AI Governance Workflow
How AI use cases move from first identification through review, approval, and ongoing monitoring — a repeatable path rather than a one-time conversation.
A use policy sets the standard. A risk review evaluates a specific tool against it. But without a defined workflow connecting the two, both exist in isolation — the policy sits in a document, the review happens inconsistently, and nothing connects one AI approval decision to the next.
Why a Workflow, Not Just a Policy
A policy tells someone what's acceptable. A workflow tells them what to actually do the moment they encounter a new AI tool or feature — who to notify, what information to gather, and how long a decision should take.
Without a defined workflow, every new AI use case becomes a one-off conversation. Some get reviewed carefully. Others get missed entirely, simply because no one knew whose job it was to flag them.
How the Workflow Runs
AI use is identified
A new tool, a vendor feature update, or an existing use case that hasn't yet been formally reviewed enters the workflow.
Intake captures the basics
What the tool does, what data it touches, who wants to use it, and how it would fit into existing legal work.
Risk level is triaged
Lower-risk use cases move toward a fast approval path. Higher-risk use cases — sensitive data, client-facing output, third-party vendors — route to full review.
Review is completed
The use case is assessed against policy, with input from IT or security where the risk profile calls for it.
Decision is recorded
Approved, approved with conditions, or declined — each outcome is logged along with the rationale behind it.
Use is monitored going forward
Approved tools re-enter the workflow if their scope changes, a vendor updates the feature, or usage patterns shift.
The core issue
Most governance failures aren't bad decisions. They're decisions that were never made at all, because nothing in the workflow forced the question to surface.
Fast Path vs. Full Review
Not every AI use case needs the same level of scrutiny. A workflow that treats a low-risk internal tool the same as a client-facing AI feature with third-party data exposure will either move too slowly on the former or too quickly on the latter.
| Fast Path | Full Review |
|---|---|
| Internal use only, no sensitive data exposure. | Client-facing output, or sensitive data such as privileged material or PII. |
| Well-understood tool category with prior approvals. | New tool category, or a vendor with no prior governance track record. |
| Human review of output already built into the workflow. | Output could be relied upon without independent verification. |
| Decision documented, expedited sign-off. | Full risk assessment, documented decision, defined monitoring plan. |
Build the workflow around your actual intake, not an ideal one
The workflow that gets used is the one that fits how requests already reach legal operations today — through an existing intake channel, not a separate AI-specific form no one remembers to use.
Where This Fits in the Governance Model
The workflow is the connective layer between the use policy and the risk review process — it's what makes both of them apply consistently rather than depending on who happens to notice a new tool first. The record this workflow produces is also what feeds governance reporting when leadership or a client asks for it.
A workflow doesn't need to be complicated to work. It needs to be the thing people actually follow, every time, without having to think about it.