AI Governance for Manufacturers: A Starter Framework
AI governance for manufacturing without the bureaucracy: a starter framework an ops leader can stand up in 30 days. Risk tiers, owners, evals, audit trail.
Most AI governance for manufacturing is written by people who have never stood on a plant floor. It reads like a privacy policy, runs 40 pages, and lands in a SharePoint folder nobody opens. Meanwhile a planner is pasting your supplier contracts into a public chatbot to summarize them, and a CSR is letting an agent send pricing to customers with no review step. Governance failed not because it was wrong, but because it was unusable.
I was VP of AI at a $250M furniture manufacturer. I shipped agents into purchasing, customer service, and ops planning. The governance that actually held up was one page, tied to real workflows, and owned by named people. Here is the starter framework I'd hand any COO or Head of IT who needs control without strangling the thing in committee.
What AI governance for manufacturing actually has to do
Forget the compliance theater for a second. Governance has exactly four jobs:
- Stop the obvious own-goals — leaked IP, a wrong price quoted to a customer, an agent acting on a hallucinated lead time.
- Make every agent traceable — who built it, what data it touches, who owns the outcome.
- Set the bar for going live — what an agent must prove before it touches a real decision.
- Give you a kill switch — a fast way to pull or pause an agent when it misbehaves.
If your governance does those four things and nothing else, you're ahead of 90% of the mid-market. Everything beyond that is refinement, not prerequisite.
The risk-tier model: not every agent needs the same controls
The single biggest mistake is treating a meeting-notes summarizer like an agent that adjusts inventory in your ERP. Tier your agents by blast radius. This is the table I use.
| Tier | What it does | Example | Control required |
|---|---|---|---|
| T1 — Read/draft | Surfaces info, drafts text a human sends | Supplier-doc Q&A, QBR draft | Owner + data scope logged. No approval gate. |
| T2 — Recommend | Proposes a decision a human approves | Order-hygiene flags, stockout alerts | Human-in-the-loop on every action. Eval set required. |
| T3 — Act | Writes to a system of record or contacts a customer | Auto-reorder, customer pricing reply | Approval gate + audit trail + rollback + named exec owner. |
The rule writes itself: the higher the tier, the more it has to prove before go-live. A T1 supplier-doc agent can ship in a week. A T3 agent that touches your ERP earns its way up from T2 only after it's been right on real cases for weeks.
Most teams should keep almost everything at T1 and T2 for the first year. You get 80% of the value with a fraction of the risk.
The one-page governance doc
Here's what fits on a single page and covers a real manufacturer:
1. Approved data and tools
List what data agents may touch (supplier specs, order history, BI extracts) and what is off-limits without sign-off (employee PII, M&A material, anything under NDA). Name the approved platforms. If it's not on the list, it doesn't get fed to a model. This one section stops the contract-in-a-chatbot problem cold.
2. The go-live checklist
Every agent passes the same gate before production: - Tested against at least 50 real historical cases, not toy prompts - Accuracy and error rate documented on those cases - Human-in-the-loop confirmed on any T2/T3 action - One owner named, one business metric defined - Rollback path written down
3. Owners and the RACI
Every agent has a business owner (the plant or ops leader who answers for the outcome) and a technical owner (who maintains it). IT is consulted on data access. No agent ships without both names filled in. An agent without an owner is a science project, and science projects are where governance goes to die.
4. Monitoring and the kill switch
Define who watches each live agent, how often, and what triggers a pause. For a T3 agent, that's a weekly review of every action it took plus an alert on anomalies. The kill switch is a real thing: a documented way to disable the agent in minutes, tested before launch.
Who sits on the governance group
Keep it small. A 12-person AI committee never ships anything. The working version:
- An ops or plant leader — owns whether the agent helps the floor or gets in its way
- IT/security — owns data access and the integration surface
- One finance voice — owns the ROI number and the budget defense
- The AI lead — owns build quality and evals
Four people, a 30-minute monthly review, and a fast async path for new agents. That's it. The point of the group is to clear agents to ship, not to invent reasons they can't.
What this looks like in practice
A reorder agent comes up. Today it's T3 — it would write POs. Governance says no, not yet. It launches at T2: it drafts reorder recommendations, a buyer approves each one, every recommendation is logged against what the buyer actually did. After six weeks the eval shows 94% of its recommendations were approved unchanged. Now the group has data, not a hunch. They promote the lowest-risk SKUs to T3 with a daily audit. That's governance doing its job — enabling the move while keeping the proof.
The 30-day path to stand it up
- Week 1 — Write the approved-data list and the go-live checklist. One page each.
- Week 2 — Tier every existing and proposed agent. Assign the two owners per agent.
- Week 3 — Stand up the four-person group. Run the first review against the checklist.
- Week 4 — Wire monitoring and the kill switch on anything already live. Document rollback.
Don't wait for a perfect framework. The shadow AI in your building is the actual risk, and it's already running.
Want to see this applied to your real workflows? Grab our free First 5 Agents teardown — we tier the five agents most manufacturers should build first and show exactly where governance gates belong on each. Then book a call and we'll pressure-test your highest-risk agent against the go-live checklist together, on your data, before anything touches production.
Let's see what's worth building first.
A 15-minute call: tell me where your AI or planning is stuck, and I'll tell you the one thing worth building first — and whether it's worth doing at all.