TelecomTV Publishes First AI-Native Telco Index

TelecomTV published its first AI-Native Telco Index on 7 September, the day before its AI-Native Telco Forum opens in Düsseldorf. Ray Le Maistre's article describes a 276-page report assessing 56 operators against 4 dimensions, foundation readiness, strategic intent, execution evidence and transformation velocity, each made up of 5 indicators, using published evidence only, with a cut-off of 30 June 2026. The index assigns each operator 1 of 7 archetypes rather than a rank; the decision not to publish a league table was taken with the ANTA steering board, whose members come from Axiata, Deutsche Telekom, Orange, NTT Docomo and Rakuten Mobile. 9 operators are placed in the top archetype, AI Vanguard: AT&T, China Mobile, Deutsche Telekom, KDDI, NTT and NTT Docomo, Rakuten Mobile, SoftBank Corp, Telefónica and Verizon. 5 are Infrastructure Architects, 15 are Strategic Accelerators and 1 is at Transformation Pending. The stated rule is that "announce does not mean executed": a commitment is recorded as a commitment, and a deployment is recorded only where the operator has published something showing it is running. SK Telecom, which the article notes is often named the leading AI-native operator, is a Strategic Accelerator because many of its efforts were still at the planning stage at the end of June. A 12-page executive summary is free; the full index is available to ANTA partners and licence holders. This post works from TelecomTV's article; neither the summary nor the full report was read for it.

Most assessments of operator AI progress, including most vendor-sponsored surveys, score intent: budgets planned, priorities ranked, use cases identified. This index scores what has been published as running, and it records an announcement as an announcement. That is the distinction between field-validated and commercially validated that AI-RAN claims have needed for 2 years, applied here across the whole operator estate, and the SK Telecom result shows the rule working. An operator with a clear strategy, disclosed investment, revenue already generated and a large revenue target still lands below the top tier because its published evidence at the cut-off described plans rather than operations. Producing that result about the operator most often cited as the leader, in a report whose steering board includes 5 operators, is a sign the methodology was allowed to run.

No financial dimension yet

The 4 dimensions measure readiness, intent, execution and speed. None measures return. An operator reaches AI Vanguard by publishing the most evidence that AI systems are in production across its operations, and that is a real achievement, but it is the same class of evidence as the customer-experience award that TM Forum gave Google Fiber last week: proof that it works, not proof of what it is worth. The index is explicit that it measures transformation progress and not who is better, and that framing is useful, because it means nobody should read the Vanguard list as the operators making money from AI. I argued in July that most of what operators call AI monetization is cost avoidance, and that the discipline starts with refusing to aggregate cost saving, defended revenue and new revenue; an index that counts deployments without asking which of the 3 flows each one serves cannot make that separation either. The industry now has a reliable way to count deployments. It does not yet have a published operating cost per subscriber, per activation or per ticket, before and after, from any of the 9, and until one of them publishes that figure the index measures the input side of a business case whose output side remains an estimate.

Because the method admits only what an operator has published, an operator that publishes more scores higher, other things being equal. 4 of the 9 Vanguard operators are Japanese, 2 are American, 1 is Chinese and 2 are European, and 2 of the 9, NTT Docomo and Rakuten Mobile, sit on the steering board that shaped the method. The article says archetype assignment is an editorial judgement based on the evidence analysed, and there is no reason to doubt that. The point is narrower: operators with a corporate habit of publishing technical detail, and operators for whom the network is a marketing asset, will be over-represented at the top of any evidence-based index, and operators that run production AI quietly will be under-represented. The index cannot correct for that without abandoning its rule, and it should not abandon its rule. The caveat applies to every evidence-based index, this one included.

Everything the index can see is inside 1 operator's estate: its data foundations, its stated strategy, its deployments, its pace. That is the version of autonomy that ships, and it is where the evidence should be collected first. The next stage, in which an operator's network AI has to coordinate with an enterprise AI, a cloud provider's AI or another operator's AI, produces almost no published evidence yet, because the coordination layer that would make it work is the one I argued no runtime supplies and that NGMN has since itemised even for coordination inside a single operator. An index built on published deployments will show that stage as empty for some time, and the absence will be accurate. A future edition could usefully add an indicator for it: whether the operator has published any interface, ontology or audit model through which an external agent can act on its network, since the developer APIs alone do not answer that question.

What has not been published

The per-operator scores, the weighting of the 20 indicators, the definition of "running" used for execution evidence, and whether any indicator captures financial disclosure are all in the licensed report and not in the article. The 56-operator list is published; the archetype of each operator outside the 3 named tiers is not. 3 things to watch. First, whether the 2027 edition adds a return dimension, or an indicator for published cost or revenue attributable to AI, which would be the single most useful change to the method. Second, whether any of the 9 Vanguard operators publishes an operating cost figure for an automated domain against its pre-automation baseline in the next 12 months, since they are now on record as the operators with the most to show. Third, where SK Telecom lands next year: the article expects it to be among the strongest profiles, and if the planned efforts have become published deployments by then, the index will have shown it can measure movement and not only position.