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AI can help teams find information, analyze complaints, and prepare quality reviews. Its outputs still need appropriate checks. Explore four everyday QMS examples, with practical controls, verification steps, and evidence to retain. Download the free PDF or get editable slides to adapt for your team.
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18 slides · PDF (914 KB) or editable PowerPoint (854 KB) · Edition 1.0, October 2026
AI tools already help with everyday quality work: searching procedures, summarizing complaints, drafting reports. For a QMS, the useful question isn't how clever the tool is. It's what happens if the output is wrong and nobody checks it.
A draft email that needs tidying is low risk. An AI summary that hides a serious complaint, or points someone to an obsolete work instruction, can affect product conformity and customer satisfaction. So the strength of the check should follow the consequence of an error.
You don't need a separate system for this. The checks fit processes you already run: documented information (clause 7.5) for approved sources and current revisions, competence (7.2) for the people who use and review AI outputs, analysis and evaluation (9.1.3) for complaint data, corrective action (10.2) for causes, and internal audit (9.2) for evidence-based findings.
Based on CBG's clause-by-clause comparison with the 2015 edition, the 2026 revision adds no AI-specific requirements and doesn't require you to use AI. Where AI is used in a QMS process, that process's existing requirements still apply.
The 2026 note to clause 7.1.6 lists knowledge “held in documented information, digital systems and other media” among the forms organizational knowledge can take. A note explains; it doesn't add a requirement.
The examples, checks and pilot approach on this page and in the presentation are CBG's own suggested practices, not ISO requirements. Adapt them to your processes and risks.
Illustrative CBG scenarios, not ISO requirements. Each one pairs a task where AI saves time with the most likely way it goes wrong.
| QMS activity | Useful AI task | What could go wrong | Suggested check |
|---|---|---|---|
| Document search | Locate an applicable instruction. | An obsolete revision is used. | Check the approved source and current revision before acting. |
| Complaint analysis | Group complaints into themes. | A rare, serious case disappears in the summary. | Trace results to originals and review critical exceptions separately. |
| Corrective action | Organize facts and suggest possible causes. | An explanation is accepted without evidence. | Treat suggested causes as hypotheses and test them. |
| Internal audits | Highlight records for investigation. | An unsupported observation becomes a finding. | Have the auditor verify evidence against applicable criteria. |
The pattern is the same in all four: AI speeds up finding or sorting information, and a competent person still makes the decision against the original evidence. Keep evidence of that check, such as the approved document consulted, the original complaints reviewed or the cause actually tested, in the records the process already produces.
An 18-slide briefing in four parts that you can present to process owners, internal auditors or leadership, or use to start a team discussion about where AI already touches your QMS.
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PowerPoint (.pptx) · 18 slides · 854 KB · Edition 1.0, October 2026
The broader revision context: what changed across the whole standard, not only where AI fits.
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View the ISO 9001:2026 Change Guide →How to evaluate risk and potential benefit under Clause 6.1, a useful frame for deciding where AI is worth using.
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View the Clause 6.1 Risks and Opportunities Guide →For planning the wider transition of your QMS to the 2026 edition.
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View the QMS Transition Program →Editable quality manual, procedures and forms for the 2026 edition.
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View ISO 9001:2026 Templates →Where the examples meet your procedures (the presentation maps the same ones): QPS 7.5-01 Control of Documented Information sets the approval, revision and access rules an AI search tool should respect, QPS 10.2-01 Corrective Action covers testing a suggested cause and verifying effectiveness, QPS 6.1-01 Actions to Address Risks helps you assess a new AI use before you rely on it, the QPS 9.2-01 Internal Audit procedure covers evidence-based audit findings, and the QPS 9.3-01 Management Review procedure is where pilot results get reviewed. These are QMS procedures, not a complete AI governance system.
Credit. This page and the presentation were inspired by the article ISO 9001:2026 and AI: What Does the New Era of Digital Quality Mean? (opens in a new tab) by Intelligence Quality. The examples, controls and recommendations are CBG's own work, and the credit doesn't imply endorsement by the article's author.
Scope. Educational guidance on using AI within an existing ISO 9001 quality management system. It is not an ISO publication, doesn't replace the ISO 9001:2026 text, and isn't a complete AI governance framework.