Checklist
Keep task stewardship when AI does the middle
Delegating the middle does not delegate the job.
When it fits
- AI generates a substantial part of the work and ownership can quietly move from the person to the tool.
When to avoid it
- Stewardship can be shared across a team; the point is explicit ownership, not insisting that one person personally performs every check.
Checklist
- The human defines the task outcome before generation.
- Acceptance criteria are visible.
- AI output is integrated with local context rather than pasted blindly.
- Material claims or actions receive appropriate verification.
- One person owns the final accept/reject decision.
Why it matters
Keep three human responsibilities explicit: define the goal and acceptance criteria, integrate the output into the real context, and decide whether the final artifact is fit to use. The model can generate and transform; the accountable worker still owns what problem is being solved and what happens next.
An example
AI drafts a test plan, but the consultant decides which business risks matter, adds system-specific constraints and signs off the final coverage.
Check your result
If the AI output disappears, someone can still explain the goal, criteria and why the final result was accepted.
Keep this limit in mind
- Stewardship can be shared across a team; the point is explicit ownership, not insisting that one person personally performs every check.
Evidence and sources
Knowledge workers in the CHI 2025 study described critical AI-assisted work as shifting toward information verification, response integration and task stewardship.
These themes describe reported practice and should not be treated as an exhaustive model of good AI use.
The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers · Qualitative findings