AI-powered PLM & Compliance
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Artificial Intelligence (AI) in PLM
Artificial Intelligence (AI) technology can radically enhance the power of data-driven product lifecycle management (PLM), turbo-charging process automation and product information tracking to expedite time to market. AI in PLM is beginning to enhance every output of new product development and product management.
AI in PLM Software
Examples of AI in PLM software include applications of predictive AI, which can forecast potential risks and errors, to identify problems before they begin in the product development process. AI in PLM can recommend the best ingredients or packaging components to improve products and reduce costs, enabling quicker decision-making, while also making it quicker and easier to search for information to meet consumer, market and regulatory requirements.
At Trace One, we’ve been hearing from our customers that they’re already seeing the power of generative AI for marketing teams. Now, they’re excited about generative AI in PLM for R&D teams and quality managers. They’re looking forward to how AI can increase efficiency and maximize return on investment (ROI) when entering and extracting information for product development and management.
PLM software has reshaped new product development and introduction (NPDI). for the food & beverage, cosmetics & personal care, and specialty chemical industries. Trace One PLM solutions empower brands and suppliers across the entire supply chain to work together directly on shared product data. PLM software also helps businesses navigate global regulatory requirements, which have increased over the past 30 years. As market pressures require NPDI to be timely and cost-effective, continued enhancements in PLM help businesses launch new products with the confidence to know they’re viable, feasible, and proactively planned.
Recent technological advancements in PLM include:
• Transitioning from on-premise to the cloud providers, maintaining the security of an enterprise cloud solution, and the speed, flexibility, cost-efficiency, and easy integration of software as a service (SaaS).
• The integration of regulatory compliance regulation data helped customers to make the right decisions for their products as they manage ongoing compliance checks, monitor changing laws, and ensure products remain compliant and competitive in every market.
• Integration with legacy systems synchronizes repositories across products, suppliers, and brands for seamless product data sharing.
• The evolution of process PLMs from discrete PLMs facilitates collaboration without spreadsheet clutter and sifting through email threads. Trace One has created a single platform that both suppliers and retailers use.
• Over time, Trace One created solutions that go beyond PLM: e-sourcing, artwork management, etc. All linked to the same product and supplier information with Master Data and sharable across several solutions.
As PLM software has evolved, different forms of data have become more inter-connected, and the amount of data has grown significantly, as has the focus on data quality. Large, high-quality data sources, and many process steps to optimize, means that there are many PLM AI use cases that can have big impacts on your NPDI development process.
Key Impacts of AI in Product Lifecycle Management
AI promises to enhance efficiency, accuracy, and agility throughout the product lifecycle.
When considering the key stages of New Product Development and Introduction (NPDI), AI in PLM has the following impact:
Automate repetitive & time-consuming tasks such as data capture or document management.
Improve efficiency and reduce manual tasks.
Interact with Trace One solutions using everyday language. Make it easier for non-technical team members to query the system, retrieve information, and perform actions.
Simplify data management, text/image comparison and proofreading.
Ensure regulatory compliance, security, and brand image.
Facilitate data mapping and integration between different systems.
Expedite time to market, and secure customer information.
Improve decision making process through suggestions (raw material, formulation).
Optimize margins and position your organization to quickly respond to consumer demand.
AI Examples in Trace One PLM
At Trace One, we leverage AI in PLM to bring even more value into our solutions and take end-to-end product development to the next level.
With AI in PLM, Trace One gives the power to food & beverage, cosmetics & personal care, and specialty chemical brands for a better and faster product development process so they can:
• Focus on added-value activities
• Create innovations
• Bring products to market more rapidly in today's competitive market landscape
With the 2026 release, Trace One launched Trace One Copilot – integrated, context-aware intelligence embedded directly within the Trace One solutions platform, which consists of proactive agents and features that summarize, synthesize, and drive tasks end-to-end.
Current State: AI in Trace One PLM
We’ve partnered with Google Vertex AI and Microsoft Azure OpenAI to empower AI in PLM.
We selected these trusted partners to provide cutting-edge technology and consistent updates to ensure a top-tier customer experience. We know that your proprietary data and its safety are crucial to your business, and so we are working with cloud providers who are dedicated to safely and securely developing AI solutions for enterprise.