Reflections are deeper dives into how law, technology, and innovation intersect. These longer form pieces analyze research and emerging trends — offering perspectives that help teams navigate what's coming next.
Conversational interfaces break down when AI handles complex workflows and governance requirements. Deploying autonomous systems requires new interface patterns for transparency, control, and human oversight
"This 2023 analysis correctly predicted that AI audit requirements would create compliance theater without meaningful bias prevention, warnings that have proven increasingly relevant as agent technologies emerge."
Every six months, the rules change. Old playbooks don't work anymore. The only way through is to ask better questions. Here are nine questions that matter for anyone building with AI
EDPB guidance demonstrates how structured privacy governance approaches for LLM systems create competitive advantages while ensuring regulatory compliance.
Organizations can't engineer moats from a business plan. Defensibility emerges from solving real problems—discovering unique workflows, building proprietary datasets, and integrating so deeply into operations that switching becomes prohibitively expensive.
The most practical insight involves accepting that perfect solutions do not yet exist. Traditional agency mechanisms provide valuable frameworks for identifying problems and structuring solutions; however, new technical and legal infrastructure must evolve in tandem with the technology.
Credo AI's Unified Control Framework maps 42 controls to multiple risks and regulations simultaneously, reducing governance fragmentation through bidirectional mappings and concrete implementation guidance.
After Stanford Law's agentic AI program, it was clear: companies are building autonomous capabilities faster than they can deploy them responsibly. This is part of a series exploring organizational frameworks that can keep pace with AI autonomy, which emerged from that program.
