# AI Governance Policy Template for Manufacturers > Source: https://netray.co/tools/ai-governance-policy-template-for-manufacturers > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Fill in your company details and get a ready-to-edit AI use policy covering approved tools, data handling, oversight and incidents. ## Category compliance-legal ## Industry Manufacturing ## Audience - CIO - IT manager - Compliance manager ## Tool **Kind:** template **Output:** document **Fields:** #### Company name **Key:** company **Type:** text **Default:** Acme Precision Components Ltd #### Policy owner (role) **Key:** owner **Type:** text **Default:** Chief Information Officer #### Effective date **Key:** effective **Type:** date **Default:** 2026-11-01 #### Version **Key:** version **Type:** text **Default:** 1.0 #### Approved AI tools **Key:** approved_tools **Type:** textarea **Default:** Company-hosted ERP assistant; enterprise tenant of the approved office assistant. No other AI tools may be used with company data until approved. #### Restricted data (never entered into unapproved tools) **Key:** restricted_data **Type:** textarea **Default:** Customer drawings and specifications, export-controlled technical data, supplier pricing, employee personal data, financial results before publication, and ERP database extracts. #### Export-controlled work **Key:** controlled **Type:** select **Options:** - Applies (ITAR or EAR) - Does not apply **Default:** Applies (ITAR or EAR) #### Policy review cycle **Key:** review **Type:** select **Options:** - Every 6 months - Annually **Default:** Annually #### Incident contact **Key:** contact **Type:** text **Default:** security@example.com **Blocks:** #### {{company}} Artificial Intelligence Governance Policy **Body:** Version: {{version}} Effective date: {{effective}} Policy owner: {{owner}} Review cycle: {{review}} #### 1. Purpose and scope **Body:** This policy sets the rules for using artificial intelligence, including generative AI assistants, AI agents and machine learning features embedded in business software, at {{company}}. It applies to employees, contractors and any supplier acting on our behalf. The aim is to let teams use AI to work faster in engineering, quality, supply chain, finance and IT while protecting customer data, intellectual property, safety and compliance. #### 2. Approved tools **Body:** Only the following AI tools may be used with company information: {{approved_tools}} New tools require a request to the policy owner, a security and data protection review, and a recorded decision. Personal accounts on public AI services must not be used for company work. #### 3. Data handling **Body:** The following data must not be entered into any tool that is not approved for it: {{restricted_data}} Export-controlled work: {{controlled}}. Where this applies, technical data must stay inside systems that meet our export control procedures and must be accessible only to authorized persons. #### 4. Human oversight **Body:** AI output is a draft. The person using it remains accountable for decisions, communications and records that rely on it. AI must not independently approve purchase orders, release product, disposition nonconforming material, change safety-critical records or post financial entries. Any action that changes ERP, MES or quality data requires approval by an authorized person, and the AI action must be logged. #### 5. Quality and safety **Body:** Use of AI in design, process planning, inspection or customer deliverables must be disclosed to the responsible engineer or quality manager. Outputs that affect product conformity must be verified by a qualified person against the controlling specification or standard before use. #### 6. Agents and system access **Body:** Every AI agent must have its own identity, least-privilege access, defined transaction limits, a named business owner and a tested method of disabling it. Agent permissions are recorded in the permission matrix and reviewed at least quarterly. #### 7. Incidents and reporting **Body:** Report suspected misuse, data leakage, harmful or incorrect output that reached a customer, or unexpected agent behavior immediately to {{contact}}. Do not attempt to hide or delete evidence. Incidents are logged, assessed for notification duties, and reviewed for process change. #### 8. Training and enforcement **Body:** All users must complete AI awareness training before gaining access to approved tools. Violations may lead to disciplinary action in line with company policy. #### Approvals **Signatures:** - Policy owner - Head of Quality - Head of Legal or Compliance - Managing Director **Notes:** This is a starting point, not legal advice. Have counsel and your export control officer review it, and align it with customer contract flow-downs, data protection law in your countries and any AI regulation that applies to you, such as the EU AI Act. ## Content **Intro:** Employees are already pasting drawings, quotes and ERP exports into public chatbots. A short written policy, approved tools and clear data rules close that gap faster than any technical control alone. **Sections:** #### How to use the template **Body:** Fill in the company details, the list of approved tools and the data you want to keep out of unapproved services. Choose whether export-controlled work applies to you, then export to Word and edit the language to fit your culture and legal advice. Keep the policy to a few pages. Policies that run to thirty pages are not read, and a short policy with a clear approved-tools list changes behavior more than a long one. #### What a manufacturing AI policy must cover **Body:** Generic corporate policies miss the issues specific to plants and engineering firms. Customer drawings and specifications often carry contractual confidentiality. Defense and aerospace work may involve ITAR or EAR controlled technical data that cannot leave authorized systems or reach unauthorized persons. Quality records are audit evidence. A policy should therefore name restricted data classes, require human approval for changes to conformity records, and set rules for agents with ERP access. **Bullets:** - An approved tool list that people can actually find - Named restricted data, not a vague reference to sensitive information - Human approval for anything touching quality, safety or financial records - A simple reporting path for incidents #### Rolling it out **Body:** Publish the policy together with an approved alternative, otherwise people keep using public tools. Pair it with a short training session and a way to request new tools within a few days. Review the incident log at each policy review and adjust. For private AI such as an on-prem ERP assistant, show staff what data it sees and how answers are logged, since trust depends on visible controls. #### Common mistakes **Body:** The most common failure is banning AI outright without giving a sanctioned option, which drives use underground. Another is writing rules nobody can check. If the policy says all AI output must be verified, define who verifies what. Finally, do not skip contractor and supplier coverage: a consultant using a public chatbot on your drawings is still your problem. **Cta:** If you need an approved AI option that keeps ERP and document data on your own infrastructure, we can help you deploy one that fits this policy. **Faq:** #### Is this policy legally binding? **Answer:** It becomes binding when your company adopts it, communicates it and ties it to employment terms. The template is a starting point and should be reviewed by your legal counsel before adoption. #### Do we need a policy if we only use vendor AI features? **Answer:** Yes. Vendor AI inside your ERP, office suite or CRM still processes company data. The policy should name which features are enabled, what data they use and who administers them. #### What about the EU AI Act? **Answer:** Obligations depend on the system's risk category and your role. Most internal productivity uses are lower risk, but transparency duties and AI literacy requirements may apply. Check with counsel for your situation. #### Who should own the policy? **Answer:** Usually the CIO or head of IT, with input from legal, quality, HR and security. Ownership should sit with one named role so decisions on new tools do not stall. ## Search terms ai governance policy template, ai acceptable use policy manufacturing, generative ai policy template, company ai usage policy, ai policy for employees template, ai governance framework manufacturing, responsible ai policy word, chatgpt usage policy company --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json