Asia’s telcos battle data debt in AI race
Outdated systems, poor data quality, and talent gaps slow edge and AI transformation.
Asia’s telecom sector is accelerating its shift toward edge computing and private wireless to fuel the next wave of AI-driven growth, but industry leaders warn that legacy infrastructure and fragmented data are undermining progress and returns.
Kristian Steenstrup, Distinguished VP Analyst and Gartner Fellow, said the speed of ROI seen globally — where 87% of industrial firms report payoffs within a year — comes from the untapped potential of existing data. “There is already a pent up availability of information,” he said. “The data in industrial equipment was always there, but because there was excessive volume and information that was inaccessible, it was like looking in a needle of haystacks of ones and zeros.”
Edge and private wireless technologies, Steenstrup added, are unlocking that potential by streamlining how data is processed and transmitted. “The number one use case that has a positive ROI is aiding equipment availability and machine reliability,” he said. “Edge processing creates better data density” and “improved communications reduce the latency,” allowing faster, smarter decision-making.
For telecom players, the surge in AI and data demand is opening long-awaited monetisation opportunities. Duncan Eadie, Managing Director, Cloud First and Infrastructure Engineering (APAC) at Accenture, said, “It really is the telcos’ customers’ desire to embrace scaled AI and reinvent their businesses using generative artificial intelligence, traditional AI ML and agentic, which is driving the opportunity in the telco space.”
After years of struggling to monetise networks, Eadie noted that edge and private wireless now “give the telcos an opportunity to provide increased bandwidth” while using connectivity “to deliver business outcomes.”
However, the region’s progress is being slowed by persistent structural challenges. “Many organisations are still constrained by legacy network architectures and also legacy IT systems,” Eadie said. “The build up of inconsistent, low quality data…really limits AI deployment and the richness of the benefits that AI can bring.”
Eadie called this “data debt” — a form of digital backlog that stifles innovation. “Ultimately, mastering that data debt is really the key challenge,” he said, urging Asian telcos to embark on a “holistic enterprise reinvention” to compete effectively in the AI economy.
