How Should Entrepreneurs Use AI Profitably?

TL;DR

Use AI to remove genuine business constraints and increase profit, not simply to automate every available process. Human value remains in judgment, accountability, risk, and the ability to think independently, while longer time horizons encourage founders to build stronger foundations and more durable businesses.

Transcript

How are you approaching this as an entrepreneur? How can we use AI to do the things that are the the normal functions of the business at a way better, way faster, etc. What I'm seeing a lot, especially with founders or people who are starting out, is they're using AI to do a lot of dumb things really fast. >> [gasps] >> And they're trying to build ... Read More

Key Insights

• AI adoption is valuable only when it improves an economically meaningful outcome. Entrepreneurs should ask whether an AI project generates more money, lowers an important cost, or removes the constraint preventing growth, rather than treating automation itself as evidence of progress.
• The $350,000 automation project replaced work that cost approximately $11,000 per month. That investment represented more than three years of the existing labor expense, while the virtual assistants were performing effectively and their process was not limiting the company’s growth.
• Customer outcomes matter more than an AI label. Businesses should advertise the solution to the customer’s problem because excitement about artificial intelligence is not universal, and some customers may even view the technology with fear rather than enthusiasm.
• Human value in an AI-rich economy is tied to stakes and responsibility. An AI system can produce recommendations, but a person or organization still owns the decision, bears liability, risks money, pays operating costs, and receives the associated upside.
• Authentic entertainment depends on real consequences even when machines can outperform humans. Audiences still care about human chess competitors and Formula 1 drivers because personal risk, skill, reputation, and responsibility create stakes that automated performance alone does not provide.
• Delegating difficult decisions to AI can weaken independent judgment. Different frontier models may provide inconsistent answers, and individual systems can often be persuaded to support opposing positions, so founders must preserve their ability to evaluate evidence and make consequential choices.
• A business foundation should reflect its intended time horizon and scale. The structure built under a five-second deadline differs from one designed for five years, just as a fast one-person agency model may not support a company seeking substantially greater revenue.
• Long-term thinking can create a durable competitive advantage. Founders who expect to operate indefinitely may invest in the underlying factory, systems, and infrastructure instead of optimizing for a quick exit, even when those foundational investments are slower and more difficult to build.
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Questions & Answers

Q: How should entrepreneurs decide where to use AI?

Entrepreneurs should apply AI where it removes the constraint currently limiting growth or improves a measurable financial outcome. Before automating a process, they should ask whether the change will produce more revenue, increase profit, reduce a significant cost, or serve customers better. A process being technically automatable does not mean automating it is the best allocation of money and attention.

Q: Why can automating a working business process be wasteful?

Automating a working process can be wasteful when that process is inexpensive, reliable, and unrelated to the company’s main limitation. The example company spent $350,000 replacing 11 virtual assistants who collectively cost around $11,000 per month and were doing a good job. Because insufficient demand was the real constraint, the automation did not directly solve the business’s growth problem.

Q: Should a company advertise itself as an AI business?

A company should emphasize the outcome customers want rather than assuming an AI identity is persuasive. Customers generally care about having their problem solved, and excitement about the underlying technology may not be shared by the market. Some people are afraid of artificial intelligence, so highlighting AI can be neutral or negative unless it clearly strengthens the promised customer result.

Q: Where does human value remain when intelligence becomes cheap?

Human value remains in judgment, responsibility, risk, and ownership of outcomes. AI can generate recommendations, but a person or organization must decide what to do, accept liability, fund the operation, and bear the consequences. That responsibility also carries potential upside, including financial rewards and ownership, making the assumption of stakes economically and socially valuable.

Q: Why do audiences still care about humans when machines perform better?

Audiences care about human performance because real participants introduce meaningful stakes. A machine may beat a person at chess, but human competitors still have reputations, emotions, and consequences attached to the result. Likewise, viewers want a human driver in Formula 1 and real prizes in reality-based entertainment because authentic risk makes the outcome matter.

Q: Why should founders avoid outsourcing difficult thinking to AI?

Founders should avoid delegating their hardest thinking because AI systems can return inconsistent answers and may be persuaded to agree with conflicting positions. Depending on them for consequential decisions can weaken the founder’s own judgment through disuse. AI can support analysis, but the founder still needs to question assumptions, compare evidence, and personally own the final decision.

Q: How does a longer time horizon change business decisions?

A longer time horizon encourages founders to build stronger foundations, systems, and infrastructure. The tower exercise illustrates that a structure assembled in five seconds is designed differently from one planned for five days or five years. Similarly, committing to operate a company indefinitely can shift attention from rapid exits toward the durable operating factory that supports future scale.

Q: Why is the fastest path to $1 million different from the path to $100 million?

The fastest path to $1 million may rely on a simple structure such as a one-person agency, but that structure may not support much larger scale. Reaching $10 million or $100 million requires different foundational choices, including systems and infrastructure that can endure expansion. Optimizing only for immediate speed can therefore create an unstable base for the larger business envisioned.

Summary & Key Takeaways

• Entrepreneurs should evaluate AI investments by asking whether they increase revenue, profit, or growth. One company spent $350,000 replacing 11 virtual assistants who cost about $11,000 monthly, even though their work was effective and was not restricting growth. The company’s actual constraint was insufficient customer demand, not operational capacity.

• As artificial intelligence makes cognitive work cheaper and more abundant, human value remains connected to stakes. People must still own decisions, accept liability, risk capital, and capture potential upside. Entertainment also depends on real consequences, which explains why audiences continue caring about human chess players, racing drivers, and authentic reality-based challenges.

• Long-term thinking changes how entrepreneurs construct businesses. A tower built in five seconds requires a different foundation from one designed over five years with unlimited blocks. Similarly, the quickest route to a $1 million business differs from the route to $10 million or $100 million, where durable systems and infrastructure become essential.