AI deployment has ‘stalled’ for most Asia companies: report

Source: Business Times
Article Date: 16 Apr 2026
Author: Koh Kim Xuan

Only 1% of firms have fully embedded artificial intelligence in their businesses.

Organisations in Asia have hit roadblocks in transforming their operations and generating new revenue streams through artificial intelligence, Singapore Technologies Telemedia Global Data Centres (STT GDC) has found.

Although about 90 per cent of organisations in the region have started to adopt AI, 71 per cent struggle to scale AI pilots into production, STT GDC said in its Mind the Gap: Bridging the AI Infrastructure Readiness Divide report on Wednesday (Apr 15).

A total of 644 companies in various sectors, including banking and financial services, manufacturing, and energy and utilities, were surveyed.

Enterprises with 1,000 or more employees made up 43 per cent of the respondent companies. Companies with 250 to 999 employees made up 29 per cent, and 28 per cent were digital natives.

STT GDC said that across Asia, AI infrastructure readiness was “fundamentally stalled”. Just 16 per cent of firms have an “operational AI strategy with robust infrastructure and governance”, it noted.

Only 1 per cent of organisations were found to have fully embedded AI in their businesses.

The survey showed that 56 per cent of companies were unable to measure AI production value and faced budget constraints. They also lacked the infrastructure to scale AI pilots into production.

“This deployment gap prevents clear ROI (return on investment) from emerging, perpetuating the cycle,” said STT GDC. “Breaking this cycle will be crucial to unlocking AI’s measurable value.”

Mature and emerging markets in Asia

AI readiness in Asia was found to be divided into two camps.

The first was termed mature markets, referring to those leading the AI adoption race. The second group, emerging markets, have yet to tap into their full potential in deploying AI.

Both mature and emerging markets face similar challenges of infrastructure limitations and talent shortages. STT GDC said that these hurdles can be overcome by partnering “specialised providers”.

Singapore, Japan and South Korea are mature markets with strong operational and regulatory readiness.

Singapore leads the region with its “strong public-private partnerships”, supported by “governance and talent pipelines” such as its National AI Strategy 2.0 launched in 2023.

However, the Republic faces land and energy-capacity constraints to support growth in high-density AI training. This has fuelled Singapore’s expansion plans beyond traditional data centre building sites.

Emerging markets such as Malaysia, Indonesia, the Philippines and Vietnam have demonstrated their potential in furthering AI deployment, which requires “growing technical expertise” and “refined governance”.

This group possesses land, power and cost advantages that address mature market capacity constraints.

They also stand to benefit from accessing infrastructure and talent from AI leaders in the region.

Malaysia’s land, power and capacity complement Singapore’s AI expansion within Johor. Indonesia’s vast renewable-energy potential and strategic zones such as Nongsa Digital Park in Batam also help alleviate the region’s infrastructure capacity crunch.

“This complementary dynamic will spawn a hyper-connected digital infrastructure ecosystem spanning Asia, positioning the region as a critical node in the global AI supply chain,” STT GDC added.

Infrastructural gaps

The survey showed that 72 per cent of organisations in Asia expect moderate to exponential growth of AI workloads over the next three years.

While this accelerated pace “demands appropriate AI-ready infrastructure”, most organisations do not have it, STT GDC cautioned, adding that traditional data centres in Asia cannot provide it.

Companies have therefore been looking to purchase AI readiness through hardware investment alone, with 64 per cent prioritising graphics processing unit acquisitions.

Infrastructure-related gaps and critical operational expertise are also overlooked.

Almost 50 per cent of companies reported insufficient compute capacity for AI workloads, with only 7 per cent having “adequate headroom for complex AI applications and adoption growth”, the survey showed.

Companies also face networking limitations, with 82 per cent having network bottlenecks, latency issues or insufficient optimisation for high-demand AI workloads.

Additionally, 83 per cent of firms in Asia reported that less than half of their information technology locations are AI-ready, and are therefore unable to facilitate better user experiences and meet data residency and sovereignty requirements.