New research shows that APAC organizations are adopting AI at speed, but data reliability, governance and skills gaps are stopping many projects from moving beyond pilot stage.  

A new global study from Informatica from Salesforce reveals that organizations across Asia Pacific (APAC) are adopting AI faster than their data management, governance and skills foundations can support.

The study, which surveyed 600 global data leaders across the US, UK/EU and APAC, found that while 66% of APAC organizations have already adopted GenAI into their business practices, many are struggling to move initiatives from pilot to production due to persistent challenges with data reliability, workforce capability and inconsistent AI governance.

The study points to several key challenges facing APAC data leaders as they scale AI across their organizations:

  • Data reliability is holding back the move from pilot to production:
    89% of APAC organizations say data reliability is a barrier to moving GenAI initiatives from pilot to production. Yet employee confidence remains high, with 67% of APAC data leaders saying most or nearly all employees trust the data being used for AI. At the same time, 88% are concerned that new AI pilots are moving forward without addressing the data reliability issues identified in earlier initiatives.
  • Skills gaps threaten responsible AI use:
    APAC respondents highlight ongoing skills shortages, with 72% identifying the need for improved data literacy training and 72% citing a need for greater AI literacy across the workforce.
  • AI governance remains inconsistent across APAC: 
    Organisations are taking varied approaches to AI governance, with 44% extending existing data governance frameworks to cover AI, 35% investing in dedicated AI governance tools, and 22% reporting they have started governance efforts from scratch — highlighting uneven readiness as AI adoption accelerates across the region.

Many APAC data leaders (86%) are planning to increase their investment in data management throughout 2026 to address foundational gaps. Their key priorities include addressing evolving regulatory requirements (43%), strengthening data privacy and security (42%), and improving data and AI governance (39%).

“Across APAC, organizations are accelerating AI adoption at a time when regulatory expectations are also evolving rapidly,” said Richard Scott, Senior Vice President, Asia Pacific & Japan, Informatica.

“Our study shows many organizations are still working to move AI initiatives from pilot to production while simultaneously building the data reliability, governance and workforce capability that regulators increasingly require. As AI becomes more embedded in business decision-making, organizations that align their AI strategies with strong data foundation and clear accountability will be better positioned to adapt to changing regulatory requirements and sustain trust over the long term.”

What enterprise practitioners say

Andy Ta, Chief Data Officer & Director, Data Analytics & AI (DNA), Synapxe, concurred: “AI delivers tremendous benefits when supported by strong governance and effective data management. At Synapxe, we embed security-by-design and robust data practices in developing AI initiatives, to ensure responsible development that is aligned with Singapore’s established government frameworks and industry standards. Strong governance and close collaboration with healthcare and technology partners enable us to drive innovation and meaningful adoption across the sector.”

Amanda Fitzsimmons, Senior Director, Customer Data, RS Group, commented: “This report highlights the significant risks of accelerating AI adoption without strong data governance and literacy. At RS Group, we address this challenge by embedding governance and accountability into how we evaluate and scale AI initiatives. For all AI initiatives, we thoroughly evaluate the technological, security, legal, and strategic implications to maximize opportunities while minimizing risks.” 

She added: “This approach helps ensure innovation moves forward responsibly, with risks understood and value clearly defined from the outset. Through investments in robust data-driven solutions, comprehensive upskilling, and close collaboration with partners like Informatica, we believe we are taking the essential steps to foster trusted, responsible AI that delivers real, measurable value to our customers and employees.”