Artificial intelligence (AI) is transforming how manufacturers manage product development, engineering changes, quality processes, regulatory compliance, and more. When AI integrates with proven product lifecycle management (PLM) and quality management systems (QMS) solutions, it can help teams find information faster, understand complex records, analyze changes, and make more informed decisions.
The value of AI depends on the information it is based on. AI can help teams search, analyze, summarize, and interpret large volumes of product and quality information. Common applications include:
Additionally, AI can streamline routine work and identify potential issues, helping ensure that established workflows remain controlled, traceable, and accountable.
AI is only as useful as the information it can access. Outdated, incomplete, or disconnected product information can lead to unreliable results. For AI to deliver useful outcomes, organizations need a reliable foundation of accurate, connected, and traceable information. Connected PLM and QMS solutions help provide that foundation by bringing product and quality information together in a controlled environment. This enables AI to work with more reliable information and helps teams, partners, and suppliers work from a trusted source.
AI can help teams understand engineering changes, locate related product information, summarize updates, and evaluate potential impacts. For quality teams, AI can help analyze corrective and preventive actions (CAPAs), nonconformances, complaints, audits, and other quality records.
When quality information is connected to the product record, teams gain greater context to understand which parts, BOMs, documents, suppliers, or changes may be associated with an issue.
AI can help quality teams search historical records, summarize related quality events, identify relevant product information, and uncover patterns in CAPA and root cause investigations.
AI supports these investigations by reducing manual research, while established QMS processes provide controls for reviewing, approving, implementing, and verifying corrective actions.
AI can help regulated manufacturers find information, review controlled records, understand product changes, and prepare for audits and regulatory activities.
For medical device companies, AI can make it easier to work with product, quality, and compliance information, while established PLM and QMS processes maintain documentation, traceability, approvals, and audit trails.
Successful AI adoption starts with trusted product information and high-quality data. A connected PLM and QMS environment provides this foundation by maintaining accurate, controlled, and traceable information across the product lifecycle.
With trusted data in place, manufacturers can use AI to find answers faster, understand complex information, improve decision-making, and spend less time searching through disconnected records.
AI in PLM helps teams find, analyze, compare, and understand trusted product data, improving engineering changes, document reviews, and decision-making.
Trusted PLM and QMS data gives AI structured, connected product information to improve search, analysis, change reviews, and quality investigations.
Generative AI helps product teams search information, summarize documents, compare revisions, review engineering changes, and make better-informed product development decisions.
