Snowflake focused on building sustainable AI advantage through data

“As AI models become increasingly commoditized, we believe the real differentiator will be the quality, connectedness, and trustworthiness of the data behind them,” says Satchit Joglekar, Managing Director, ASEAN at Snowflake.

Snowflake kicked off 2026 by announcing its intent to acquire Observe as the vendor looks to boost its capabilities in observability and agentic AI. Now only will this acquisition bring Snowflake to another level; it will also open up opportunities for the partner ecosystem.

In Southeast Asia, Snowflake continues to gain momentum in its expansion plans. In 2025, the AI data vendor announced growth plans in Malaysia and Thailand and is expected to continue to focus on enabling customers in their AI and data strategy in 2026.

CRN Asia caught up with Satchit Joglekar, Managing Director, ASEAN at Snowflake to get his views on how the vendor is looking to keep the momentum going this year following a successful 2025 in the region.

“In 2026, we're focused on helping enterprises build sustainable AI advantages through their data. As AI models become increasingly commoditized, we believe the real differentiator will be the quality, connectedness, and trustworthiness of the data behind them. This means providing robust data governance frameworks, continuous model monitoring capabilities, and the infrastructure enterprises need to deploy AI confidently at scale,” Joglekar said.

He added that Snowflake is also investing heavily in helping customers move beyond experimentation to production-grade deployments. This can be either through Snowflake’s engineering teams working side-by-side with them, or through enhanced observability and operational governance tools.

Opportunities in 2026

According to Joglekar, the biggest opportunity for Snowflake is all about helping Southeast Asian enterprises build AI on a strong data foundation before their competitors do.

“We’re expanding our regional presence to make that happen. With Snowflake instances going live in Malaysia and Thailand in 2026, we’re bringing local data residency capabilities and lower latency to more enterprises across ASEAN. This positions us to better serve organizations navigating cross-border data flows and regulatory compliance across the region,” he said.

Joglekar also mentioned that they are seeing particularly strong demand in financial services, where institutions are looking to move from proof-of-concept projects to AI that delivers tangible results. Specifically, Joglekar explained that banks are looking to deploy AI at scale while managing these complex operational risks. Beyond BFSI, the vendor is also seeing opportunities across retail and other sectors where hyper-personalization powered by quality data can drive significant competitive advantages.

“Ultimately, the market is demanding platforms that can support the entire AI lifecycle from data sourcing to model training, deployment, and ongoing monitoring—all while meeting the unique regulatory and operational requirements of this region,” he added.

While the opportunities are increasing, Joglekar also pointed out that the biggest hurdle to technology will be organizational readiness. He said many enterprises are still working through challenges with fragmented data systems that aren't ready for machine learning, despite 92% of early adopters seeing ROI from AI initiatives.

Some of the challenges that Snowflake is observing include:

• Data quality and governance: Without high-quality, trusted data, AI struggles to deliver meaningful value. Organizations often need to strengthen their data foundations before they can scale AI effectively.

• AI change management: One of the harder aspects of AI adoption isn't building the models—it's reshaping how people work with them. Companies are finding they need structured approaches to reskilling, building trust in AI systems, and redesigning organizational accountability.

• Operational AI risk management: As AI becomes embedded in mission-critical operations, organizations are finding they need to manage risks that go beyond bias and accuracy to include data residency, model stability, system resilience, and third-party oversight. Those without robust governance frameworks may find it challenging to deploy AI at scale.

The AI bubble

When asked about concerns about the AI bubble bursting in 2026, Joglekar mentioned that Snowflake does not see an AI "bubble burst". Instead, the vendor sees the market maturing from hype to value creation.

“AI is only as powerful as the data it is built on, and what we’re observing across our 7,300+ customer accounts using Snowflake’s AI capabilities weekly is a clear shift: enterprises are moving from experimentation to building trustworthy applications with incremental, practical implementations that deliver measurable business outcomes,” he said.

Joglekar explained that Snowflake’s technology platform helps customers unlock value from massive volumes of data at scale, reducing cost and delivering results.

“This quarter, we introduced 283 new product capabilities, and we’re seeing the fastest ramp in product adoption in our history, with 1,200 customers already harnessing next-generation, agentic AI at scale. This tells us that demand isn’t disappearing—it’s becoming more sophisticated and outcomes focused,” he added.

Interestingly, Joglekar also mentioned that Snowflake expects to see less of is AI spending without clear accountability. This means enterprises will increasingly require clear evidence of tangible business impact: improved customer retention, revenue growth, operational efficiency gains. At the same time, he believes boards are likely to treat AI investments with similar rigor as any other strategic technology deployment.

“In Southeast Asia, where digital transformation is accelerating rapidly, this shift may happen relatively quickly. Our mission is to help every enterprise in the region achieve its full potential with data and AI. We expect the gap between companies with strong data infrastructure and those without will widen quickly—and that's where the real competitive advantage will be won,” he concluded.