AI (artificial intelligence) in a manufacturing company
Until a few years ago, artificial intelligence in the manufacturing industry was mainly associated with the implementation of processes – robots, automation, and algorithms controlling production lines. Currently, AI in manufacturing companies also covers areas related to administration and human resource management. AI assistants created for the noSilo application facilitate daily access to knowledge and decision-making, as well as supporting competence analysis and employee onboarding. AI in production reduces decision-making time, limits information chaos, and gives people exactly the information they need – while ensuring data security.
What is AI in a modern manufacturing plant?
Artificial intelligence in manufacturing plants is commonly used in the operational area – it includes, among other things, real-time machine data analysis, failure prediction, production schedule optimization, quality control, as well as resource and supply chain management. Algorithms learn from historical data, allowing anomalies to be detected instantly and helping to respond before downtime or serious errors occur.
Modern companies are going a step further and using AI in production to streamline areas related to HR and administration – areas that until now have relied mainly on manual data analysis and managerial experience. Artificial intelligence supports tasks such as competency management, employee development planning, onboarding, and easy knowledge sharing. AI assistants available in the noSilo application analyze the data collected in the system to generate responses to user queries, eliminating the need for time-consuming searches through documents, reports, and software modules. Employees ask questions in a chat window on their desktop and receive a ready-made, organized, and best-matched response in seconds.
At noSilo, we have released two specialized solutions based on artificial intelligence. The manager assistant, an AI assistant for production managers, effectively supports competency analysis and employee succession planning. The knowledge assistant, on the other hand, provides users with quick access to information contained in the knowledge base. How exactly do AI assistants work?
Assistant manager – how does AI support leaders in planning development?
In a manufacturing environment, development planning applies to both individual employees and teams. Managers constantly make decisions that affect the functioning of the entire plant. What actions should be taken to maximize team flexibility and replaceability? Which employee should be prepared for promotion? Answering these questions requires time-consuming analyses of competency matrices and job description documents – but with AI assistants, these time-consuming analyses can be reduced to the few seconds it takes to ask a question and generate an answer. What role does an AI assistant play in competency management and development planning?
Automatic analysis of competency gaps
The AI assistant can instantly analyze competency gaps based on data contained in noSilo competency matrices. How does it work? The manager enters a query or command, for example, “Prepare an analysis of the current competency status of team/employee X. Identify areas for improvement and missing training.” Such an analysis can be carried out for both an individual and the entire team. In response, the manager receives clear information about competency gaps and areas requiring attention, broken down by priority. At the top of the list, the assistant will indicate the key areas that need to be focused on first. Job matrices cover hard and soft competencies, so the most important skills necessary for the proper performance of tasks (e.g., operating a specific machine) will have a different priority than competencies related to teamwork.
Career path and succession planning in seconds
The assistant manager also provides invaluable support in planning career paths and promotions for employees. In order to conduct such an analysis in a factual manner, it is necessary to review a large amount of documentation. The manager must know the answers to the following questions:
- What competencies are required for a given position?
- What competencies does the employee selected for promotion already have, and which ones do they still need to acquire?
- How long will it take to acquire all the competencies necessary for succession?
The assistant manager analyzes this information in a matter of seconds. They process data from operational documents to check the requirements for the selected position and then compare them with the current skill level of a specific employee based on the information contained in the competency matrices. What’s more, based on historical data, the assistant is able to estimate how long it takes on average to acquire a selected competency at the plant, so the manager knows when to expect the employee to be fully ready for promotion.
Knowledge assistant – no more searching for documentation in binders
In manufacturing plants, knowledge is often scattered—machine operating manuals, SOPs, health and safety procedures, and HR regulations are hidden away in binders that rarely anyone looks at. The noSilo platform allows you to gather all your knowledge in one central place, namely the Knowledge Base available in the application. But that’s not all! The knowledge assistant makes it even easier to access information by eliminating the need to manually search through documents in the system. Just type in a question, and the assistant will instantly search the knowledge resources assigned to the user’s role and generate the most relevant answer based on that, including specific sources.
This solution also provides invaluable support in onboarding new employees. AI in employee onboarding allows them to find their feet in the production environment more quickly and independently obtain answers to questions about procedures, machine operation, or health and safety rules.
“Chatting” with company documentation
Let’s imagine a situation in a production hall: an employee returns after a long break and is unsure what start-up parameters to set on the machine. In such a situation, there are several solutions.
- Option 1. The employee can ask a colleague at the next desk for advice. However, leaving their desk will result in a temporary increase in unproductive time – both for the employee who has doubts and for the employee who will have to spend time dispelling their colleague’s doubts.
- Option 2. The employee can ask their supervisor for advice. The supervisor’s workstation is usually located a little further away, so in this case, the need to search for information also results in an increase in unproductive time. In addition, the supervisor has to take time away from their current duties.
- Option 3. The employee can search the Knowledge Base themselves. At their workstation, the employee will search for the relevant document in the application, read its content, and obtain information about the preferred settings.
- Option 4. The employee can enter a query for the Knowledge Assistant. A few seconds to enter the command, a few seconds for the response – that’s all it takes to remember how to operate the machine and prepare it for work.
This is what “chatting” with company documentation is all about – instead of searching for information in multiple files or involving other employees and supervisors, the user asks a single question and immediately receives a precise answer based on applicable documents. The knowledge assistant reduces the time needed to obtain information to a minimum, and the generated answer is always consistent with current procedures. The assistant also provides links to specific sources in the Knowledge Base, so that employees can learn the full context of the answer if necessary.
Benefits of implementing AI through the noSilo platform
The greatest value of AI in manufacturing is the acceleration of daily work. According to KPMG’s “Intelligent Manufacturing” report, as many as 96% of industrial companies report improved operational efficiency after implementing AI, and 42% of respondents indicate that the greatest improvement is faster data-driven decision making.
The most important benefits of implementing AI through the noSilo platform include:
Data security at noSilo
The collection and processing of data by AI in the field of HR raises certain concerns regarding data security and cyber threats. AI assistants at noSilo operate in full compliance with applicable security requirements.
The lack of internet access guarantees that responses are generated solely on the basis of data provided by the organization and limits the risk of cyberattacks. If it is not possible to generate an accurate response based on the organization’s data, the employee will receive appropriate feedback.
What’s more, the assistant only sees the information base available to the logged-in user, which means that people in different positions will receive a response based solely on the information they are authorized to access. Line employees will have a different scope of knowledge, managers will have a different one, and directors will have yet another. It is not possible to bypass roles or permissions – the information processed is fully controlled.
Artificial intelligence in a manufacturing company provides effective support to line employees and managers in quickly accessing information. Accurate analyses generated on the basis of organizational data facilitate competence management and team development planning. At the same time, working on the basis of user roles and permissions ensures complete security of the information being processed.
Bibliografia:
https://www.sciencedirect.com/science/article/pii/S2772662223000899;
https://www.ibm.com/think/topics/ai-in-manufacturing;
https://assets.kpmg.com/content/dam/kpmgsites/xx/pdf/2025/05/intelligent-manufacturing-report.pdf.
She has many years of experience in the manufacturing environment, gained both in team management and in the coordination of internal processes. Her practical experience in operational and managerial work has given her a deep understanding of the challenges faced by managers and production employees – from work standardization and communication to competence development.
This experience forms the foundation on which she bases her current expert activity. In her articles, she shows how digital solutions and modern management methods can realistically support the daily work of production plants, making processes more transparent, orderly, and effective.
