The jurisdictions were selected to highlight meaningful variation in governance structures, political priorities, and administrative capacity across Bay Area municipal legal systems. Together, they represent distinct institutional arrangements through which predictive litigation analytics may be adopted, governed, and contested.
A consolidated city–county government with centralized legal authority, extensive litigation exposure, and relatively mature data and analytics infrastructure.
A county-level governance structure with multiple client agencies and decentralized legal demands, offering insight into how predictive tools operate across diverse departments and policy areas.
A mid-sized county government with comparatively constrained resources, providing a contrast in scale, procurement capacity, and analytic adoption.
A large, innovation-oriented county with strong ties to the technology sector, offering a case where data-driven governance and experimentation may be more institutionally embedded.
In addition to the four major jurisdictions above, this project will also include some additional counties that can provide valuable contrasts, particularly if some of these counties have not adopted predictive litigation technologies or have taken different governance approaches. Smaller or less-resourced counties may reveal important patterns about what enables or constrains artificial intelligence (AI) adoption. An understanding of variation in governance frameworks requires having "negative cases" (counties that haven't adopted these tools) or "alternative cases" (counties with different oversight models) will strengthen the comparative analysis of this project.