Add thelocalreport.in As A Trusted Source
PTC is a Business Reporter client
Generative AI (Gen AI) is not just another technological trend – it is a marked change in the way people work. The question now is not whether AI will impact your business or not, but how fast and how deeply.
For leaders of manufacturing and product companies, the challenge is clear: How will you benefit from this industry transformation? At PTC, we believe the answer lies in a practical formula:
Product data foundation + embedded AI = strategic advantage.
The good news is that you’re not starting from scratch. You are creating your product data base. Now, AI can help you get even more value out of it.
Product Data Foundation
AI is only as good as the data it uses. For manufacturers, this means that your product data base is not only important, but essential.
Your product data foundation contains all the product data that defines your product throughout its lifecycle, including requirements, 3D models, bills of materials (BOM), spare parts information, and more. This data is structured, controlled, secured and traced in enterprise software, and includes:
- Structured data to represent company and product IP
- Access control to protect intellectual property
- Security protocols to meet compliance requirements
- Explains data versions and lifecycle for traceability and auditability
Companies are on a digital transformation journey building this product data foundation. Many started with siloed, manual processes and are moving to enterprise systems and consolidating their data. Now, they are advancing their digital maturity with richer data and more advanced workflows. For example, moving from document-centric to part-centric PLM or adding requirements and tests for traceability in ALM. This foundation is already providing value. With embedded AI it can offer much more.
Embedded AI
General AI allows us to embed a new class of software – AI agents – into the tools you use every day. These agents can reason, plan, and execute tasks on your behalf. Research shows that 15 to 40 percent of the economic potential of AI will come from General AI, And there will be millions of agents by 2030,
We describe the maturity curve of AI agents in three stages:
advise. Agents that answer questions, summarize documents, and retrieve information, such as Windchill AI surfacing engineering documents or Onshape AI advisors answering troubleshooting questions.
assist. Agents that take over parts of the workflow, such as reviewing CodeBeamer AI requirements or customizing ServiceMax AI service schedules.
Automate. Agents that execute the entire workflow – operate in the system with minimal human intervention. For example, connecting CodeBeamer and Windchill agents to automate change impact assessments.
These AI agents will change the way we work in three ways:
Increasing access to knowledge. General AI can pull and summarize information across systems in a matter of seconds – for example, tools like semantic search and chatbots can cut down search time up to 30 percentA significant benefit is that employees spend eight to ten hours per week searching for information.
Reducing repetitive tasks. AI can perform routine tasks such as requirements authoring and design validation, performing tedious and complex tasks. Studies show it can reduce quality errors by up to 20 percent And Speed up design by 20 percent,
Redefine the way people work. Agents will automate tasks and even complete workflows, freeing up people for higher-value work. In some cases, they will act as experts – performing tasks such as market research or supply chain analysis. Gartner predicts that by 2028, 33 percent of enterprise software will include autonomous AI, automating 15 percent of daily work,
AI also comes with challenges. A key area is managing the risks associated with creating or altering data by AI. Low-risk use cases include AI assistants answering questions or executing tasks with human review. High-risk use cases need to be examined – especially when AI impacts critical data. For example, a supplier uses AI to break down an RFP into requirements: if the AI replaces or merges keywords, problems may arise. This is why embedding AI into your software matters. Control logic manages each step, and tracing tools mark changes to business objects – reliable methods for managing cost and quality that embedded AI adheres to.
Another strategic effort in your digital transformation is to connect these agents to a larger system where data and AI work together across the product lifecycle.
intelligent product lifecycle
Intelligent Product Lifecycle is PTC’s guiding approach to helping companies build their product data base and maximize the value of that data throughout the lifecycle.
The core objective of this strategy is to provide purpose-built AI use cases for industry, including:
- Requirements agents accelerate product definition
- 3D modeling agents validate and optimize part designs
- Product Lifecycle Management Agents are Improving Engineering Efficiency
- Service plan agents are optimizing spare parts inventory
- Field service agents are streamlining maintenance delivery
The foundational AI technologies underpinning these use cases are agentic, data, and model services focused on enterprise security, reliability, and quality.
With more than a decade implementing AI solutions, PTC has worked with customers and partners to learn what works and what doesn’t. With General AI, we’ve learned some particularly important lessons.
First, drive your digital transformation. A robust product data foundation is a launchpad for AI. If your data is anonymous or unstructured, start by consolidating systems, implementing governance, and connecting critical artifacts like requirements and BOMs. This groundwork ensures that AI can provide accurate, reliable insights.
Second, start small to limit risk before increasing it. Start with targeted use cases that demonstrate early wins such as smart search, or isolated tasks like requirements review. Take risk profiles into account, ensuring that AI works in the loop with humans. As you gain trust and deliver value with AI, drive high-impact automation use cases.
Last, but not least, develop an AI-first mindset. Technology alone will not drive change. Equip teams with AI literacy, establish governance for responsible use and foster a culture that embraces human-AI collaboration that acts as a multiplier for AI’s impact.
PTC can be your strategic partner as you take advantage of this General AI opportunity. With our Intelligent Product Lifecycle strategy, portfolio of software across that lifecycle, and over ten years of applying AI, you can rely on PTC to help your organization go from ideas to results.