Start an AI Persuasion and Behavioral-Science Governance Advisory

1. 1

   Name the encoded-persuasion problem

   Your insight is that AI systems now encode specific human persuasion tactics (the documented example is a collection agent asking a debtor to repeat a promise aloud for commitment effect), and that these behaviors carry ethical and legal risk most builders never examine. Make the invisible visible for clients. This framing is the reason to hire you before a problem surfaces.

2. 2

   Build the tactic taxonomy

   Catalog persuasion techniques an AI might use and classify them: acceptable and honest, gray-area, or crossing into manipulation, coercion, or deception. In collections, the line matters because harassment and deception are also legal violations. The taxonomy is the framework you sell and apply.

3. 3

   Set governance guardrails

   Help clients decide which tactics their AI may use, document the rationale, and build constraints so the system cannot drift into coercive behavior at scale, which is a real risk when persona systems optimize for outcomes. Governance here is both an ethics and a liability control. Cross-reference the persona-based AI collections and compliance-first platform cards, where these tactics live.

4. 4

   Tie ethics to compliance and reputation

   In regulated collections, an unethical persuasion tactic is often also an FDCPA or unfair-practices violation, and even where it is legal it is a reputational landmine. Show clients that governing persuasion protects them legally and publicly, not just morally. This dual argument is what moves skeptical, outcome-focused teams.

5. 5

   Sell governance engagements and generalize

   Offer persuasion-audit and governance-design engagements to collections AI vendors first, then extend to any persuasion-based AI (sales, marketing, engagement products), at high advisory margins (roughly 50 to 80 percent net). There is no income promise; demand grows with scrutiny of AI persuasion and the EU AI Act. Your credibility rests on being the person who flagged the risk before it became a headline.

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