9. AI in People Work
AI-fy, augment, keep human
The decision framework
Use when
Every 'should AI do this' question in a people process
AI-fy
Low judgment, low empathy load, low error cost, decent data: automate the admin end-to-end, human audits
Augment
Valuable but judgment-bearing: AI drafts, assembles, themes; a named human decides and owns
Keep human
High empathy, high stakes, or consultation-sensitive: humans only, stated publicly
“Assess each workflow on judgment, empathy, error cost, data readiness and sensitivity.”
The decision path
- 01Is the task legally sensitive, consultation-sensitive, high-empathy or high-consequence? Keep the decision human. AI may assist only within explicit boundaries.
- 02Is the work rules-based, reversible, low-sensitivity and supported by reliable data? AI-fy it, with monitoring and a named owner.
- 03Everything between those points belongs in Augment. AI can draft, assemble or identify patterns. A named human decides and owns the outcome.
Move through it with these
- Judgment
- How much judgment does the task require?
- Empathy
- Is empathy part of the task, or only part of how the outcome is told?
- Error cost
- Who carries the consequence if it is wrong, and can it be reversed?
- Data readiness
- Is the data accurate, representative and permitted for this use?
- Sensitivity
- Does it touch pay, jobs, rights, privacy or a consultation duty?
How to use it
The public boundary is the trust move. Name the decisions AI will not make: discipline, ratings, hiring, grievances and accommodation. AI may assist with administration or preparation only where that use is lawful, governed and clearly bounded. A named human decides and owns the outcome.
Questions to ask
- How much judgment does the task require?
- Who experiences the consequence if it is wrong?
- Is empathy part of the task or only part of how the outcome is communicated?
- Is the data accurate, representative and permitted for this use?
- Does the task affect someone's job, pay, opportunity, reputation, privacy or rights?
- What decision must a named human continue to own?
- How will the use be monitored and reviewed?
The output
A one-page decision record naming the chosen path, the permitted AI role, the accountable human, the controls, the public boundary and the review date.
Where it breaks
- Treating technical capability as permission
- Calling a person “human in the loop” when they have no real authority
- Using weak or unrepresentative data
- Automating the sensitive decision while keeping only the communication human
- Failing to tell employees where AI is used
- Treating the first classification as permanent
Card details
- Model type
- Grid
- Origin status
- Synthesis
- Content last reviewed
- 28 July 2026
Origin
SynthesisAutomate, augment, keep human is common vocabulary in AI practice. What is specific here is the five-way scoring (judgment, empathy, error cost, data readiness, sensitivity) and the public never-AI list as a trust move. Assembled by Harsimran Kaur Kapoor, 2026.