The challenge of applying Artificial Intelligence to Life Cycle Assessment without losing technical consistency
In recent years, Life Cycle Assessment (LCA) has entered an unexpected phase driven by Artificial Intelligence. Tools capable of processing inventories in seconds and generating impeccable graphics have become accessible, allowing many companies to get quick answers without needing to master the methodology.
AI has democratized calculation and removed barriers. However, after the initial enthusiasm, an inevitable question arises: is what the machine delivers truly reliable?
The risk of driving an F1 with a standard car licence
AI has an undeniable virtue: it crunches numbers at astonishing speed and remains unfazed by constant inventory changes. But there is a critical difference between calculating and understanding.
Using AI to perform an LCA without a solid technical foundation is like getting into a Formula 1 car with only a basic driving license. Both are vehicles, both have an engine and a steering wheel, but the power of an F1 in inexperienced hands is, quite simply, dangerous. AI does not “raise an eyebrow” at inconsistent data or detect if you are mixing technically incompatible processes; it simply processes, returns results, and moves on.
An LCA is not a flat mathematical exercise, but an interpretation of a complex system in which a basic error can completely invalidate a sustainability strategy or an official verification.
The value of the expert: the driver behind the technology
This is where the technician contributes what cannot be captured in an algorithm: judgment, context, and intuition. An expert thinks before calculating; they know when data is an “optimistic wish” and which processes can compromise the rigor of a study.
Far from being a threat, AI should be an ally that frees us from mechanical work and allows us to explore scenarios quickly. But experience still outweighs any algorithm because, in the end, LCA is a story that must be read and defended before third parties.
Our vision at Solid Forest: a project towards the future
At Solid Forest, we are an active part of this evolution, but from the technical responsibility that defines us. Therefore, we are currently developing a strategic project to study and incorporate artificial intelligence capabilities into our Air.e LCA software.
We are not seeking a race for blind automation, but rather designing a tool where AI supports the technician, facilitating more intuitive modeling and resolving mechanical tasks without the professional ever losing control or judgment. Our goal is that, in the near future, technology will accompany the expert so that they can focus their time on what truly adds value: analyzing, deciding, and improving.
Conclusion
AI moves the boat, but the technician steers. Combining technology and human judgment is the only way for the future of LCA to be not only more rapid and effective, but above all truthful, real, and purposeful.
Originally published on Solid Forest’s Trends blog
