Despite the Asia-Pacific (APAC) region’s rapid artificial intelligence (AI) adoption, a significant number of organisations lack the data architecture needed to achieve measurable return on investment (ROI), according to Boomi.
Boomi commissioned Omdia for a survey of more than 1,100 senior technology and business decision-makers across Australia, New Zealand, Singapore, Malaysia, and the Philippines.
The study found that 74% are already running active AI initiatives. Nine in 10 believe AI-enabled automation will significantly reshape their business processes within two to three years.
Even with the adoption momentum, only 46% currently have a platform-led approach to integration, highlighting a widening gap between AI ambition and execution.
Meanwhile, nearly a quarter said they are unable to effectively measure the success of AI initiatives, a critical gap when trying to assess ROI.
“APAC organisations are moving quickly on AI, but the research suggests that many organisations still appear to treat AI as an extension of broader technology spending rather than a strategic business transformation initiative,” said David Irecki, Boomi’s CTO in the APJ region.
“The gap between adoption and ROI realisation stems from one fundamental issue: weak data foundations. Without unified integration, governance, and data quality frameworks, each new AI initiative adds complexity rather than value,” said Irecki.
The research found that 89% are actively seeking to reduce tool and technology sprawl, and 92% are already consolidating across data, process integration, application programming interface (API) management, and automation.
Meanwhile, 94% of APAC organisations view data integration, access, and governance as a key priority, while 93% believe AI initiatives will increase focus on data quality and governance policies.
Still, only half of respondents have formal AI-specific data governance policies in place, and 81% said unmanaged shadow integrations are disrupting data quality and confidence.
“Nine out of 10 organisations we’ve surveyed cite governance as a priority, but only half have formal policies in place.” said Michael Barnes, Omdia’s chief analyst on Enterprise IT Asia.
“When teams are building AI models on data they don’t fully control or orchestrate across systems, they lack visibility into what’s feeding what. That gap becomes a real business risk,” said Barnes.
Data sovereignty is emerging as a major consideration, with 76% of firms expressing concerns about data residency requirements.
However, only 24% said those concerns are having significant impact on their data integration or AI strategies, suggesting many organisations are still in the early stages of operational planning.
“Scaling AI successfully depends on trusted, connected, and governed data. CIOs and senior IT leaders are increasingly focused on simplifying fragmented environments, improving data quality and building the operational foundations required to support enterprise-scale AI,” added Irecki.
He said the strong pace of AI adoption across APAC — led by Malaysia at 86% and Singapore at 78% — demonstrates that organisations are moving beyond experimentation and into implementation, but it’s time for organisations to put in place the right data foundations, integration capabilities, and governance structures.
“Without this shift, organisations risk creating isolated AI activity without delivering measurable business outcomes. Governance, data quality, and clear performance measurement are what transform AI deployments into sustainable business value, enabling organisations to translate adoption into productivity gains, operational efficiency, and competitive advantage,” said Irecki.
