Insights
Practitioner depth on making the data beneath your AI trustworthy, explainable, and auditable — not brochure fluff.
The full blueprint: the Why, What, Where, How — plus how AI connects to your data and where the guardrails go. With a glossary.
Regulators just confirmed SR 11-7 excludes generative AI — and that gap is your exposure. How to close it.
Read it → Agentic AIAgents don't just answer — they act. The five controls that keep them safe, bounded, and auditable.
Read it → FrameworksUnder DORA, AI is ICT risk and operational resilience — not an ethics topic. What you must actually do.
Read it → The landscapeSeven forms of AI reporting, from self-service to agentic — and the one foundation every one depends on.
Read it → AI reportingThe #1 reason AI reporting goes wrong — and the one control that fixes most of it.
Read it → ReadinessSeven concrete tells your data foundation isn't ready — and what to do about each.
Read it → FoundationsThe single most important control between your data and an AI that answers questions about it.
Read it → Financial servicesGovern AI that touches financial reporting using the controls your bank already runs.
Read it → RiskWhat shadow AI is, why finance is exposed, and how to govern it without killing productivity.
Read it → FrameworksThe three frameworks demystified — and the practical actions that actually matter.
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