Snowflake CEO: AI Will Kill Legacy Software

Snowflake CEO Sridhar Ramaswamy's perspective is shaped by his 15-year tenure at Google, where he was integral in growing the AdWords and advertising business from $1.5 billion to over $100 billion. Before his current role, which he assumed after Snowflake acquired his AI-powered search engine startup Neeva, he spearheaded Snowflake's AI strategy. The strategy to replace legacy software hinges on Snowflake’s "AI Data Cloud" platform. It provides tools like Cortex AI, a managed service offering pre-built AI models for tasks like sentiment analysis and summarization, and Snowpark ML, a framework for developers to build custom models directly on their data without moving it. This allows companies to create their own AI applications securely within the Snowflake environment. This shift toward agentic AI is not unique to Snowflake; it represents a broader market evolution from simple automation to autonomous systems that can reason and adapt. For instance, ServiceNow now offers an AI Agent Studio and Orchestrator to automate complex, cross-department workflows in areas like HR service delivery and IT operations. Internal pilots at ServiceNow have seen agents automate 97% of software provisioning and resolve 85% of routine IT requests. Other enterprise software giants are making similar moves. Oracle is embedding AI agents directly into its Fusion ERP and HCM applications, while Salesforce is evolving its Einstein platform into "Agentforce" to autonomously execute multi-step sales and service tasks. In the HR space, Workday has introduced generative AI for creating job descriptions and employee growth plans, leveraging its vast dataset of HR and finance transactions. The target for this disruption is the substantial legacy software modernization market, which was valued at over $26 billion in 2025 and is projected to grow to over $92 billion by 2034. This market is driven by the urgent need for enterprises to resolve technical debt and enable cloud-native agility. Financial markets are already signaling this capital reallocation. Analysts suggest that weaker-than-expected revenue guidance from major SaaS players like Salesforce can be partly attributed to enterprises beginning to shift budgets away from legacy SaaS investments to fund new generative AI initiatives. McKinsey forecasts that generative AI is being adopted three times faster than SaaS was, potentially doubling the rate of vendor switching as companies seek out modern, AI-native platforms.