Draft for review. Framing and scope statements below should be confirmed before publication.
Artificial intelligence is entering the institutions that decide things about people: courts, tribunals, ministries, regulators, and the enterprises they oversee. The question those institutions now face is not whether to use intelligent systems, but how to do so within the constraints of law — transparently, accountably, and in a manner that survives scrutiny.
This practice advises on precisely that question. It is non-jurisdictional in nature: governance, standards, and strategy work that draws on legal method without constituting the practice of law in any particular forum.
For public institutions
Frameworks for algorithmic and AI-assisted decision-making in public administration; accountability and review mechanisms; procurement standards for AI systems; and the design of processes that preserve meaningful human judgment where the law requires it.
Sovereign AI strategy
Advice to governments and public bodies on sovereign AI capability — national and sub-national infrastructure resilience, data governance, and alignment with the emerging international regulatory landscape, from the European Union's AI Act to Canada's evolving federal approach.
Enterprise governance
Compliance architectures for organisations deploying AI in regulated or high-impact settings: governance policies, risk classification, audit and documentation practices, and readiness for the regulatory regimes now taking shape across jurisdictions.
How this work is organised
Advisory engagements are conducted in association with Ethical AI AI Governance, a governance initiative founded by Mr. Patel, and are informed by his doctoral research at Queen Mary University of London on AI systems that operate within the constraints of law. Where questions become contentious — where automated systems meet litigation — the litigation practice takes over.
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