When AI Carries Your Name: A Briefing for Leaders Using AI at Work
A practical briefing for leaders using AI at work who need to understand when faster output becomes a judgment, approval, or reputation risk.
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Business leaders, executives, senior managers, general counsel, compliance leaders, risk leaders, consultants, and board-adjacent professionals.
Human accountability for AI-assisted decisions, documents, reports, advice, approvals, and oversight.
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What must be true before AI-assisted work carries your name
Where your name is already attached
Identify where AI-assisted work may already be touching your approval, professional judgment, or reputation.
When human review is not enough
Understand why “human in the loop” language can still leave accountability unresolved.
What must be verified
Examine what must be checked before AI-assisted work is approved, shared, submitted, or relied upon.
Why software cannot own judgment
See why technical controls and software tools cannot replace human accountability.
The five accountability conditions
Evaluate time, review capacity and tools, information access, documentation infrastructure, and formal refusal rights.
The Name Standard℠
Use Lozen Advisory’s framework to identify accountability gaps before they become visible failures.
How the hour runs
Where AI is touching human judgment
How ordinary AI-assisted work becomes an approval, reputation, and accountability issue.
When oversight becomes ceremonial
Why a named human reviewer does not automatically create meaningful accountability.
The five conditions of the Name Standard℠
Time, review capacity and tools, information access, documentation infrastructure, and refusal rights.
Applying the standard at work
What leaders should verify before approving, sharing, submitting, or relying on AI-assisted work.
Hosted by Lozen Advisory
Akilah E. Kamaria leads Lozen Advisory, a governance advisory firm providing strategic counsel for the era of algorithmic accountability.
When AI-assisted work carries your name, what can you actually verify?
Attend the webinar to examine the conditions required for meaningful human accountability before AI-assisted work is approved, shared, submitted, or relied upon.