AI in Manufacturing:
Faster Answers and Less Dependence on Experts

Manufacturers work with complex products and countless technical variations. It’s only natural that colleagues, partners, and customers regularly ask highly specific or technical questions. In many cases, this critical product knowledge is not fully documented in systems — it also lives in the minds of a select group of specialists. These experts are not always available, and when they retire or leave the company, valuable knowledge can disappear with them.

As a result, manufacturers often face long response times, incomplete product information, and increasing pressure on internal experts. To remain competitive, companies need to reduce this dependency. AI offers a solution by capturing fragmented expert knowledge, preserving it, and making it instantly accessible across the organization.

The Core Challenge: Fragmented Product Knowledge

Product information is usually spread across multiple sources: PDFs, technical documentation, internal systems, and the knowledge of experienced colleagues.

When a question comes in, employees often have to manually collect and combine information from different places. This makes the process slow and heavily dependent on people who happen to know the answer.

At the same time, many questions are repetitive. Common examples include:
- “Which component do I need?”
- “How should this part be applied?”
- “Is there a replacement product available?”

How AI Changes This: Instant Answers to Product Questions

AI makes it possible to answer these questions instantly by using all available information sources. Instead of searching through documents or asking colleagues, employees receive direct and concrete answers.

This creates several benefits:
- Faster response times
- Less dependence on experts
- Fewer interruptions during daily work
- More consistent and reliable answers

As a result, employees can work more independently and respond faster in their day-to-day activities.

Reducing Pressure on Experts

Organizations such as Holmatro and Dekker Zevenhuizen face these exact challenges.

Holmatro, a specialist in hydraulic technology, handles complex technical questions from dealers around the world every day. Dekker Zevenhuizen, a supplier of custom kitchen and bathroom countertops, deals with technical questions related to highly customized production processes.

Both companies experience recurring questions where answers are manually gathered from documentation or expert knowledge. With AI, these questions can be answered instantly, enabling employees to work faster, making product knowledge broadly available, and significantly reducing pressure on internal experts.

Instead of repeatedly answering the same questions, experts can focus on where they create the most value:
- Product development
- Innovation
- Strategic decision-making

The impact on the business world is enormous. Why pay millions for bulky, standardized SaaS packages when a small team of AI engineers can build custom systems? We are already seeing large companies move away from expensive software vendors to develop their own systems.

Software is no longer an expensive “product” you purchase, but a flexible “tool” you create yourself.

Supporting Sales and Service Teams

AI also plays an important role in sales and service processes. These teams need to respond quickly and accurately to customer questions. Where the process previously relied heavily on searching and asking around internally, AI provides direct access to knowledge.

With AI, teams can:
- Quickly find the right product or alternative
- Compare products based on specifications
- Better respond to customer needs

This improves the quality of advice while accelerating the sales process.

Conclusion

The biggest opportunity for manufacturers lies in speeding up processes and unlocking existing knowledge. By implementing AI, product questions can be answered instantly while significantly reducing pressure on experts.

Companies like Holmatro and Dekker demonstrate that success is not about doing more work, but about working faster and smarter with the knowledge already available. This makes organizations more efficient, consistent, and scalable.

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