which they can buy cheaper elsewhere, but contextual awareness that the network holds and they do not.

Selling that is a coordination problem before it is a latency problem. Robots talking to other robots across an ownership boundary need an agreed model of what is being asserted, whose authority stands behind it, and what record both sides will accept afterwards. That is the gap I argued no runtime supplies, and that NGMN has now enumerated at length for coordination inside a single operator's own domains, which is the easier version of the same problem. An operator can install the accelerators in its exchanges this year. It cannot unilaterally produce the model that lets a vehicle manufacturer's autonomy stack trust and pay for what the network says about the road. The compute is the part of this that money can buy quickly, which is why it is the part vendors describe in detail.

What to watch

3 things. First, where the accelerators physically land. If operator edge AI deployments in the next 18 months are announced at central offices and metro sites, the location argument is settled and the cell site edge can be retired from the conversation. Second, a published cost per inference or cost per token at a telco edge site against a hyperscale baseline, from anybody, on the record. That single figure decides whether distributed inference is an economic position or a latency preference. Third, the first contract in which an enterprise pays an operator for network context rather than for compute or connectivity, because that is the class of deal the 2010s never produced and it is the only one that would show the demand side has actually changed.

EE Launches First Priority Consumer Network Slice

EE launched a service called Fast Lane on 20 August, and Telecoms.com reported it as the UK's first commercial network slice sold to consumers and small businesses. The mechanism is simple. When congestion is expected, the customer is moved onto a dedicated slice of EE's 5G standalone network, which the operator brands 5G+. The scenarios EE names are rush hour, major events, live streaming from a sold-out gig, taking card payments at a festival, joining a video call while travelling. Claire Gillies, chief executive of BT's Consumer Division, called it "the UK's first commercial network slice to deliver meaningful benefits to both consumers and businesses." EE says 5G+ now reaches around 54 million people, 78% of the UK population, with a plan to reach 99% by the end of March 2030, as part of a £40 billion investment programme. Fast Lane is sold only through a premium handset plan, not as a standalone or SIM-only option.

I want to start by emphasizing the innovative aspect. This is a real new revenue line. It is not a framework paper, it is not a pilot inside one operator's walls described as a capability across everyone's. Somebody is going to pay money to EE for a network attribute, and after 8 years of the slicing conversation producing conference sessions instead of invoices, that deserves to be said plainly. It is also the first time I can recall a British operator putting a retail price on differentiated network quality rather than on a bigger bucket of gigabytes. That is a category change and it is worth taking seriously.

The product is priced on scarcity, and the scarcity is the operator's own congestion

Now the rationale. Fast Lane sells preferential treatment at a congested cell. The value of the product is a direct function of how congested that cell is. Telecoms.com raised the obvious question, whether consumer slicing gives operators a reason to slow densification, and then answered it fairly by pointing at EE's own build plan, which is running hard from 78% coverage toward 99% and is backed by a £40 billion commitment. I do not think EE is withholding capacity. But the accounting point survives the good intentions. Willingness to pay for Fast Lane is highest exactly where the network performs worst, and it falls as the build succeeds. That is not a scaling revenue line. It is a harvest on a constraint, and the constraint is one the operator has publicly promised to remove.

A congestion-priced lane is a legitimate thing to sell and a bad thing to extrapolate. If I were modelling this, I would treat the addressable moments as a fixed and slowly shrinking pool: the stadium, the festival, the commuter peak, the trade show. Those are real, they recur, and they do not compound. The number to watch is not the launch, it is whether the attach rate holds in year 3 in the places where 5G+ has since been densified. That number is the only one that would tell you whether this is a product or a symptom.

Quality on demand shipped as a tariff because a tariff needs no shared model

Here is the part I find genuinely instructive, and it lands on an argument I have been making for a year. Quality on demand is 1 of the 4 showcase network APIs the GSMA has put at the centre of Open Gateway, alongside device location verification, SIM swap detection and number authentication. The industry has spent 3 years and roughly 300 mobile networks trying to sell that capability to developers through an interface, and this month the answer to why it has not converted arrived in the form of a systems integrator joining the programme. Meanwhile EE is selling the same underlying capability to a consumer, through a handset tariff, and it works.

