Artificial Intelligence in a Manufacturing SME: Our Field Experience
agosto 05, 2026
Artificial intelligence in manufacturing SMEs has been one of the most discussed topics in recent months. It's often discussed in very general terms, alternating between enthusiasm and fear, as if there were only two possible scenarios: on the one hand, those who envision fully automated factories, on the other, those who fear that AI will eventually replace people.
Our experience, at least for now, is very different.
In the day-to-day work of a company operating in the precision mechanics sector, artificial intelligence hasn't replaced designers, technologists, or quality control technicians. It's simply begun to help us work better. And, above all, faster.
AI does not replace skills
When talking about artificial intelligence, it's easy to imagine tools capable of making autonomous decisions. In the reality of a manufacturing SME, the value is often much more tangible. We don't use AI to design a gear instead of our engineers. We don't ask it to define a manufacturing cycle, and we don't entrust a linguistic model with the responsibility of choosing a material or validating a design. These remain activities that require experience, knowledge of the production process, and the ability to assess context. Artificial intelligence, on the other hand, intervenes in all those activities that absorb time without representing the true added value of our work. And this is precisely where we have begun to see the most interesting benefits.
Where we use artificial intelligence today
Over the past few months, we've experimented with several practical applications. Some have become an integral part of our daily work. AI supports us, for example, in the technical development of new components, helping us organize information, compare solutions, and accelerate preliminary analysis activities. We also use it to quickly compare technical standards, customer specifications, and design documentation, identifying differences, areas of concern, and requirements that warrant further investigation.
At the same time, we're developing internal applications built on our company data. These aren't generic tools, but solutions designed to address our organization's very specific needs. Artificial intelligence has also become a valuable tool in preparing commercial offers, presentations, technical documentation, and client meetings. Technical translations and communication with international suppliers and clients are also tasks we can now complete more quickly, while still maintaining a final human review.
The real advantage is not artificial intelligence
The more we use these tools, the more I'm convinced of one thing. Competitive advantage doesn't lie in having access to artificial intelligence. Today, that technology is available to virtually anyone. The real difference comes from how it's used. What matters is the quality of the questions, the ability to contextualize the problem, and above all, the expertise needed to critically interpret the answers.
A model can compare hundreds of pages of technical documentation in a matter of seconds. It can summarize information, highlight differences, suggest connections. But it doesn't know the manufacturing history of a component. It doesn't know whether a given tolerance can actually be produced with the available process. It can't determine whether a certain processing sequence will increase the risk of deformation after heat treatment. And it can't decide whether a customer request should be discussed before even starting production.
These assessments continue to require technical expertise and direct knowledge of the process.
The real challenge concerns companies
For this reason, I don't believe the future will be a competition between people and artificial intelligence. Rather, we believe we will witness an increasingly marked gap between companies that integrate these tools into their processes and those that continue to consider them simply a chatbot to ask a few questions. Integrating AI means rethinking the way we work, identifying repetitive tasks, automating what doesn't create value, freeing up time for technical analysis, customer engagement, product development, and strategic decisions.
In other words, it means using technology to enhance people's skills, not replace them.
A path still evolving
In our case, too, there's no definitive model: we're still in a phase of continuous experimentation. Every week, we discover a new potential use, develop a new tool, modify a workflow. Some ideas produce results that exceed expectations, others prove less effective than we imagined.
And that's absolutely normal: we're learning.
Like most manufacturing companies that have decided to seriously address this change, we're probably learning . The important thing is to maintain a pragmatic approach. Measure the results, understand where AI truly creates value and where its contribution remains limited.
Sharing experiences is worth more than predictions
When it comes to artificial intelligence, we read daily predictions about how the world of work will change. These are interesting insights, but we believe it's even more useful today to share concrete experiences. Knowing where a company has managed to save time, which applications have truly worked, and which tools have proven less effective than expected.
Whether customized systems have been developed based on company data or whether standard platforms are primarily used. These experiences can help other companies understand how to integrate artificial intelligence into their processes in a conscious and sustainable way.
Artificial intelligence isn't a universal solution; it doesn't replace technical skills or eliminate the need for experience, but it can become an extremely effective tool for speeding up repetitive tasks, organizing information, and supporting people's daily work.
For more information on solutions for the mechanical transmission and gear industry, contact GSI Ingranaggi.
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