“Agentic AI reliability and data strategy will determine corporate competitiveness.

Snowflake, an AI data cloud company, recently released its 'AI + Data Forecast 2026 Report', predicting that the key topics in enterprise AI in 2026 will be agentic AI and data strategies.

The analysis suggests that ensuring reliability, data governance, and operational infrastructure innovation are essential for companies to build an AI ecosystem that extends beyond generative AI to actual business execution.

Every year, Snowflake publishes AI and data trends based on insights from CEO Sridhar Ramaswamy and key leaders.

In this year's report, the company emphasized that "the era centered on large-scale language models (LLMs) is over, and agentic AI with sophisticated reasoning and execution capabilities will become the standard for corporate competitiveness."

This represents a shift beyond simple chatbots to AI agents that perform actual work and are embedded throughout corporate systems.

“The pace of AI innovation is accelerating, but the performance gap between companies will widen,” said Anahita Tafvizi, chief data and analytics officer.“Data quality, governance, and organizational capabilities will be key factors in determining the level of AI utilization,” he said.

In particular, with the introduction of agentic AI expected to increase developer productivity by approximately 33%, the importance of talent with orchestration capabilities that organically connect data, AI, and business tools is expected to increase.

The report noted that feedback loops and self-verification mechanisms are essential for agentic AI to be fully utilized in corporate environments.

When a structure is established that reflects user feedback and adjusts its own judgment, AI can make more sophisticated decisions.

“Just as Google’s search algorithm has evolved based on click data, Agentic AI will also learn user patterns and increase its reliability,” explained CEO Ramaswami.

It also predicted that micro-agents specialized for specific tasks would proliferate before single 'super-agents'.

“By combining micro-agents like Lego blocks, we can efficiently handle complex tasks,” said Snowflake CIO Mike Blandina.

Analysis also suggests that for agentic AI to spread across corporate systems, a protocol that standardizes communication between AI agents and external systems is needed.

Just as TCP/IP drove the spread of the internet, the emergence of a dominant AI protocol is expected to significantly accelerate development and interoperability.

The role of the open source foundation model is also expected to expand further.

It is also expected that the operational infrastructure will be reorganized from an analysis-centered structure to a real-time processing and status management-centered structure.
<br /> In particular, Postgres supports online processing workloads that require low latency and fast response, and is expected to emerge as a core infrastructure for large-scale real-time event processing generated by agentic AI.

The report analyzed that agentic AI will be a double-edged sword in the security environment.

“Agentic AI can perform sophisticated attacks, such as vulnerability detection, exploit automation, and data exfiltration, which could magnify the threat landscape,” warned Snowflake CISO Brad Jones.

On the other hand, there is also a positive outlook that utilizing AI agents can strengthen the response capabilities of security operations centers (SOCs) and alleviate the problem of personnel shortages.

The report predicted that agentic AI will expand to focus on practical work execution in major industries such as retail, finance, and manufacturing.

Snowflake emphasized that "2026 will be the first year for companies to move beyond simple AI adoption and build a company-wide AI ecosystem."