AI literacy should change how people choose tools, protect data, verify outputs, disclose assistance, and escalate errors. One generic prompt class rarely covers those responsibilities.
People often adopt tools because approved workflows are slow or unclear. An inventory should reveal jobs, data, accounts, integrations, costs, and unmet needs before it assigns remediation.
A workflow can change when the model, prompt, retrieval source, tool permission, policy, price, or human checkpoint changes—even if the application name does not.
“Human in the loop” is too vague when a tool encounters identity risk, money movement, safety, legal claims, upset customers, missing evidence, or conflicting instructions.
Connected agents can accumulate new tools, broader scopes, changed owners, stale tokens, and exception rules. A short recurring review can reveal drift before it becomes an incident.
Training content can be factually plausible and still teach the wrong sequence, omit prerequisite knowledge, overload learners, or give an unsafe example.