In economic terms AI will make super intelligence a factor of production.
In economics, the factors of production are the fundamental resources or inputs required to create any good or service. Whether you are baking a loaf of bread or building a software platform, you need a combination of these elements to produce an output.
In this episode, I will argue that AI will become a factor of production soon, specifically super intelligence, but before making that case let us firstly review the classic factors of production.
Classical economists categorize these resources into four main pillars, each of which earns a specific type of income (its "return").
1. Land (Natural Resources)
This encompasses all naturally occurring resources used in the production process. It includes physical real estate, but extends much further into materials extracted from the earth.
- Examples: Agricultural soil, water, crude oil, minerals, timber, and even the air or electromagnetic spectrum.
- Economic Return: Rent. The income earned by the owners of land or natural resources for allowing others to use them.
2. Labor (Human Effort)
Labor is the physical and mental effort contributed by humans in the creation of goods and services. It measures the work done by people, regardless of their skill level.
- Examples: A software engineer writing code, a farmer harvesting crops, a teacher leading a classroom, or a delivery driver.
- Economic Return: Wages. The compensation paid to workers in exchange for their time and effort (including salaries, bonuses, and benefits).
3. Capital (Manufactured Resources)
In economics, capital does not just mean money. Instead, it refers to the human-made tools, machinery, and infrastructure used to produce other goods and services. Money is simply "financial capital" used to buy physical capital.
- Examples: Factory buildings, delivery trucks, computer servers, hammers, and software algorithms.
- Economic Return: Interest. The return earned on the capital invested in the business.
4. Entrepreneurship (The Organizer)
Entrepreneurship is the human initiative that combines the other three factors: land, labor, and capital, to create something of value. It involves taking on the risk of the venture and innovating.
- Examples: A founder starting a tech startup, a local baker opening a new storefront, or an inventor patenting a new product.
- Economic Return: Profit. The financial reward left over after all the costs of land (rent), labor (wages), and capital (interest) have been paid. Profit is the reward for taking on the business risk.
In a previous article I wrote back in 2004 entitled “Defining the Knowledge based Economy” (ref: https://leadprompt.sh/a/18-Defining-the-Knowledge-based-Economy), I argued that Knowledge was the fifth factor of production:
“Knowledge: the Fifth Factor
Enterprise and labor are factors that are affected by the level of knowledge contained within these factors. For example, a successful experienced entrepreneur is more likely to succeed with a new venture than an inexperienced business person straight out of business school. Therefore we can safely say that enterprise and labor obtain knowledge over time, and in the knowledge-based economy, this knowledge increases the worth of both of these factors.
Knowledge itself may also act independently of human factors of production, for example knowledge may be contained within a computer system rather than in a human mind. Such knowledge bases may contain wealth-generating information, for example details on building a valuable pharmaceutical.”
It is always strange to read ones words from 22 years ago, especially the sentence “for example knowledge may be contained within a computer system rather than in a human mind”. Clearly I was not thinking about AI at the time, but it seems like a good fit for the computer system as a replacement for a mind.
Therefore I would like to change my mind after all of these years, and argue that AI is the fifth factor, specifically super intelligence.
Thanks to AI we now have a marketplace in super intelligence, enabling anyone to pay a small fee to access vast repositories of human knowledge on any topic in seconds. Given the widespread availability of such tools, it would seem likely that they will become a common input into a diverse range of economic activities.
If we accept that super intelligence is this new, fifth factor of production, the natural next question for any economist, or engineer, is the following: what is its economic return? And more importantly for those of us leading technical teams, how does it reshape the other four pillars?
When raw cognitive power becomes abundant and commoditized, available instantly and at the speed of compute, the fundamental bottlenecks of production shift. The differentiator is no longer just how many smart people you can hire, but how effectively your architecture and systems can orchestrate this new digital intellect.
It forces us to rethink organizational design. AI transitions from being a mere tool, which we would traditionally classify as Capital, to an active participant in problem-solving. In an era where super intelligence is a standard baseline input, the real premium falls squarely on the Entrepreneurship factor: the vision to direct that intelligence toward the right systemic problems, and the engineering discipline to keep the resulting systems simple, modular, and robust.
We don't just need to adopt AI; we need to build AI-first structures that integrate this intelligence seamlessly into our production cycles, breaking down traditional silos along the way.
That’s the true challenge for the next decade of tech leadership.
Thank you for tuning in to Lead Prompt. I’m John Collins. Until next time, keep executing from the root
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Title music is "Apparent Solution" by Brendon Moeller, licensed via www.epidemicsound.com
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