Arun Jayapal

Innovation without governance is just liability waiting to happen.

As organizations rush to deploy LLMs, safety often takes a backseat. But in high-stakes domains like Finance, LegalTech, or Healthcare, a single data leak or biased output can destroy trust.

Drawing on my experience establishing the AI Quality Assurance Framework at EY and architecting compliance systems for Onit, I offer a technical and process-level audit of your AI strategy.

What we will cover:* The "Big 3" Audit: Evaluating your models against the pillars of Robustness, Fairness, and Explainability.

1. PII & Data Leakage: Reviewing your redaction pipelines. Are you stripping sensitive entities (NER) before they hit the context window?.
2. Guardrails & Hallucination: analyzing your current "evals" strategy. Do you have deterministic checks in place to prevent the model from going rogue?
3. Regulatory Readiness: A high-level check on how your architecture aligns with emerging standards (like the EU AI Act principles).

Who is this for? Heads of AI, CTOs, and Product Leaders in regulated industries (Fintech, Legal, Health) or startups preparing for enterprise due diligence.

Outcome: You will move from "hoping it's safe" to having a defensible governance strategy with clear action items for your engineering team.