The reason is the one I set out when I argued at DTW Ignite that the API is not enough. Fast Lane requires no shared model with anybody. One operator, one subscriber, one radio, one contract, one billing relationship. There is no counterparty to negotiate with, no ontology to agree, no authority delegated across a boundary the operator does not own, and no audit trail that two parties both have to accept. It is a unilateral act inside a single administrative domain, which is precisely the class of capability that ships. The Open Gateway APIs that shipped are all in that same class, single-attribute lookups and bounded requests inside one operator's estate, and I have argued that is part of why they are worth what they are worth. EE has just proved the rule from the other direction. Take the exact same network function, strip out the requirement to coordinate with an external party, and it goes to market in a quarter rather than a decade.

That could be read as a warning. The capabilities that clear the boundary problem are the ones an operator can sell to its own subscriber. Everything on the other side of the boundary, the enterprise AI negotiating a service level with a network AI, the slice provisioned and assured across two estates, still needs the meta-model of topology, ontology, authority, state and audit that I argued no runtime supplies and that NGMN has now enumerated at length. Fast Lane does not advance that work. It circumvents it.

Selling it only with a handset tells you what EE thinks it has

The packaging is the tell, and it is the detail I would push hardest on. Fast Lane is available only on a premium handset plan. Telecoms.com flagged that this may hamper uptake, which is true, but the more interesting reading is what it says about internal conviction. If you believe you have built a network capability, you sell it as an attribute of the connection, on any SIM, at a price, and you let the market tell you what it is worth. If you believe you have built a retention lever, you bolt it onto the highest-value handset tier where it defends an existing margin and never has to survive a standalone price test. EE has chosen the second. That is a rational commercial decision and it is also an admission that the capability is not yet trusted to stand on its own.

What to watch

4 things. First, whether EE ever offers Fast Lane SIM-only. The day it does, the company believes it has a network product; until then it has a device upsell with a network feature attached. Second, whether any operator anywhere publishes an attach rate or an ARPU delta for consumer slicing, because the launch is easy and the second year is the evidence. Third, whether the same capability shows up as a priced quality-on-demand API through Open Gateway at a comparable value, which would be the first real read on whether the boundary tax is worth what I think it is worth. Fourth, whether a lane sold on congestion sits comfortably inside the UK's net neutrality framework once it has scale rather than novelty. I am not going to declare a verdict on that one, and I would be surprised if nobody asks the question.

The industry has spent 8 years promising that slicing would let operators sell different connectivity products rather than by the gigabyte. The first commercial consumer version in Britain sells one attribute, at specific times, bundled with a phone. That is progress, and it is a fraction of the size of the story that was told to justify 5G standalone. 

NGMN Confirms Agentic AI Needs Improvements

The Next Generation Mobile Networks Alliance published a report on 12 August, "Network Automation and Autonomy Phase III: Agentic AI for Autonomous Mobile Networks," and it reads like a standards body catching up to an argument I have been making for a year. The headline finding, reported by Keith Dyer at The Mobile Network, is that the industry has to solve interoperability, security, governance and data before agentic AI can deliver autonomous networks at commercial scale. The detail underneath the headline is what matters. NGMN says the current ecosystem is too fragmented for agents to form a consistent understanding of the network, because vendors use different data models and different terminology, and it calls for common information models, ontologies and semantic mappings, aligned across 3GPP, TM Forum, ETSI, O-RAN, IETF, W3C and BBF. It asks for a telecom-grade Zero-Trust Agent Ecosystem with secure agent identity, authentication, authorisation, policy enforcement, audit logging, runtime monitoring, and the ability to revoke or quarantine an agent. Read that list again. Topology, ontology, authority boundaries, state, audit trails. That is the meta-model of the agentic plane, and it is now in a report with an operator alliance's name on the cover.

I want to be precise about the provenance here, because the sequence is the point. I argued at DTW Ignite that the API is not enough, that the interfaces we built for developer access were never designed to let an autonomous agent understand what it is acting on. I argued a few weeks later that the agent runtime is not the agent model, that a place to execute an agent and put guardrails around it supplies none of the topology, ontology, authority and audit that coordination between agents actually needs. NGMN has now enumerated eight cross-organisation challenge areas, and they map almost one for one onto that case. Lack of standards for agent knowledge and context sharing. Incomplete information modelling for networks. Lack of end-to-end security, identity and trust for autonomous functions. Lack of operator-friendly governance and lifecycle tools. Under-addressed economic and organisational readiness. When a body chaired by Orange's group CTO writes the same list I published, the argument stops being a contrarian read and becomes the consensus. That is a good day for the thesis. It is a better day to point out the part the report does not solve.

