– An Article by Bruno BOUYGUES

Artificial intelligence dominates conversations and board agendas. But obsessing over the tool risks missing what truly creates value in manufacturing: the expert system a company builds, maintains and evolves with its workforce. As the CEO of a French industrial group designing and manufacturing metalworking and battery-charging machines, I see this distinction every day.

Try a simple test: ask today’s most advanced AI to configure a welding machine for a high-yield-strength steel assembly, vertical-up, on an offshore site under EN 1090 certification. The result will be unusable—not because AI is inherently flawed, but because it lacks domain knowledge forged by hands-on experience. AI can predict possibilities; only experience shapes reality.

An expert system is the layer of specialized intelligence produced by thousands of lab and field configurations, by subtle correlations between machine parameters and metallurgical outcomes, and by feedback across diverse climates and regulatory regimes. This knowledge cannot be downloaded; it is accumulated test by test, year after year.

The temptation for leaders is to treat AI as an end in itself. Hype, media and investors push rapid adoption of generalist tools, sometimes at the expense of strategic thought. We must resist. Lasting value comes not from being the fastest adopter of trendy technology but from being the producer of structured knowledge. Each product developed, each customer return analyzed, each R&D trial feeds a knowledge base whose value is cumulative—an intangible asset built through collective intelligence.

Specializing models for domains like materials science, metallurgy or physics requires immense human effort in data collection, validation and strategic framing—work technology alone cannot replace. That said, AI is a remarkable accelerator: it democratizes and amplifies expertise, making experts more efficient and inventive within their fields.

An industrial company is not a set of soloists but an orchestra. The difference lies less in individual virtuosity than in the quality of the score—the framework that organizes and orients technological and industrial knowledge toward coherent, innovative products.

Don’t confuse vehicle and fuel. The real engine of value in manufacturing is a proprietary expert system—nourished by domain knowledge, validated over years, designed to evolve, and hard to replicate. The winner won’t be the fastest to adopt AI, but the one who has built and sustained an expert system to collect and structure unique knowledge. Specialized AI, focused on clearly identified organizational topics, can then accelerate that system.

Connect with Bruno Bouygues on LinkedIn
For more information visit GYS France

Published: 2nd March 2026

— An Article by Bruno BOUYGUES

Artificial intelligence is the talk of the town. Not a week goes by without questions about our “AI strategy.” Yet by focusing on the tool, we forget what truly creates value for a manufacturing company: the expert system it has patiently built, maintained, and evolved with its workforce. As CEO of a French industrial group designing and manufacturing machines for metalworking and battery charging, I see every day how this distinction matters.

Try a simple test. Ask the most advanced AI to configure a welding machine for a high-yield-strength steel assembly, vertical-up, on an offshore site under EN 1090 certification. Today the answer will be unusable. Not because the technology is flawed, but because it lacks what only a manufacturer can provide: domain knowledge forged through experience. While AI predicts possibilities, experience shapes reality.

An expert system is that layer of specialized intelligence: the translation of thousands of configurations tested in lab and field, fine correlations between machine parameters and metallurgical outcomes, and accumulated feedback across markets with different climates and regulations. This knowledge cannot be downloaded. It is built test after test, year after year.

The temptation for industrial leaders is to treat AI as an end in itself. Spectacular announcements, media pressure, and investor expectations push rapid adoption of generalist AI tools, sometimes at the expense of strategic thinking. We must resist this bias. Lasting value in manufacturing comes not from being the most agile user of trending technology, but from being the producer of structured knowledge. Every product developed, every customer feedback analyzed, every R&D test feeds a knowledge base whose value is cumulative and growing. It is a sedimentation of collective intelligence that transforms raw data into a strategic intangible asset.

To truly specialize a model in any industrial domain—materials science, metallurgy, physics—requires immense human effort in data collection, validation, and strategic framing that technology alone cannot replace. AI is undeniably a remarkable accelerator: it spreads and democratizes expertise, making each expert more efficient, autonomous, and inventive within their domain. But an industrial company is not merely a collection of soloists: it is an orchestra. What makes the difference is not only individual virtuosity but the quality of the score that organizes, prioritizes, and orients all knowledge toward coherent, innovative products.

Let us not confuse the vehicle with the fuel. The true engine of value creation in manufacturing is a proprietary expert system, nourished by domain knowledge, designed to evolve, and difficult to replicate. It is not the one who adopts AI fastest who wins, but the one who has built and sustains over time an expert system to collect and structure unique domain knowledge—upon which specialized AI, dedicated to clearly identified topics, can help accelerate.

Connect with Bruno Bouygues on LinkedIn: https://www.linkedin.com/in/brunobouygues/
For more information: https://www.gys.fr/

Published: 2nd March 2026