San Francisco: Artificial intelligence (AI) adoption by enterprises in the Asia Pacific, including ASEAN, is currently widespread and gaining significant traction. Snowflake Chief Executive Officer (CEO) Sridhar Ramaswamy stated this aligns with enterprises’ aspirations to become more streamlined, leveraging technological advancements to enhance operational systems. “Yes, I think AI adoption absolutely is widespread because every company wants to be efficient. When it comes to Asia-Pacific and Japan (APJ) investments, we have a big presence in countries like Japan, Australia, and India, and we are definitely investing more in areas like Indonesia, Malaysia, and Vietnam. We have an office in Singapore with a great team and are keen to do more business there (ASEAN),” he told reporters on the sidelines of the Snowflake Summit 2025 held at Moscone Centre.
According to BERNAMA News Agency, despite North America being the world’s leader in technology adoption, the Asia-Pacific (APAC) region is narrowing the gap, particularly in generative AI (GenAI). Research from the Boston Consulting Group indicated that the perceived value of generative technologies is higher in APAC than in Europe and just a percentage point behind North America. In both North America and APAC, 16 percent of organizations are finding proven value with AI, but APAC is investing more heavily overall.
This trend is timely, as ASEAN countries are embracing AI, which could potentially increase the ASEAN economy by 10 percent to 18 percent, or close to US$1 trillion by 2030. Snowflake, a global cloud data company based in Singapore, has joined other international companies expressing interest in the region. On Monday, Snowflake, with a net worth of US$70.12 billion as of June 2, 2025, announced its intention to acquire Crunchy Data, a startup offering cloud-based database software.
Apart from this acquisition, Snowflake also introduced its new agentic AI innovation, Snowflake Intelligence, which provides business users and data professionals with a unified conversational experience. Powered by intelligent data agents, it allows users to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Akin to ‘ChatGPT’, Snowflake Intelligence offers more customized solutions according to customers’ needs, making AI and machine learning workflows easily connected and trusted for both technical and non-technical users.
Additionally, the company unveiled Data Science Agent, an agentic companion designed to boost data scientists’ productivity by automating routine machine learning model development tasks. This enables users to simplify their AI and ML workflows, democratize access to data across businesses, and eliminate the technical overhead that slows down business decision-making, all through natural language interactions within Snowflake.