For most of the past two centuries, the economics of business rewarded scale. The bigger the factory, distribution network, workforce or balance sheet, the harder a company was to challenge. Size brought purchasing power, access to capital, armies of specialists and the ability to spread costs across millions of customers.
Modern corporations were built around a simple assumption: successful companies become big companies.
This is now changing, and fast, driven by the power of artificial intelligence, global connectivity and robotics; and it does not apply to firms only, it is a new paradigm in life, starting from national power.
Thomas Friedman recently described in The New York Times what he calls the “new physics of power” reflecting on advances in warfare and how relatively small powers can use drones, software, precision weapons and asymmetric tactics to impose extraordinary costs on much larger powers. We also see smaller economies innovating and punching above their weight on the global economic scene.
There is also something similar, and arguably more exciting for us as individuals, happening in business. Technology has been lowering the cost of challenging incumbents for decades, but AI will be a powerful way of accelerating the process to the point where we need to rethink what corporate scale actually means.
There were clues long before ChatGPT entered our lives in 2022. When Facebook agreed to buy Instagram for $1 billion in 2012, Instagram employed just 13 people. In the same year, in the same business sector of photographs and memories, Kodak declared bankruptcy, with more than 150,000 employees. Two years later, Facebook agreed to acquire WhatsApp in a deal worth $19 billion, when the messaging service had only 55 employees. WhatsApp was already serving more than 450 million monthly users and adding more than one million registered users a day. Small companies could clearly achieve extraordinary reach, but there were hurdles to build and operate a global business. Now AI is beginning to remove that constraint, too.
Consider Lovable, the Swedish company that allows people to create software using natural language. It reached $100 million in annual recurring revenue only eight months after launch, with 45 full-time employees. Gamma, which uses AI to create presentations and websites, reached $100 million ARR profitably with about 50 people, having raised only $23 million initially. Cursor, the AI coding company, crossed $100 million in recurring revenue in early last year while pursuing explicitly what it calls a “small, talent-dense” model.
While these are private company figures and should be treated with some caution, the pattern is becoming difficult to dismiss. What AI is changing is not simply productivity; it is the minimum efficient size of the firm. A small team can now draw on computing infrastructure it does not own, distribute globally through platforms it did not build and increasingly use AI to write code, produce marketing, analyse customers, translate material, answer queries and perform administrative work. Capabilities that once required departments can increasingly be bought by the token.
This changes the competitive equation. A large incumbent still possesses formidable advantages – capital, customers, data, brands and relationships – but it must also carry its accumulated organisational weight: legacy systems, management layers, committees, processes and thousands of people whose activities must be co-ordinated. A challenger does not need to replicate all of this. It can concentrate a small number of talented people, equip them with increasingly capable AI agents and attack one profitable product, customer segment or inefficiency.
That is the corporate equivalent of asymmetric warfare where the incumbent has to defend the whole castle; the challenger only needs to find one gate.
The logical extreme is the much-discussed one-person unicorn. Sam Altman has spoken of technology executives betting on when someone will create a billion-dollar company without hiring another employee. Whether that happens next year or in three years matters less than the direction of travel, as it will happen eventually. Until recently, the proposition would have been economically absurd. Now, it no longer is.
This should change the questions governments and chief executives ask about AI. Too much discussion still concerns how many jobs AI will eliminate. The more interesting question is what kind of organisation becomes possible when intelligence and execution become dramatically cheaper. The great companies of the next decade may not necessarily be those employing the most people, occupying the largest headquarters or possessing the most elaborate structures. Increasingly, a revealing corporate metric may be how much value an organisation creates per employee.
For the Gulf, there is an even bigger implication. If technology reduces the premium historically attached to large populations, deep labour markets and enormous corporate structures, smaller economies gain an unusual opportunity. The UAE does not need to reproduce Silicon Valley’s scale to produce globally important companies. It needs talent, capital, ideas, speed and an environment in which very small teams can operate globally from day one.
For two centuries, we learnt how to scale organisations in order to scale impact. AI may allow us to separate the two. Small was once something a company grew out of. Increasingly, it may become something the smartest companies fight to preserve.
