APAC telcos battling data debt as AI gains lag

New research from Accenture suggests that “data debt",caused by fragmented, inconsistent and poorly governed data, is hampering decision-making and slowing progress on the adoption of artificial intelligence across the Asia-Pacific (APAC) telecommunications sector.

According to Cracking the Code on Data Debt, 71% of APAC telecom executives say limited visibility across networks and portfolios delays decisions. Two-thirds report that staff spend more time cleaning data (66%) than analysing it (34%). Only 2% of respondents have an integrated data strategy that enables seamless, cross-functional data sharing.

A related study, The Front Runner’s Guide to Scaling AI, indicates that only 21% of communications service providers (CSPs) in the region are realising measurable value from their AI investments. The report highlights that companies seeing the greatest returns are those making long-term, sector-specific investments across core processes in the telecom value chain, modernising their technology stacks, developing AI-ready data infrastructure, and reshaping workforce skills.

Across APAC, the five areas receiving the strongest strategic focus include:

• Self-healing automated networks and field-engineer technical assistants (Network & Service Assurance)

• Agent co-pilots (Customer Experience & Care)

• Sales co-pilots and AI-generated marketing content (Sales & Marketing)

Tore Berg, Managing Director and Lead for Accenture’s Communications, Media and Technology practice in APAC, said telcos recognise AI’s potential but only a minority are investing at the depth required. He continued, “A small group of AI leaders are making the deep investments and sustained effort needed to reinvent with AI, boosting productivity and unlocking new opportunities to fund and accelerate future expansion.”

Vivek Luthra, Senior Managing Director for Data & AI in APAC and Southeast Asia, stressed the need for organisational transformation, he added, “Scaling AI impact requires more than incremental improvements – it demands bold, strategic bets that focus on the core of a company’s value chain. Technology and talent are the two main areas that need investment… The industry needs professionals who can bridge telecommunications expertise with advanced AI capabilities.”

Tejas Rao, Managing Director and Global Network Practice Lead, emphasised the importance of “agentic AI” in advancing network autonomy. He noted,“Agentic AI can accelerate a telco’s journey to truly autonomous, zero-touch network operations… Intelligent systems that proactively manage, optimise and secure infrastructure will make operations more efficient and resilient.”

Research background

The Front Runner’s Guide to Scaling AI surveyed 2,000 C-suite and data-science executives from nearly 2,000 large companies, each with revenues above USD1 billion, across 15 countries and ten industries. The study assessed organisations against ten AI-related capabilities, including data readiness, talent readiness and responsible AI practices, and grouped them into four categories: Experimenting, Progressing, Fast-Followers and Front-Runners. Thirty-eight APAC CSPs were included.

Cracking the Code on Data Debt draws on responses from 256 senior telecom executives in 24 countries, including 66 from the APAC region, all from companies with revenues exceeding USD5 billion.