The report describes coordination inside a boundary the operator owns

Look closely at the architecture NGMN proposes. A supervisory agent coordinates specialist agents, one each for RAN, core, transport, cloud and security, to diagnose a service problem, weigh corrective actions, resolve conflicts, and verify that service was restored. The worked examples are fault management, service assurance and RAN optimisation. In the RAN case, a cross-domain agent delegates intent to a RAN optimisation agent, which supervises a sub-agent in the infrastructure layer, and when an optimisation action collides with network-wide energy management the cross-domain agent arbitrates the trade-off. This is a serious and correct piece of engineering. It is also, in every example, coordination across domains that a single operator owns. RAN, core, transport, cloud and security are five administrative domains inside one company's walls. The hard thing NGMN is describing is getting an operator's own silos, built by different vendors with different data models, to hand each other a shared and trustworthy understanding of state. That is worth doing, and it is exactly why a runtime and a set of guardrails were never going to be enough. But it is one owner reconciling with itself.

The problem I have been pointing at sits one boundary further out, and NGMN's own scope is the clearest evidence that it is a distinct and harder problem. When an enterprise's AI wants to negotiate with an operator's network AI, for a service level, a slice, a capacity commitment, a remediation, there is no shared owner to impose a common ontology, no single authority to issue the identities, and no single audit log that both parties will accept as the record of what was agreed and who was answerable. Everything NGMN specifies, the semantic alignment, the zero-trust identities, the audit trail, is defined for agents operating within the operator's estate. Across an ownership boundary, the same requirements do not disappear. They get harder, because now two parties have to agree on the model before either can trust an action, and neither controls the other. NGMN has validated that the meta-model is necessary. It has not, and by its own framing could not, close the gap where the two hardest words in this whole subject live, which are coordination and accountability between parties who do not report to the same CTO.

Containment, coordination, accountability, in that order of difficulty

It is worth keeping the three layers separate, because vendors and now standards bodies keep collapsing them. Containment is the Zero-Trust Agent Ecosystem: the identity, the authorisation, the runtime monitoring, the kill switch that lets you revoke or quarantine an agent inside your own network. That is genuinely useful and NGMN is right to specify it in detail. Coordination is the shared ontology and semantic mapping that lets one agent understand what another agent is doing, and this is the layer NGMN is now trying to build across an operator's internal domains. Accountability is the ability to produce, on demand, the identity of an agent, the authority under which it acted, and a trail that a regulator and an outside counterparty would both sign, across a boundary you do not own. The industry has spent a year shipping the first layer and calling it the third. NGMN has now, to its credit, put real weight on the second. The third is still open, and it is the one I argued the EU AI Act made expensive when its enforcement powers switched on at the start of this month, because enforcement does not stop at the edge of your administrative domain.

There is a discipline point here that operators should not lose in the enthusiasm of seeing a favourite thesis ratified. NGMN itself flags it: "While technology groups focus on architecture, few have formal guidance on the required telco organisational changes," and it lists economic and organisational readiness as an under-addressed challenge in its own right. The meta-model is not a product you procure. It is a set of agreements about topology, ontology, authority and audit that has to be built and then adopted, and the report's call for alignment across seven standards organisations is a fair description of how long that takes. Cross-SDO harmonisation of information models is measured in years, not quarters. When I helped set network autonomy targets in operator programmes, the technology was rarely the thing that slipped. The organisational change and the cross-domain agreements were. Anyone booking autonomous-network savings against a framework paper rather than a ratified model is doing the same thing I warn against when vendors stack their individual efficiency claims into a total no network has ever achieved. Read this report as the industry agreeing on the destination. Do not read it as arrival.

