Public Sector Data Modernization for AI Readiness

Legacy data systems in government agencies are increasingly recognized as barriers to AI adoption and mission delivery, not just IT challenges. Federal mandates and public demand for faster services have made modernization urgent. Leaders at Snowflake Summit highlighted how outdated infrastructure creates silos that prevent effective data use. Without modern data platforms, agencies cannot support AI workloads central to serving communities. The shift in perspective treats data modernization as a mission-critical priority rather than a technical task.

Multnomah County, Oregon, migrated from a decade-old SQL Server environment to a modern platform in five months using Snowflake’s SnowConvert AI. The hybrid migration approach combined deterministic code conversion with AI-assisted fixes for complex tasks like dynamic SQL and automated testing. The county reduced future licensing costs, standardized architecture across previously siloed departments, and improved collaboration between health, public safety, and library systems. Officials emphasized the importance of early preparation and starting migrations well before licensing deadlines.

San Francisco’s Chief Data Officer, Soumya Kalra, is leading a cultural and technical shift to break departmental silos and embed data-driven decision-making in service delivery. The city’s modernization focuses on building trust, shared standards, and internal champions before unifying data across agencies. Kalra’s team prioritizes involving stakeholders from all operational functions, not just IT, to ensure solutions meet real-world needs. The effort underscores that change management, not technology alone, determines the success of modernization efforts.

Public sector organizations that succeed in modernization reframe data as a strategic asset rather than a back-office concern. Agencies like Multnomah County and San Francisco view their data foundations as runways for future AI and predictive analytics capabilities. Tools like AI-assisted migration and governed-data platforms exist to accelerate this shift, but agencies must allocate sufficient time for testing, stakeholder engagement, and phased implementation. The goal is a unified, governed data environment that enables cross-agency insights and sustained innovation.