True 5G network adds AI twin to plan Andaman capacity

True 5G network planning is getting an artificial intelligence upgrade: True Corporation has deployed AI-powered "network twin" technology to forecast demand, plan capacity and spot problems before customers notice them, including at busy Andaman coast destinations such as Krabi and the Phi Phi Islands, the Bangkok Post reported on Monday.

A network twin is a virtual copy of the operator's physical telecom infrastructure. Engineers can use it to simulate different scenarios, test the impact of proposed changes and find ways to improve performance before touching the real network.

How the True 5G network twin works

Instead of making changes on live equipment and waiting to see the results, True's engineers can model them first. The company said this helps with network planning, capacity optimisation and early detection of faults that could affect service.

The project is part of True's longer-term plan to build an "autonomous network" that relies more on AI and data analytics to run efficiently and deliver more reliable connections. It also supports the company's True5GX service, which aims to raise speed, capacity and reliability as data use climbs.

"Customers are consuming significantly more data, while different locations have different connectivity needs," said Khurrum Ashfaque, True's chief network officer. "True is focused on enhancing network speed, capacity, reliability and management by combining advanced 5G technologies with data analytics and AI to deliver better connectivity experiences across Thailand."

Data use keeps climbing

True's own figures show why capacity planning matters:

• 48.8 million mobile subscriptions as of the third quarter of 2026.
• 20.5 million of those are 5G subscriptions.
• 38GB average mobile data use per subscriber per month in the first half of 2026.
• 35% higher data use than before True merged with Total Access Communication (dtac) in early 2023.

Ashfaque said the increase shows growing demand for more capacity, faster data and more dependable connections.

Tourist seasons on the Andaman coast

True plans to combine the network twin with its "nano cluster" strategy, which manages performance at a very local level based on how customers actually use the network in each area.

Tourist areas are a clear example. In Krabi and other popular destinations in southern Thailand, mobile traffic can swing sharply with the travel season and visitor numbers. The network twin lets engineers model those swings and decide where extra capacity, better coverage or upgrades should come first.

The company said the strategy also supports its push to extend coverage beyond big cities to islands and sea routes, particularly in tourist areas along the Andaman coast. At Maya Bay on the Phi Phi Islands, True has launched 5G service using microwave backhaul, a wireless link that carries traffic back to the core network where laying cable is impractical.

Competition at sea and on the islands

Coverage for boats and islands has become a selling point for Thai operators. Rival AIS recently said its 5G sea coverage now reaches about 60km on the Chumphon to Koh Tao ferry route. For Phuket residents and visitors who spend time on boats to Phi Phi, Krabi or Phang Nga, better signal at sea means more reliable maps, messaging and safety calls.

The upgrade also comes as Thailand's telecom and digital rules are in the spotlight. The regulator recently rejected a US push for full foreign ownership of Thai network operators, while the government is preparing new tiered rules for data centres, which carry much of the traffic flowing over mobile networks.

True did not give a timetable for wider rollout of the network twin or say how much it is investing. As high season begins, visitors to the Andaman coast will be the first real test of whether the AI planning keeps pace with demand.

The details are from the Bangkok Post report on True's 5G development, published on 9 November.

Photo: Maya Bay on Koh Phi Phi, where the True 5G network now reaches visitors via microwave backhaul (Diego Delso via Wikimedia Commons, CC BY-SA 3.0).