Observed Signal · Jun 16, 2026 · Market Research · Source: https://martechseries.com/feed/ · Impact: 3/5 · Sentiment: Neutral
Boomi Study: APAC Risks AI ROI Without Data Foundations
Boomi commissioned Omdia to survey more than 1,100 senior technology and business decision-makers across Australia, New Zealand, Singapore, Malaysia and the Philippines, finding rapid AI adoption in APAC but widespread gaps in data architecture, integration and governance. Key findings include that 74% of respondents are running active AI initiatives, only 46% have a platform-led integration approach, and roughly half have formal AI-specific data governance policies. The research highlights widespread efforts to reduce tool sprawl and consolidate data and integration technologies, while concerns about data residency and unmanaged "shadow integrations" persist. Boomi and Omdia executives warn that weak data foundations risk turning AI adoption into isolated projects without measurable ROI, and urge organisations to prioritise unified integration, data quality and governance to realise enterprise-scale AI benefits.
Survey from a MarTech data vendor highlighting widespread gaps in data integration and governance across APAC is moderately important for marketers and AdTech/MarTech teams because it signals barriers to realizing AI-driven measurement and automation benefits.
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Key Takeaways & Evidence Grounding
- Boomi commissioned research conducted by Omdia surveying more than 1,100 senior technology and business decision-makers in APAC (Australia, New Zealand, Singapore, Malaysia, Philippines).
- 74% of respondents report they are already running active AI initiatives; 90%+ expect AI-enabled automation to reshape business processes within two to three years.
- Only 46% of organisations currently use a platform-led approach to integration; nearly 25% said they cannot effectively measure AI initiative success.
- 89% are actively seeking to reduce tool and technology sprawl and 92% are consolidating across data, process integration, API management and automation.
- 94% view data integration, access, and governance as a key priority, but only ~50% have formal AI-specific data governance policies; 81% cite unmanaged shadow integrations disrupting data quality.
Connected Companies & Entities
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Data Management Emerges as Top AI Challenge for Enterprises
A Semarchy survey of 1,000 global C-level executives across the UK, US and France finds data management (51%) is now the single biggest AI challenge, overtaking cost and talent. The report says 51% of leaders are implementing AI initiatives without Master Data Management (MDM) foundations and 38% are not enforcing data quality standards. Consequences already reported include AI project delays (22%), operational inefficiencies (21%) and compliance issues (19%). While ethics/regulation prioritization rose from 50% in 2025 to 77% this year, optimism about meeting AI goals doubled to 92%. Nearly two-thirds (65%) are pursuing agentic capabilities and 48% are investing in DataOps. Semarchy CTO Craig Gravina warned that sidelining data leadership (only 7% of CDOs and 18% of CIOs seen as chief AI strategists) risks accumulating AI technical debt.
81% of Enterprises Stall AI Over Data Governance Gaps
Transcend published The 2026 State of Customer Data in the World of AI, a report based on a survey of 228 senior IT and business leaders at enterprises with 5,000+ employees. The research finds 81% of enterprises experienced at least one AI initiative delayed, scaled back, or abandoned in the prior 12 months, and identifies permission and governance gaps as the primary cause. Key issues include high rates of permission errors during the AI lifecycle (93%), engineering time consumed by remediation rather than feature work (only 23% of AI engineering hours go to features), and limited enterprise readiness for AI governance (15% have all four foundational capabilities). The report introduces an “Encoded AI Governance” framework, outlines five best practices and a 90-day phased action plan, and includes case studies where Transcend helped large enterprises unblock revenue.
Enterprises Deploy AI Faster Than Governance, Smarsh Study
Smarsh released the 2026 Enterprise AI Trends Study (conducted by FTI Consulting) finding that 55% of enterprises are actively deploying AI while only 26% say governance is keeping pace. The report highlights limited visibility into unauthorized or "shadow AI" (only 30% report comprehensive detection and management capabilities) and frames communications data as a critical foundation for responsible AI, investigations, and business intelligence. The study identifies five trends — governance lagging adoption, communications data becoming strategic, interconnected systemic risk across AI agents/APIs/third-party apps, a shift toward proactive security and resiliency, and compliance evolving into a strategic function. It also reports enterprise investment priorities: 62% in AI/ML capabilities, 53% in data quality/enrichment, and 51% modernizing archives. Smarsh and FTI executives emphasize that scaling AI safely requires stronger data governance across connected ecosystems.
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