Start an AI Admissibility and Examiner-in-the-Loop Governance Consultancy

1. 1

   Define the pattern you sell

   Your core insight is that in legally consequential domains, human oversight and defensibility must be designed into the AI product, not added later. Package that as a clear method, because vendors know they have a risk but rarely know how to build for it.

2. 2

   Learn where AI assistance ends

   The pivotal line is between AI that accelerates intake and anomaly detection and AI that touches a credentialed professional's actual opinion, which is where documented liability begins. Master that boundary across a few fields, since spotting exactly where a product crosses it is your differentiated value.

3. 3

   Build a defensibility assessment

   Create a repeatable review that examines a product's human-in-the-loop design, audit trails, explainability, and how its output would hold up under cross-examination or regulatory review. A concrete deliverable, a report with prioritized fixes, sells far better than open-ended advising.

4. 4

   Pick your beachhead domains

   Forensics, legal tech, healthcare AI, and financial-compliance AI all share this problem. Start where your background gives you credibility, then generalize the method to adjacent regulated fields as you build case studies.

5. 5

   Sell to vendors and their buyers

   AI vendors want to close enterprise and government deals that hinge on defensibility, and institutional buyers want assurance before adopting. Both will pay for an independent assessment, and conference talks on courtroom-ready AI put you in front of both at once.

6. 6

   Price by project and retainer

   Fixed-fee assessments to start, then advisory retainers as vendors iterate their product and governance. Work with, not instead of, their lawyers, and be explicit that you advise on design and risk rather than giving legal opinions unless you are a licensed attorney doing so.

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