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 IDC InfoBrief, based on a survey of 800 technology leaders across APAC, Europe, and the US, found 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.
Ben Elms, CEO, Expereo, says:
“Every enterprise we speak to is investing in AI, yet the data shows a clear gap opening up between AI ambition and AI outcomes. More often than not, that gap comes down to the network underneath. AI only delivers on its promise when the infrastructure carrying it is built to support it.
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.”
APAC is also leading on adoption, with 35% of organizations reporting extensive AI use across the business, against a global average of 25%3. Yet adoption alone is not enough without the right foundations beneath it.
Eric Wong, President, APAC, Expereo, says:
“Asia Pacific is moving aggressively on AI adoption, but many organizations are discovering that scaling AI successfully requires more than just investment in applications and models. The underlying network, cloud connectivity, and operational readiness matter just as much. 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. 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 business4. 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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