A useful AI transparency session you can run this week.
The AI System Disclosure gives MSPs and consultants a clean first engagement: help the client publish basic AI transparency, then turn the gaps into concrete PSF evidence work.
Do not sell fear. Publish clarity. Then help the client close the evidence gaps the disclosure exposes.
Run the meeting like a standards body, not a software demo.
List where AI is already used: chat, email, documents, support, sales, code, finance, HR, and vendor tools.
Record people affected, data touched, autonomy level, owner role, human route, and incident process.
Generate the AI System Disclosure and decide what should be public now versus improved before publication.
Map priority actions to PSF domains: input boundary, output validation, observability, human oversight, security, and vendor resilience.
Agree one evidence artifact to create this week: data boundary, escalation route, incident log, eval record, or fallback plan.
A simple script that lands with non-technical leaders.
You are probably already using AI in more places than you think. The goal today is not to shame anyone or block useful tools. It is to publish the basic facts a customer, employee, or regulator would reasonably expect to see.
What stronger assurance usually requires next.
A disclosure is a public transparency record. When the system is consequential, the next work is usually concrete: workflow capture, controls, policy, evidence packs, incident exercises, vendor reviews, and formal assurance.