Dive Brief:
- Snowflake is putting billions behind its enterprise AI strategy. On Wednesday, the company expanded its collaboration with AWS, making a $6 billion infrastructure commitment to the tech giant over the next five years, according to a company announcement. The investment in AWS Graviton processors and AI infrastructure reflects growing demand among enterprises for running data and AI workloads.
- The data warehousing and analytics vendor is also bolstering its play for enterprise AI agent adoption through its acquisition of Natoma, a Model Context Protocol platform. The platform provides governance capabilities and will add an identity layer for AI agents, helping enterprises oversee AI system interactions, according to a separate Wednesday announcement. Terms of the deal were not disclosed.
- “Across industries, organizations are moving toward a future where employees and intelligent agents work side by side to accelerate decisions, automate complex workflows and unlock entirely new levels of productivity and innovation,” Snowflake CEO Sridhar Ramaswamy told investors during the company’s earnings call Wednesday. Snowflake reported $1.39 billion in revenue during its Q1 2027, up 33% year over year.
Dive Insight:
Snowflake’s investments in AI infrastructure and agent capabilities align with customer interest in how the technology can redefine business workflows, as well as personalize customer and employee experiences.
Global financial services company BNY deploys multiple AI agents throughout the bank’s operations, including digital engineers that find and fix low-complexity code issues. Meanwhile, retail giant Walmart has rolled out different agent platforms, allowing the technology to touch every part of its operations.
Agentic AI is pushing enterprises to rethink how their businesses operate, according to Gartner. Eight in 10 CEOs said autonomous AI will drive meaningful change in their operational capabilities.
Vendors are rushing to meet enterprise demand for the technology.
Google launched its Gemini 3.5 family of models for agentic work earlier this month. LLM provider Anthropic released AI agent templates for financial services companies earlier this month as well, and OpenAI teamed up with ServiceNow in January to enhance its enterprise AI capabilities.
Snowflake is also bidding for enterprise spend and has spent the last several months partnering with companies to meet that end, including its recent AWS partnership expansion. The company expanded partnerships with Anthropic and Accenture in December to scale enterprise agentic and generative AI adoption.
“Our platform brings together the four elements organizations need to become an agentic enterprise,” Ramaswamy said during this week’s earnings call. “A unified, governed data foundation, access to leading AI models, connectivity across enterprise applications and workflows, and a unifying agentic control plane that turns intent into governed actions.”
Still, even as agentic AI adoption takes industries by storm, CIOs are caught in a balancing act between technology, processes — and people. Technology leaders speaking during the MIT Sloan CIO Symposium earlier this month highlighted the criticality of investing in employees to ensure the long-term success of AI projects.
