What if the most experienced person in your factory leaves tomorrow?
Imagine an engineer with 20 years of experience resigning.
A production line breaks down, a machine starts showing abnormal signs, or a defect that occurred years ago suddenly reappears. The manual may not be enough to explain exactly how to handle the situation.
In these moments, companies often have to “ask the veteran.”
But what happens if that person is no longer at the factory?
The problem is not simply losing one employee. A company may also be losing decades of experience stored in one person’s mind.
I. Where Does Your Factory’s Knowledge Actually Live?
Not all knowledge is documented in SOPs or manuals.
A significant amount of expertise is accumulated through years of hands-on experience:
- How to troubleshoot machine failures.
- Warning signs that appear before a breakdown.
- Root causes of defects.
- How to adjust machines under different circumstances.
- Incidents that happened in the past but were never documented.
- Practical knowledge that only experienced employees know.
This is known as Tacit Knowledge.
The challenge is that tacit knowledge is extremely difficult to transfer and can disappear when experienced employees leave the company.
II. How Much Can AI Replace in Manufacturing?
The answer is: there is no fixed percentage.
AI cannot become an engineer with decades of hands-on experience overnight. However, AI can help companies digitize and make accessible part of the knowledge that previously existed only in people’s minds.
For example, a company can bring together:
Manuals + SOPs + incident reports + maintenance records + quality reports + troubleshooting history
↓
AI Knowledge Base
When an employee asks:
“Machine A is experiencing Error X. Have we encountered a similar case before?”
AI can search the available data and provide similar cases, possible causes, previous solutions, and relevant documents.
AI does not replace engineers. AI makes engineers’ experience more accessible to the entire organization.
III. From “Ask the Veteran” to “Ask AI”
Traditional model:
New employee → Doesn’t know → Asks senior employee → Senior provides guidance
AI-enabled model:
New employee → Asks AI → AI searches knowledge → Suggests possible actions → Human verifies
This can be particularly valuable when companies face:
- Labor shortages.
- Experienced employees approaching retirement.
- Difficulties training new employees.
- Knowledge scattered across multiple systems.
- Long search times when troubleshooting issues.
Of course, decisions related to safety, quality, and actual operations still require human verification and accountability.
IV. Where Should a Factory Start with AI?
Companies do not necessarily need to launch a large-scale AI project from day one.
A better approach may be to start with a specific use case:
Step 1: Collect Data
Manuals, SOPs, incident reports, maintenance records, quality reports, etc.
Step 2: Build an AI Knowledge Base
Allow employees to search for information using natural language.
Step 3: Validate
Let engineers and domain experts verify AI-generated results.
Step 4: Measure
Track improvements in information search time, troubleshooting time, and new employee training.
The solution can then be expanded into AI Agents, Predictive Maintenance, Quality Inspection, or AI × MES/ERP.
Suggested Internal Links:
- AI Agents for Enterprise
- MES × AI
- Manufacturing DX
- AI Quality Inspection
V. BAP Helps Manufacturing Companies Apply AI
BAP Solution Japan provides AI/DX and software development solutions, supporting companies from PoC to development and operation.
Potential applications include:
- Generative AI
- AI Knowledge Search
- AI Agents
- AI × Existing Systems
- AI × OCR
- AI × Data
- AI for Manufacturing
Instead of starting with a complex system, BAP can work with your company to identify the most suitable use case, develop a PoC, and evaluate its effectiveness before scaling.
Internal Links:
→ BAP AI Solutions
→ BAP Manufacturing / DX Solutions
→ AI Development & Consulting
VI. The Important Question Is Not “What Percentage of People Can AI Replace?”
If the most experienced person in your factory leaves tomorrow, ask yourself:
“What percentage of their knowledge will remain within the company?”
If the answer is “very little,” it may be time to start digitizing your organizational knowledge.
AI does not necessarily need to replace the most experienced person in your factory.
AI can help ensure that their knowledge does not leave the factory when they do.
VII. What Challenges in Your Factory Can AI Solve?
BAP helps companies identify the right use cases and implement Generative AI, AI Knowledge Search, AI Agents, and AI/DX solutions, from PoC to real-world deployment.
Talk to BAP to identify the AI use case with the greatest potential to deliver tangible business value for your company.
