Incumbents are racing to add AI to their organizations. The bigger challenge is competing with businesses designed around AI from day one.

For many established companies, the AI conversation starts with tools: Where can we deploy AI pilots? What processes can we automate? How much time or money can we save?

Meanwhile, a new generation of companies is starting with a different question: If we use AI from the ground up, how would we design this business?

Incumbents are largely using AI to improve organizations built for an earlier era. AI-native competitors can rethink the organization itself: its workflows, staffing, management layers, products, and cost structure.

An established company might use AI to make an existing process more efficient. An AI-native company can ask whether that process, or the organizational structure around it, needs to exist at all.

This raises a much harder question than how to adopt AI: How do you keep running the business that works today while simultaneously building the one that might replace it tomorrow?

For more than two centuries, companies have been designed around assumptions inherited from the industrial age.

As organizations grow, they add specialization, management layers, processes, controls, budgets, and systems intended to make performance more predictable. Successful companies become very good at serving known customers, forecasting demand, improving efficiency, and scaling what already works.

AI does not suddenly make those capabilities obsolete. But it does make some of the assumptions behind them worth questioning.

A startup built today can assume from the beginning that significant amounts of knowledge work can be automated or augmented.

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