Responsible AI consulting · AI governance
What is responsible AI consulting?
Responsible AI consulting turns policy language into operating practice. It defines which tasks staff may hand to AI, which require human review, and which are prohibited. The work produces written boundaries, review owners, escalation paths, and documentation a team of fifteen can actually follow and defend later.
The difference between an AI policy and AI governance
A policy states intent. Governance decides who does what, when review happens, and what gets recorded. Most organizations have the first and not the second, so staff improvise and the audit trail becomes a log nobody reads.
A three-level task boundary
| Tier | Meaning | Control |
|---|---|---|
| Tier 1 | Safe and low risk. No sensitive information, low consequence if wrong. | Approved use list. Spot checks. |
| Tier 2 | Useful but consequential. Public-facing output, records, or judgment calls. | Named human review before release. |
| Tier 3 | Prohibited or specialist only. Sensitive, legal, clinical, or identifying information. | Blocked, or routed to a designated owner. |
What an acceptable-use framework contains
- Approved tools and accounts, named explicitly.
- Task-by-task classification into the three tiers.
- The information that may never be entered into a tool.
- Who reviews Tier 2 output, and what review means.
- When and how staff escalate, with a response expectation.
- What gets logged, who reads the log, and on what date.
- Review cadence and the owner of the next revision.
How the engagement runs
- Discovery: current tools, tasks, records, and pressure points.
- Readiness review: the gap between policy, actual tool use, workflow, human review, escalation, and manager follow-through.
- Boundary drafting in plain language, sized for the team.
- Role-specific briefing so staff and managers can apply it.
- Review calendar with named owners and dates.
Evidence boundary
A three-level task boundary identifies lower-risk approved use, use requiring human review, and prohibited or specialist-only use. This work is educational and operational. It is not legal, compliance, or clinical advice. Final scope, deliverables, and pricing are confirmed in writing before work begins.
Questions buyers ask
Direct answers
- What is human-in-the-loop AI governance?
- It is governance that names a person, not a principle. A specific role reviews defined output before it reaches the public or the record, and that review is documented.
- Who should review AI-generated work?
- The person already accountable for the output. Governance should follow existing responsibility rather than create a new committee.
- When should an employee escalate an AI task?
- When the task involves sensitive or identifying information, a legal or clinical question, an unfamiliar tool, or an output they cannot verify.
- How should an organization classify AI use by risk?
- By consequence, not by tool. Sort tasks by what happens if the output is wrong, then apply Tier 1, Tier 2, or Tier 3 controls.
Next step
Discuss governance support.
A twenty-minute scoping call confirms audience, current tool use, and whether a bounded governance engagement is the right first step.
Contact question: what audience and outcome does your initiative need to support?