AI Destroys the Old Learning Curve

 

 

“Scale drives efficiency -- for almost a century, industrial planners have relied on this simple principle. In 1936 aeronautical engineer Theodore Wright discovered that costs fell in a predictable way every time production doubled. The more you produce, the cheaper things become, in part because the learning cost per unit declines.

 

Artificial intelligence has accelerated this principle.

 

It is rewriting Wright's Law, which assumes that experience follows production: You make mistakes, learn from them and improve.

 

 AI makes it possible for experience to come before production. Simulation can happen millions of times before a single box is shipped. Experience scales almost instantly at no real cost. The learning curve doesn't only steepen. It collapses.

 

That means knowledge that once took decades of human trial and error can emerge in weeks, days, even hours.

 

In a supply chain, this is a profound shift. Decisions about capacity, warehouse space, routing, technology adoption and risk management can be modeled, tested and optimized in advance. The costs of imprecise planning shrink dramatically.

 

AI is breaking Wright's Law because the learning cycle is no longer physical but computational. Distribution models can test, fail and improve millions of times faster than any team of human engineers. Experience can be generated in advance, at scale and at negligible cost.

 

The result is even more powerful when AI combines with robotics, sensors, geospatial intelligence and cloud computing. These technologies multiply one another. Every scanned container, every yard entry and every truck movement becomes a signal that AI systems use to process and price computation. Accuracy rises. Innovation compounds.

 

The missing ingredient is wisdom. Data without context is noise. The future belongs to systems that combine raw computational power with judgment, pattern recognition and domain expertise. Think of these as AI savants -- specialized systems that already exist, and are evolving rapidly. Unlike general consumer AI tools, they blend technical capability with deep industry insight.

 

When AI savants are infused with the experience of seasoned professionals, innovation cycles collapse even further. They don't simply iterate faster. They skip steps. They test smarter. They pivot instantly. Discovery accelerates at light speed.

 

The implications for logistics are extraordinary. Supply chains may stop behaving like managed systems and start functioning more like adaptive organisms. AI agents will negotiate, reroute and optimize flows of goods in real time. Traditional ownership models, fleets, warehouses and even labor could be replaced by dynamic orchestration of perfectly used assets.

 

Winners won't be the companies that move the most freight. Winners will be those that control the richest data streams, that build and deploy AI savants, and that embrace the new reality rather than clinging to outdated assumptions about scale.

 

This transformation is thrilling and unsettling at the same time. Entire categories of jobs may disappear far more quickly than in past cycles of creative destruction. Nations and corporations that dominate AI may end up controlling not only knowledge but the arteries of global trade. Hyperoptimized networks could become fragile black boxes, highly efficient but brittle when confronted by shocks or adversarial attacks. The innovation cycle is steepening. New products and services will rise and fall with greater frequency, and companies that can adapt quickly will expand their workforces to satisfy demand.

 

For all its dangers, this elimination of entire categories of jobs may produce a flourishing of entrepreneurial activity. We may see nimble companies in numbers never seen before, each rising quickly, taking advantage of the low cost of building businesses and the distributed access to tools, and sunsetting as fast if they don't solve problems for customers.

 

This new golden age of logistics entrepreneurship will unveil solutions to problems we may not even know exist. Wright's Law still matters, but AI has broken it. Knowledge can materialize instantly. Innovation and disruption will arrive in shock waves, not cycles. The challenge will be not building the tools but surviving the pace of their consequences.

 

Leaders who adapt to this new world will shape the future of commerce. Those who don't will be replaced.

 

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Mr. Rosenthal is CEO and co-founder of ESP Logistics Technology. Mr. Zuckerman is a senior partner and managing director at the Boston Consulting Group.” [1]

 

1. AI Destroys the Old Learning Curve. Rosenthal, Jonathan; Zuckerman, Neal.  Wall Street Journal, Eastern edition; New York, N.Y.. 23 Oct 2025: A17.