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AI Fluency Determines Trust Threshold

User trust in AI agents is inversely correlated with their AI fluency - less fluent users lose trust after single failures while fluent users expect iteration and refinement

Decision Rule

Before deploying AI to low-fluency users, implement extensive guardrails, testing, and gradual introduction to prevent trust loss from early failures

How It Works

AI-fluent users understand that agents require prompting, context, and iteration to work well, while non-fluent users expect perfect performance immediately and lose confidence after one bad experience

Failure Modes

Deploying imperfect AI to non-fluent users without education

Not implementing sufficient guardrails for low-fluency environments

Assuming all users will iterate and improve AI performance

Under-investing in user education about AI limitations

Example Decision

A company introduces AI customer service agents first to their technical support team (high AI fluency) for iteration, then deploys to general customer service team (lower fluency) only after extensive testing and training