Asia Outpacing the World in AI Adoption

Asia is outpacing the world in AI adoption, with China and Singapore topping the list of countries where businesses consider AI critical to their organizations’ operations. However, poor data quality and security risks could stall progress, says a new report by Hitachi Vantara.

The “How AI is Shifting Data’s Foundation” report interviewed 1,200 IT decision-makers across 15 countries. It found that organizations in the region are still struggling with fundamental data challenges despite moving beyond initial AI pilots.

Messy, unrefined data

While organizations in the region want to integrate AI more deeply, critical metrics remain underwhelming. On average, Asian enterprises estimate that their AI models produce accurate outputs just 32% of the time, and data is available where and when it’s needed only 34% of the time.

Even more concerning is the quality of data itself, with a mere 30% deemed structured, indicating that most information feeding into AI systems is messy and unrefined. So although numerous organizations across the region emphasize AI's strategic importance, these ambitious goals may falter due to inadequate foundational data infrastructure.

The data indicates that many Asian companies haven't yet reached the stage of benefiting from well-developed AI systems, but rather are struggling with fundamental deployment challenges. Poor data standards and accessibility appear to be holding back AI projects from delivering the transformative results executives are hoping for.

Thriving with AI

Achieving sustained AI advantage in Asia calls for laying the right data-centric groundwork for AI to thrive. Among the region’s most successful AI adopters, 40% credit the use of high-quality data for their achievements, above the 38% global average.

For instance, converting unstructured data into refined, AI-ready information can support more accurate models, while robust security measures and governance frameworks help meet regulatory demands and align with global best practices.

Ultimately, successful AI transformation depends on making informed, strategic decisions about data infrastructure, says the report. A robust foundation is critical for scaling effectively to get the most out of AI without sacrificing data quality, security, or sustainability management.

“Asia’s rapid AI adoption is not a promise; it’s a reality,” said Adrian Johnson, the senior vice president and general manager for The Americas and Asia Pacific at Hitachi Vantara. “The region’s markets show that when organizations pair advanced adoption with data best practices, AI can transcend pilot projects to become truly transformative. However, leaders must recognize that data availability, security, quality, and governance are not optional. Without them, AI’s potential will remain under-realized.”

Johnson noted that enterprises in Asia can fully capitalize on their early lead by aligning AI expansion with data integrity and strategic resource investments. With a focus on foundational data elements, along with strategic partnerships and effective governance, AI initiatives can deliver “truly transformative and enduring value,” he says.

The Hitachi Vantara State of Data Infrastructure Report can be downloaded here (free registration).

Image credit: Hitachi Vantara