{"slug": "boomi-finds-apac-data-gaps-threaten-ai-roi", "title": "Boomi Finds APAC Data Gaps Threaten AI ROI", "summary": "Boomi released research commissioned to Omdia showing that 74% of Asia Pacific organizations have active AI initiatives, but only 46% use a platform-led integration approach and nearly a quarter cannot measure AI success, threatening AI ROI. The survey of over 1,100 senior decision-makers across five APAC countries found 89% face tool sprawl and 92% are consolidating integration, API management, and automation, while only 50% have formal AI-specific data governance policies.", "body_md": "# Boomi Finds APAC Data Gaps Threaten AI ROI\n\nBoomi published research commissioned to **Omdia** showing that Asia Pacific organisations risk failing to realise AI return on investment without stronger data foundations. The **Omdia** survey of more than **1,100** senior technology and business decision-makers across Australia, New Zealand, Singapore, Malaysia, and the Philippines found **74%** are already running active AI initiatives and about **nine in 10** expect AI-enabled automation to reshape processes within two to three years (Omdia, reported via Boomi press release). The survey reports only **46%** have a platform-led approach to integration and nearly a quarter cannot effectively measure AI success. Respondents also flagged tool sprawl (**89%**) and consolidation across integration, API management, and automation (** 92%**). The release includes quotes from David Irecki, CTO APJ at Boomi, and Michael Barnes, Chief Analyst, Enterprise IT Asia at Omdia, on governance and data-quality risks.\n\n### What happened\n\n**Boomi** announced new research, commissioned to **Omdia**, that surveyed more than **1,100** senior technology and business decision-makers across Australia, New Zealand, Singapore, Malaysia, and the Philippines, reporting that **74%** of organisations are running active AI initiatives (Boomi press release / Business Wire). The survey found **only 46%** currently use a platform-led approach to integration and that nearly a quarter of respondents said they are unable to effectively measure the success of AI initiatives (Omdia via Boomi). The study also reports **89%** are seeking to reduce tool and technology sprawl and **92%** are consolidating across data, process integration, API management, and automation (Boomi press release).\n\n### Technical details\n\n**Omdia** respondents flagged data integration, access, and governance as priorities, with **94%** viewing those areas as key and **93%** saying AI initiatives will increase focus on data quality and governance policies, yet only **50%** reported formal AI-specific data governance policies in place (Omdia via Boomi). The survey further reports **81%** of organisations see unmanaged shadow integrations as disrupting data quality and confidence, and **76%** view data residency as a concern even though **24%** say residency materially affects strategy (Melbourne-Insider summary of the Omdia data).\n\n### Reported quotes\n\n\"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, Chief Technology Officer, APJ, **Boomi** (press release). Michael Barnes, Chief Analyst, Enterprise IT Asia at **Omdia**, is quoted warning about model development on poorly controlled data, saying teams lack visibility into data lineage and its business impact (Omdia quote in press release).\n\n### Industry context\n\nEditorial analysis: Companies and practitioners building production AI pipelines commonly encounter friction when integration is fragmented, governance is immature, and shadow IT proliferates. In comparable enterprise surveys, those gaps correlate with longer model deployment cycles, higher costs to remediate data issues, and weaker ability to measure downstream ROI.\n\n### Context and significance\n\nEditorial analysis: The **Omdia** findings, as distributed by **Boomi**, underscore a recurring pattern where rapid AI adoption outpaces investment in data engineering and governance. For organisations across APAC, the combination of high AI project incidence (**74%**) with low formal governance coverage (** 50%**) raises the risk that many projects will deliver limited, hard-to-measure business value despite heavy tooling and automation efforts.\n\n### What to watch\n\nEditorial analysis: Observers and practitioners should track three indicators: uptake of platform-led integration and API management solutions across APAC, the share of organisations publishing AI-specific data governance policies, and metrics teams publish to demonstrate measurable AI outcomes. Public vendor procurement announcements and follow-up industry surveys will show whether consolidation efforts reported by **89%-92%** of respondents translate into durable architecture and measurement improvements.\n\n### Practical takeaway for practitioners\n\nEditorial analysis: Teams evaluating or running AI initiatives should prioritise observable metrics for data quality, lineage, and integration health. Industry experience shows that establishing those telemetry and governance primitives earlier reduces rework during model production and simplifies ROI measurement across stakeholders.\n\n## Scoring Rationale\n\nThe story highlights widely reported data governance and integration gaps that matter to practitioners building production AI, but it is a vendor-commissioned industry survey rather than new technology or regulation. Its practical relevance is moderate for teams prioritising data architecture.\n\nPractice with real Ad Tech data\n\n90 SQL & Python problems · 15 industry datasets\n\n[Active Search Campaigns by BudgetEasy](/problems/sql/active-search-campaigns-by-budget)\n\n[High CPC Clicks & Poor Landing PagesMedium](/problems/sql/high-cpc-clicks-poor-landing-page)\n\n[Campaign ROAS by Attribution ModelHard](/problems/sql/campaign-roas-by-attribution-model)\n\n250 free problems · No credit card\n\n[See all Ad Tech problems](/problems/datasets/adtech)", "url": "https://wpnews.pro/news/boomi-finds-apac-data-gaps-threaten-ai-roi", "canonical_source": "https://letsdatascience.com/news/boomi-finds-apac-data-gaps-threaten-ai-roi-60486399", "published_at": "2026-06-16 07:19:25.560452+00:00", "updated_at": "2026-06-16 07:19:27.834169+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-policy", "ai-infrastructure", "ai-research", "ai-ethics"], "entities": ["Boomi", "Omdia", "David Irecki", "Michael Barnes", "APAC", "Australia", "New Zealand", "Singapore"], "alternates": {"html": "https://wpnews.pro/news/boomi-finds-apac-data-gaps-threaten-ai-roi", "markdown": "https://wpnews.pro/news/boomi-finds-apac-data-gaps-threaten-ai-roi.md", "text": "https://wpnews.pro/news/boomi-finds-apac-data-gaps-threaten-ai-roi.txt", "jsonld": "https://wpnews.pro/news/boomi-finds-apac-data-gaps-threaten-ai-roi.jsonld"}}