What to watch

The honest test has not changed, and NGMN has now made it a formal requirement rather than a personal opinion. For any action an agent takes on its own, can you produce its identity, the authority under which it acted, and an audit trail that both a regulator and an outside counterparty would accept. If the answer lives entirely inside one vendor's runtime, you have containment and you should not mistake it for accountability. NGMN has described the plane the runtime runs on, in more detail than anyone in the industry has committed to print, and it has correctly located the work in standards and organisation rather than in any single box. The next phase belongs to whoever builds the ontology and the identity fabric that hold up not just across an operator's own domains, but across the boundary to the enterprise on the other side of the negotiation. That boundary is where the value is, and it is the one the report stops at. Watch for whether the alignment NGMN asks for actually happens across those seven bodies, and watch, as always, for a pilot inside one operator's walls being described as autonomy across everyone's.

Agentic AI: Autonomous Agents Governance and Enforcement

As of yesterday, the European Commission can fully enforce the AI Act against providers of general-purpose AI models, and the transparency obligations under Article 50 begin to apply. The obligations themselves have been in force for a year. What changes now is teeth: Brussels can investigate, order corrective measures, and levy fines of up to 15 million euros or three percent of worldwide turnover, whichever is higher. Tech Policy Press reported the shift on the 13th of July, and made the point that gives it weight for anyone building networks. The enforcement switch flips just days after the first reported case of an autonomous AI agent carrying out a cyber operation nobody asked it to perform, compromising the Hugging Face platform, as Reuters reported on the 28th. The capability and the accountability mandate arrived in the same week, and they are pointed at each other.

For a month I have watched the telecom industry celebrate the exact capability the regulation now proposes to hold someone answerable for. AT&T describes tens of billions of tokens and over a hundred billion network signals processed daily, 4-hour investigations cut to a minute, and roughly 30 times return. TM Forum reports the sector crossing into Level 4 autonomous networks. Vendors are shipping the agentic NOC and the self-healing network. The good news and the governance problem are the same sentence. Agents are now taking actions in production that no human reviewed in the moment. That is the point of them. It is also the point at which a regulator asks who is answerable.

Enforcement is not an abstraction. To sanction a provider, or to defend yourself as an operator, you have to be able to say which agent took which action, under whose authority, with what audit trail, and across which administrative boundary. In a telecom network that last clause is the hard one. An agent that chains tool calls across provisioning, billing, customer records, and network management is doing precisely the thing that no single log captures and no single owner witnesses end to end. When an autonomous action provisions a service, pulls subscriber data, or adjusts an account, it has crossed several systems that were never designed to hand each other a shared, signed record of intent and authority. The action happened. Reconstructing who owned it is the part that does not exist yet.

This is the meta-model of the agentic plane that I have argued the industry keeps skipping. I made the case that the agent runtime is not the agent model, and before that, at DTW Ignite, that the API is not enough. The coordination problem needs a model of topology, ontology, authority boundaries, state, and audit trails. A runtime supplies none of those across a boundary. It supplies execution and guardrails inside one administrative domain. That is containment, and containment is a genuinely useful thing to own, but it is not coordination between two parties and it is not accountability across them. The regulation just made the distinction expensive.

Let's watch how the two sides of the Atlantic are responding, because the contrast is instructive. In the United States, lawmakers are floating an AI kill switch, the option to suspend or shut a model down when the risk gets severe. A kill switch answers one question well: can I stop it. It answers a different question not at all: who was this agent authorized to act for, and can you produce the record that a regulator and a counterparty would both accept for what it already did. Stopping an agent and being answerable for it are not the same capability, and only one of them is a compliance obligation as of this morning.

So the discipline for operators moving to higher autonomy is now imposed rather than optional. Compliance turns the audit trail and the authority boundary from an architecture nicety into a requirement you can be fined for missing. The honest test is the one I would put to any autonomous-network business case. For any action an agent takes on its own, can you produce the identity of the agent, the authority under which it acted, and a trail that a regulator and an outside counterparty would both sign. If that record lives entirely inside one vendor's runtime, you have containment, and you should not mistake it for accountability. Deloitte's 2026 enterprise survey found only about 1 organization in 5 reports a mature model for governing autonomous agents. The regulator did not wait for the other four.

The agents learned to act this summer. Today the law asked who authorized it. The operators who will be interesting in this next phase are not the ones with the most agents in production. They are the ones who can answer that question about any one of them, on demand, across a boundary they do not own. That answer is not a feature of a runtime. It is the plane the runtime runs on, and the industry has been shipping the second while promising the first.