Governance, Evidence and Trust
Do You Trust Your AI’s Decisions?
Why trust in artificial intelligence depends on evidence, traceability, roles and review criteria, not just the apparent quality of a response.
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Trust is not an impression about the answer. It is the infrastructure that allows explaining how the decision was produced, reviewed and authorized.
An eloquent answer can be fragile. When the organization does not record context, sources, responsible parties and criteria, it confuses persuasion with reliability.
Governance does not exist to promise absence of error. It exists to make the process observable, allow correction and clarify who can authorize each use.
THREE PRACTICAL DECISIONS
- Record the evidence used in relevant decisions.
- Define the responsible party, reviewer and approval authority.
- Create a simple path to challenge and correct an output.
If this decision were questioned tomorrow, would your organization be able to reconstruct the reasoning?
Use this question as the agenda for your next conversation with the team. The goal is not to reach a universal answer, but to make visible the criteria, limits and responsible parties of the real context.