This principle applies particularly in sealing technology: if service reports on seal inspections or the history of replacement parts are not recorded uniformly, AI remains blind. For example, a company that regularly maintains sealing systems for customers can only provide proactive maintenance advice if all previous assignments are fully documented digitally.
Typical digital construction sites in service
The hurdles are similar in many industrial companies:
- Data chaos and lack of structure
Information is scattered and cannot be searched centrally. Some of it is stored in the ERP system, some in Excel lists, and some in individual emails. For AI, this means no access and no reliability.
Experienced service technicians have valuable specialist knowledge, but this is rarely documented centrally. In sealing technology, often only one colleague knows how certain high-pressure seals are installed or tested. When this employee retires, there is a risk of knowledge loss.
Service reports are still written by hand, then typed up later in the office and transferred to the system. Every media break costs time, carries the risk of errors, and renders data unusable for real-time analysis.
- Established isolated applications
Historically developed individual solutions—such as a separate tool for resource planning, a local Access database for spare parts, or WhatsApp communication with customers—are often not networked. Information is lost or must be maintained twice.
Service calls are often coordinated by phone, data is forwarded by email, and error reports are manually transferred to Excel. Such processes are error-prone, slow, and prevent proactive work.
Media discontinuity and a lack of transparency are particularly risky in sealing technology, with its safety-critical applications: in the worst case, unclear documentation can lead to incorrect decisions regarding maintenance or spare parts provision.
Roadmap: Step by step towards an AI-supported organization
The good news is that all these problems can be solved—with a structured, step-by-step roadmap.
- Inventory and goal definition
The first step is analysis: Which processes are digital, where are there media breaks, and what goals does the company want to achieve? Should the response time to service requests be halved, the error rate reduced, or spare parts availability made more transparent?
Example: A manufacturer of sealing systems decides that customers should have access to the maintenance history of their systems and the current spare parts inventory at any time via a portal.
- Consolidate the database
All information—from customer master data and asset histories to spare parts inventories—must be recorded centrally. Mobile apps can enable technicians to enter service reports digitally directly on site, including photos and timestamps. This creates consistent, searchable data that can later be used for AI.
- Digitize core processes
Resource planning, ticket management, and knowledge documentation are particularly important. Digital resource planning can automatically match available technicians with orders. Mobile applications enable reports to be recorded in a structured manner on site. This speeds up billing, reduces errors, and improves data quality.
- Involve employees and build skills
The focus remains on people. Service technicians need to feel the benefits of digitalization: less paperwork, faster access to relevant information, and clearer processes. Training courses, feedback sessions, and practical introductory scenarios create acceptance.
- Launch initial AI pilot projects
Once the database and processes are established, the first AI applications can be tested:
- Chatbots that pre-sort inquiries
- Intelligent knowledge databases that assist technicians with fault diagnosis.
- Algorithms that predict seal failure based on operating data.
It is important to define measurable success criteria, such as: “20% fewer unplanned downtimes” or “30% faster response times.”
- Make successes visible
Early success stories boost motivation. If the average processing time is reduced from 8 to 5 hours, this should be communicated internally and externally.
- Establish continuous improvement
Digitalization is not a project, but an ongoing process. Systems must be adapted to changing requirements. Feedback loops and open communication are crucial.
