On the operational side, True is deploying AI to predict network issues, automate processes, and improve service performance
In sum – what to know:
AI beyond efficiency – True is embedding AI into enterprise services and customer platforms, aiming to generate new revenue streams rather than relying solely on cost savings.
Telcos as enablers – Nationwide infrastructure, data access, and regulatory ties position operators as key players in scaling AI in emerging markets.
Monetization focus – Long-term upside is tied to enterprise AI adoption and customer insight monetization, not standalone AI tools.
Thai telco True Corporation is positioning artificial intelligence (AI) as a core layer of national infrastructure, outlining plans to scale AI across Thailand’s economy while embedding governance and operational use cases into its telecom business.
The strategy, presented during the “AI Revolution SHIFT 2026” event in Bangkok, frames AI not as a standalone technology push but as a structural shift in how telecom operators generate value. True said it is pursuing what it calls an “AI-first telco-tech” model, combining network intelligence, enterprise services, and governance frameworks to support broader economic digitization.
At the center of this approach is a dual focus: using AI to improve internal operations and leveraging it to create new revenue streams. On the operational side, the Asian carrier is deploying AI to predict network issues, automate processes, and improve service performance. Its “Genie” system, for example, enables autonomous network operations, including traffic rerouting and self-healing capabilities, reducing resolution times from hours to minutes.
On the commercial side, True is developing AI-driven services aimed at enterprises and consumers. Its “MARI” virtual agent uses real-time behavioral data to personalize offers and customer interactions, with the goal of increasing engagement while lowering service costs. The broader ambition is to move beyond connectivity and embed AI into enterprise workflows and customer-facing services.
This shift reflects a wider trend among telecom operators seeking to monetize AI not just through efficiency gains, but through new digital services. According to Lian Jye Su, chief analyst at Omdia, the sustainability of this model depends on how deeply AI is integrated into enterprise offerings.
“As True bundles its AI solutions within a comprehensive enterprise stack, it is a sustainable business service. Thai enterprises need local support in AI, and the enterprise AI solution offering is becoming a standard practice among Thai telcos, with AIS being a prominent leader in this space. The biggest revenue upside will come from the monetization of customer insights while supporting Thai SMEs to expand into global markets,” the analyst told RCR Wireless News.
At the same time, True is emphasizing governance as a foundational element of its AI strategy. The company has established an AI Council to oversee risk, compliance, and lifecycle management, alongside a Responsible AI policy focused on privacy, transparency, and accountability. This reflects growing regulatory and societal scrutiny around AI deployment, particularly as it scales across critical sectors.
True’s positioning also highlights the role telecom operators can play in national AI ecosystems, particularly in emerging markets. With existing infrastructure, customer data, and regulatory relationships, telcos may be better placed than new entrants to deploy AI at scale.
“In emerging markets, telcos still have strong advantages, especially in the provision of nationwide AI infrastructure, localized customer data, regulatory trusts, and existing government relationship. It won’t turn True into an competitor against top AI startups, but it positions them as an national AI enabler through the offering of localized AI services,” Su said.
However, this advantage does not eliminate competition from hyperscalers or global AI platforms. Instead, it suggests a more complementary role, where telcos act as local enablers of AI adoption, particularly in regulated or sovereignty-sensitive environments.
