Responsible AI, Security & Governance

Map who is affected, what can go wrong, and who owns the decision.

• Harms, stakeholders, risk tiers, and governance roles
• Lifecycle controls from intake through retirement
• Impact scoping, decision records, and escalation paths

Deliverable: a system impact assessment with risk tier, stakeholders, and proposed controls.

Follow data through a system without pretending the source is the whole story.

• Consent, minimization, provenance, retention, and sensitive data
• Access controls, purpose limitation, and vendor boundaries
• Data-flow mapping and practical governance questions

Deliverable: an AI data governance plan with data flows, controls, owners, and open questions.

Choose measurement and explanation practices that fit the stakes and the people affected.

• Measurement choices, subgroup analysis, and tradeoffs
• Interpretability, documentation, and user-facing explanations
• Data gaps, proxy risk, and what a metric cannot establish

Deliverable: a bias and equity evaluation with subgroup results, limitations, and mitigation options.

Threat-model the seams where models, tools, data, and users meet.

• Threat modeling, prompt injection, and insecure tool use
• Data exfiltration, supply-chain risk, and privilege boundaries
• Adversarial tests, severity, and remediation ownership

Deliverable: an adversarial test suite with findings, severity, and recommended fixes.

Turn responsible practice into evidence another reviewer can inspect.

• Model and system cards, audit evidence, and vendor review
• Incident response, change control, and approval records
• Control mapping without confusing documentation for safety

Deliverable: a control evidence pack with owners, artifacts, gaps, and review cadence.

Evaluate an enterprise AI product from intake through launch recommendation.

• Risk register, system boundary, and stakeholder review
• Red-team report, controls, residual risk, and launch conditions
• Executive recommendation that is clear about uncertainty

Capstone: a risk register, red-team report, control set, and executive recommendation for an AI product.