Artificial Intelligence (AI) is no longer a distant concept—it’s here, and it’s reshaping industries at an unprecedented pace. For component manufacturers, AI promises efficiency, speed, and cost savings. For years now, we’ve been promised that one day we would be able to get truss designs “at the push of a button” and that day is almost here. Imagine truss designs generated in minutes, optimized for material usage, and ready for production. It sounds like a dream, and in many ways, it will be. But as someone who has spent over 35 years in this business, I believe caution is not just advisable—it’s essential.
The Allure of AI
AI-driven design tools are advancing rapidly. Within a few years, I expect AI will be capable of producing truss designs with 90% accuracy. That’s impressive. But here’s the question: what about the remaining 10%? In our industry, a 10% error rate isn’t just a rounding issue—it can mean structural failures, costly rebuilds, and liability nightmares. If those errors slip through unchecked, the financial and reputational damage could far outweigh the savings AI brings.
I was once told that working in component design was like taking a never-ending math test where any score less than perfect was considered a failure. Of course, mistakes are going to happen, but whereas 90% on a math test in high school would generally be cause for celebration, 90% accuracy as a component designer means you are likely to have a short career. That reality underscores why human oversight remains critical—even as AI becomes more capable.
The Talent Pipeline Problem
Here’s the bigger concern: if AI replaces junior designers today, who will become the senior designers tomorrow? Traditionally, junior designers learn the craft through hands-on experience, gradually developing the judgment and intuition that no algorithm can replicate. It has been proposed that the easiest path to AI integration might include using senior, experienced designers to review work created by AI. But, if we eliminate that entry-level training ground, we risk creating a future where there are no seasoned professionals to review AI-generated work. Ten or twenty years from now, who will catch the mistakes AI inevitably makes?
This isn’t just a theoretical problem—it’s a structural one. Our industry thrives on expertise built over decades. If we disrupt that pipeline, we may find ourselves overly dependent on technology that, while powerful, is not infallible.
The Cost of Overconfidence
Let’s put numbers to this. Suppose AI handles 90% or even 95% of designs flawlessly. That remaining 5%—the errors—could lead to thousands of dollars in material waste, project delays, and even legal exposure. For a component manufacturer operating on tight margins, one major mistake could erase an entire year’s profit. Are we prepared to absorb that risk? Or worse, are we prepared to explain to a client why their structure failed because “the computer said it was okay”?
A Balanced Approach
AI is coming and resisting it entirely would be a mistake. The benefits are real: faster turnaround, reduced labor costs, and enhanced optimization. But adoption must be strategic. Here’s what I recommend:
- Invest in People: Continue hiring and training junior designers. Let them work alongside AI, learning to spot errors and understand design principles. This hybrid approach ensures we maintain a pipeline of experienced professionals.
- Define Review Protocols: Establish rigorous checks for AI-generated designs. Senior designers should remain the final authority, not just a rubber stamp.
- Measure Risk vs. Reward: Calculate the potential cost of errors before fully automating. If the downside outweighs the savings, rethink the strategy.
- Plan for the Long Term: Technology evolves, but human judgment remains irreplaceable. Build a workforce that complements AI, not one that disappears because of it.
The Bottom Line
AI will transform the truss and component business—it’s inevitable. But transformation without foresight can lead to unintended consequences. As manufacturers, we must embrace innovation while safeguarding the expertise that has sustained this industry for decades. The question isn’t whether AI will change our work—it’s whether we’ll manage that change wisely.
How do you feel about the coming adoption of AI in this industry? Is it inevitable? Will it really deliver on the promises we are hearing? Will there be a bust brought on by a shortage of experienced, knowledgeable people over the long term?