Rapid AI adoption across Australia and New Zealand is exposing a growing challenge for organisations: the gap between AI ambition and data readiness.
New research commissioned by Boomi and conducted by Omdia shows that while many organisations are actively deploying AI, they often lack the underlying data architecture needed to generate measurable return on investment.
AI adoption is rapid, but ROI remains elusive
The survey of more than 1,100 senior technology and business decision-makers across the Asia-Pacific region, including Australia and New Zealand, found that 72% of Australian organisations and 65% of New Zealand organisations are already running active AI initiatives.
Despite this momentum, many organisations are struggling to translate adoption into measurable outcomes. More than one-quarter of respondents in Australia (28%) and one-third in New Zealand (34%) said they are unable to effectively measure the success of their AI initiatives.
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The growing importance of data governance and integration
Although 39% of Australian organisations and 43% of New Zealand organisations do not yet have a dedicated AI budget, most are planning to increase investment over the next 18–24 months.
Investment priorities are increasingly concentrated in foundational capabilities:
- 92% in Australia and 93% in New Zealand for data integration, preparation, and orchestration
- 90% in Australia and 88% in New Zealand for AI governance, risk, and compliance
- 94% in Australia and 91% in New Zealand for data quality, security, and privacy
However, only 46% of organisations in Australia and 39% in New Zealand currently have a platform-led approach to integration, highlighting a gap between ambition and execution.
Why shadow systems and data fragmentation are a risk
Nearly 85% of Australian organisations and 84% of New Zealand organisations are actively seeking to reduce tool and technology sprawl. In addition, 90% in Australia and 84% in New Zealand are already consolidating across integration, API management, and automation tools.
Despite this, data fragmentation remains a challenge. Around 76% of organisations in Australia and 72% in New Zealand report that unmanaged shadow integrations are affecting data quality and trust.
Building the foundations for scalable AI
David Irecki, Chief Technology Officer for APJ at Boomi, said organisations are still in the early stages of shifting from experimentation to transformation.
“APAC organisations are moving quickly on AI, but the research suggests that many still treat AI as an extension of broader technology spending rather than a strategic business transformation initiative,” Irecki said.
“The gap between adoption and ROI 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.”
Governance as a strategic priority
Data governance is now emerging as a central priority for organisations across the region. Around 94% of Australian organisations and 89% of New Zealand organisations now view data integration, access, and governance as critical.
However, less than half currently have formal AI-specific data governance policies in place.
Michael Barnes, Chief Analyst for Enterprise IT Asia at Omdia, said this gap presents a growing business risk.
“Around nine out of 10 organisations we’ve surveyed cite governance as a priority, but less than half have formal policies in place,” Barnes said.
“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.”
From adoption to business value
Data sovereignty is also emerging as a consideration, particularly in Australia, where 76% of organisations expressed concerns about data residency requirements, compared with 59% in New Zealand.
However, only a small proportion report that these concerns are significantly affecting current AI or integration strategies, suggesting many organisations are still in early stages of operational planning.
Ultimately, the research highlights a clear shift underway: organisations are moving beyond AI experimentation and into implementation. But without stronger data governance, integration, and measurement frameworks, many risk failing to convert adoption into sustainable business value.
As organisations scale AI initiatives, data quality and governance will increasingly determine whether AI delivers productivity gains and competitive advantage—or simply adds complexity.
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