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APAC Firms Face Data Architecture Gap as AI Adoption Accelerates, Boomi Study Finds
A recent survey conducted by Boomi in partnership with analyst firm Omdia reveals that while the Asia‑Pacific (APAC) region is rapidly adopting artificial intelligence (AI), many organisations lack the data architecture needed to translate that adoption into measurable return on investment (ROI).
The study surveyed more than 1,100 senior technology and business decision‑makers in Australia, New Zealand, Singapore, Malaysia and the Philippines. It found that 74 % of respondents are already running active AI initiatives and 90 % expect AI‑enabled automation to reshape their business processes within two to three years. Despite this momentum, only 46 % of organisations use a platform‑led approach to integration, indicating a widening gap between AI ambition and execution.
A key barrier identified is the difficulty of measuring success. Nearly a quarter of respondents said they are unable to effectively assess the impact of their AI projects, a critical shortfall when organisations need to demonstrate ROI. Boomi’s chief technology officer for the APJ region, David Irecki, said the gap stems from weak data foundations. “Without unified integration, governance, and data quality frameworks, each new AI initiative adds complexity rather than value,” Irecki explained.
The survey also highlighted a strong focus on reducing tool and technology sprawl. 89 % of organisations are actively seeking to consolidate across data, process integration, application programming interface (API) management and automation. 92 % are already consolidating in these areas. Data integration, access and governance are top priorities for 94 % of respondents, and 93 % believe AI initiatives will increase focus on data quality and governance policies.
However, only about half of organisations have formal AI‑specific data governance policies in place. 81 % reported that unmanaged shadow integrations disrupt data quality and confidence. Omdia’s chief analyst on Enterprise IT Asia, Michael Barnes, noted that when teams build AI models on data they do not fully control or orchestrate across systems, they lack visibility into what’s feeding what. “That gap becomes a real business risk,” Barnes said.
Data sovereignty also emerged as a major consideration. 76 % of firms expressed concerns about data residency requirements, but only 24 % said those concerns are having a significant impact on their data integration or AI strategies. This suggests many organisations are still in the early stages of operational planning.
Boomi’s research points to a strong pace of AI adoption across APAC, led by Malaysia at 86 % and Singapore at 78 %. The company argues that organisations are moving beyond experimentation and into implementation, but must establish the right data foundations, integration capabilities and governance structures to avoid isolated AI activity that fails to deliver measurable business outcomes.
The study underscores that governance, data quality and clear performance measurement are essential for transforming AI deployments into sustainable business value. By building trusted, connected and governed data environments, CIOs and senior IT leaders can support enterprise‑scale AI that translates adoption into productivity gains, operational efficiency and competitive advantage.
The findings come at a time when many APAC firms are investing heavily in AI, yet the lack of robust data architecture remains a critical bottleneck. As the region continues to adopt AI, organisations that prioritise data governance and integration will be better positioned to realise ROI and avoid the pitfalls of fragmented, poorly governed data ecosystems.
The study surveyed more than 1,100 senior technology and business decision‑makers in Australia, New Zealand, Singapore, Malaysia and the Philippines. It found that 74 % of respondents are already running active AI initiatives and 90 % expect AI‑enabled automation to reshape their business processes within two to three years. Despite this momentum, only 46 % of organisations use a platform‑led approach to integration, indicating a widening gap between AI ambition and execution.
A key barrier identified is the difficulty of measuring success. Nearly a quarter of respondents said they are unable to effectively assess the impact of their AI projects, a critical shortfall when organisations need to demonstrate ROI. Boomi’s chief technology officer for the APJ region, David Irecki, said the gap stems from weak data foundations. “Without unified integration, governance, and data quality frameworks, each new AI initiative adds complexity rather than value,” Irecki explained.
The survey also highlighted a strong focus on reducing tool and technology sprawl. 89 % of organisations are actively seeking to consolidate across data, process integration, application programming interface (API) management and automation. 92 % are already consolidating in these areas. Data integration, access and governance are top priorities for 94 % of respondents, and 93 % believe AI initiatives will increase focus on data quality and governance policies.
However, only about half of organisations have formal AI‑specific data governance policies in place. 81 % reported that unmanaged shadow integrations disrupt data quality and confidence. Omdia’s chief analyst on Enterprise IT Asia, Michael Barnes, noted that when teams build AI models on data they do not fully control or orchestrate across systems, they lack visibility into what’s feeding what. “That gap becomes a real business risk,” Barnes said.
Data sovereignty also emerged as a major consideration. 76 % of firms expressed concerns about data residency requirements, but only 24 % said those concerns are having a significant impact on their data integration or AI strategies. This suggests many organisations are still in the early stages of operational planning.
Boomi’s research points to a strong pace of AI adoption across APAC, led by Malaysia at 86 % and Singapore at 78 %. The company argues that organisations are moving beyond experimentation and into implementation, but must establish the right data foundations, integration capabilities and governance structures to avoid isolated AI activity that fails to deliver measurable business outcomes.
The study underscores that governance, data quality and clear performance measurement are essential for transforming AI deployments into sustainable business value. By building trusted, connected and governed data environments, CIOs and senior IT leaders can support enterprise‑scale AI that translates adoption into productivity gains, operational efficiency and competitive advantage.
The findings come at a time when many APAC firms are investing heavily in AI, yet the lack of robust data architecture remains a critical bottleneck. As the region continues to adopt AI, organisations that prioritise data governance and integration will be better positioned to realise ROI and avoid the pitfalls of fragmented, poorly governed data ecosystems.
