PLM and AI: Smarter product development

Artificial intelligence (AI) has entered the fashion conversation, and it is reshaping how we think about product development. Within PLM software, AI has the potential to take the routine out of daily work and replace it with insight.

For fashion brands, this means less time searching for data and more time creating. At Delogue, we believe that the future of AI in PLM is not about replacing people, but about empowering them, helping creative teams spend more time designing and less time managing files, communication, and spreadsheets.

Where AI meets PLM today

Right now, our first step into AI PLM technology is the Delogue AI Knowledge Base, a conversational assistant trained on our tutorials, workflows, and customer guidance. When a user needs help, the AI can instantly answer questions, explain processes, or guide them through features directly inside the platform. It uses elements of our own PLM language model and retrieval learning to understand context and give precise, friendly replies.

This first layer of AI creates a more seamless experience for users, reducing time spent on support and allowing product developers to keep their focus inside their product lifecycle management system. It is small but powerful,  and it marks the beginning of how artificial intelligence will enhance everyday PLM work.

At Delogue, we believe AI should add real value, not just a headline feature. That’s why we take time to train, test, and refine before releasing anything new. Our goal is not to have “AI” for the sake of it, but to build AI agents and models that genuinely work and make life easier for product developers. The next step is where things get truly exciting, exploring how machine learning and automation in PLM can transform data, communication, and creativity across the entire product lifecycle.

PLM and Machine learning for smarter data management

The next steps in PLM machine learning are not only about reading documents or pulling out details, but about helping brands structure the information they already have. Fashion companies work with countless partners, and every key account asks for data in a slightly different format. This is where AI agents inside a PLM system can make a real difference. Instead of teams spending hours reorganising product data for each export, an AI can learn the logic behind these formats and prepare the structure automatically.

With the right training, PLM automation can understand how materials, colours, sizes, suppliers, and timelines are organised across the platform and reshape this information into whatever layout a partner needs. It becomes a collaborative assistant that understands your data model and supports you when new requirements emerge.

This type of training still takes time, because AI models must learn industry language, abbreviations, and the way fashion teams actually work. But once trained, the outcome is a smoother, more consistent flow of information across the product lifecycle. Instead of chasing files or reformatting spreadsheets, teams can rely on an AI agent that helps them deliver accurate, structured data in minutes, not days.

Language models and communication in PLM

The fashion industry thrives on collaboration, yet communication often slows product development. Here, PLM language models can become real partners. AI can support translation between teams and suppliers, summarise long threads of feedback, or even draft polite, accurate replies based on existing communication.

When combined with training PLM automation, AI can learn how teams communicate and suggest better ways to phrase, tag, or categorise messages. It can find relevant documents, link to similar styles, or pull up past discussions. This does not replace creativity or human tone,  it simply clears the way for clearer, faster dialogue.

From support to prediction: the next frontier

As AI in PLM continues to evolve, machine learning will move from assisting to anticipating. Once trained on enough data, AI could identify patterns in delays, predict bottlenecks in sampling, or suggest more sustainable sourcing options. By analysing historical product lifecycle management data, it could even help brands refine forecasting and reduce waste.

These predictive tools will take time to mature, and they must be trained carefully to ensure that insights are accurate and ethical. But their potential is clear: fashion teams will be able to plan, design, and deliver with more confidence than ever before.

A human-centred future for AI PLM

For Delogue, AI is a tool to simplify, not complicate. The strength of AI PLM software lies in how it complements human creativity and judgement. Whether through intelligent guidance like the Delogue AI Knowledge Base or through future machine learning and automation in PLM, our focus remains on making technology work for people. We believe it is essential to always have a human in the loop, ensuring that AI supports decisions rather than replacing them.

AI is not a shortcut, it is a companion that learns, improves, and helps teams navigate their daily work with less friction and more flow. As we continue to train our systems and integrate new PLM AI solutions, one thing remains unchanged: fashion’s creativity should always lead the process, and technology should follow.