Home Frontier Tech AI & ML FOMO trumps actual results in fueling AI investment boom in APAC

FOMO trumps actual results in fueling AI investment boom in APAC

Enterprise AI spending is climbing rapidly, with boards racing to deploy the technology faster than they can measure whether it works. 

According to the latest IDC InfoBrief, commissioned by Expereo, around 70% of organizations are investing in AI, motivated by its potential or by the fear of falling behind the competition. But they lag in disciplined ROI evaluation, and one in five (20%) admit they are investing aggressively in AI with little evaluation, driven by the fear of being left behind.

In Asia Pacific (APAC), that pressure is even more pronounced as 37% of organizations admit investing aggressively with little evaluation – nearly double the global average, and well ahead of the US (10%) and Europe (13%). 

The pressure is most acute in Australia (45%) and Vietnam (44%), while in Singapore, more than one in three organizations admit the same.

The report is based on a survey of 800 technology leaders across APAC, Europe, and the United States.

Findings show that AI has become one of the most prioritized technology investments globally, with 51% of organizations planning to prioritize AI or machine learning investment over the next 12 months – rising to 61% across APAC. 

However, returns are failing to keep pace with the hype. Just 19% of global organizations surveyed say their AI implementations have exceeded expectations, and only 5% report they have significantly exceeded them1.

Across APAC, 40% say implementations have exceeded or significantly exceeded expectations – ahead of the global average but still leaving the majority falling short. 

Globally, the most-cited reasons for underperformance are inadequate or poor-quality training data (51%), higher-than-expected costs or ROI not achieved (47%), and AI not performing as well as expected (46%). 

For APAC specifically, the picture is broadly similar – though costs bite harder: 49% cite poor-quality training data, 54% cite cost overruns or ROI not achieved (rising to 80% in Malaysia), and 46% say AI has simply not performed as expected.

Where organizations have the right foundations in place, the results speak for themselves. Across APAC, 87% report productivity improvements in the business units most affected by AI, and 82% say quality of work has improved.

Globally, 26% of organizations whose AI implementations have failed to meet expectations cite inadequate network or connectivity performance as a contributing factor. 

Looking ahead, 54% of organizations say they need more flexible and scalable networks to thrive in an AI-driven environment, and 51% need greater resilience and reliability to maximize uptime. 

In APAC, the gap is acute as only 9% of organizations describe their network infrastructure as fully ready to support new AI, cloud, and digital initiatives, and 37% say it will need upgrading or replacing soon. 

The need is most acute in Thailand (74%) and Singapore (58%), both of which rank above the regional average on demand for flexible, scalable networks. In Indonesia, nearly half of all organizations (48%) say their infrastructure will need upgrading or replacing soon.

Ben Elms, CEO of Expereo, said that without resilient, scalable, cloud-optimized networks, even the most well-funded AI programs will struggle to deliver ROI. 

“Getting the network right is no longer an IT decision; it is one of the most important conversations happening in the boardroom today to help fulfill AI ambition,” said Elms.

APAC is also leading in adoption, with 35% of organizations reporting extensive AI use across the business, against a global average of 25%. Yet adoption alone is not enough without the right foundations beneath it.

Eric Wong, Expereo president in APAC, said the region is moving aggressively on AI adoption, but many organizations are discovering that scaling AI successfully requires more than just investment in applications and models. 

“Across the region, we are seeing enterprises reassess whether their infrastructure is truly ready to support AI at scale, particularly around performance, resilience, governance, and visibility,” said Wong. “Organizations that address those foundations early are generally seeing stronger outcomes and faster operational impact from their AI initiatives.”

Boardrooms are also waking up to the longer-term risks of unchecked AI investment. According to the survey, 54% of global tech leaders cite the creation of new security risks as a significant potential future threat for their organization’s use of AI, while 39% globally are concerned about losing track of AI-related costs and ROI once the technology is embedded across the business. 

In APAC, that concern is sharper still as 41% of technology leaders in the region are worried about losing oversight of AI-related costs and ROI as adoption deepens – a figure that rises to 54% in Malaysia. 

Digital sovereignty is also moving up the strategic agenda, with 38% of APAC organizations rating it a high or top priority as they look to retain control over data and navigate an increasingly complex regulatory landscape.

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