In recent meetings with investors and the board of directors, Mind Connector frequently receives a seemingly simple question that nonetheless contains many misunderstandings: “Can AI create these strategic plans?” This question doesn’t stem from skepticism, but from a genuine expectation: that AI is increasingly adept at writing, analyzing quickly, using clear logic, and even performing SWOT analysis, Budgeting and growth planning can be done in minutes. The issue isn’t whether AI can do it, but rather that many people are equating “a well-written strategy” with “a strategy that can operate and survive.” This equating, if not clarified, will cost many businesses their time, resources, and opportunities.
A business strategy isn’t just a piece of paper; it’s a series of costly decisions.
AI can write a very coherent strategy. It’s structured. It has arguments. It has logical justifications. It reads perfectly. But in real business life, a strategy isn’t judged by the accuracy of the wording, but by the organization’s ability to withstand the challenges when it’s implemented.
A strategy that looks right on paper but fails to account for the fact that the business lacks the capital to make the same mistake twice, the personnel to implement multiple strategies simultaneously, and the brand’s resilience to withstand a media setback, is essentially a wishful thinking description, not a strategy.
The biggest difference between strategies created by humans and those created by AI lies not in logic, but in the concept of “cost.” AI doesn’t have a concept of the cost of a wrong decision. Experts do.
Why do AI always write strategies that sound so “reasonable”?
One easily recognizable characteristic of AI-generated strategies is their balance and safety. Every element is mentioned. Every direction has a rationale. Every risk is listed. But that very completeness is the problem.
Strategy isn’t a knowledge test where the more complete you are, the higher your score. Strategy is a ruthless selection process where businesses are forced to say “no” to many seemingly attractive options.
AI is trained to optimize the probability of success, not to optimize the survival of a specific business. Therefore, AI tends to suggest expansion, diversification, leveraging multiple channels, and reaching multiple segments. These suggestions aren’t theoretically wrong, but they are very dangerous in a context where resources are constrained.
A strategist writing a business plan will always ask: if we do this, what will the business have to give up? AI doesn’t.
Strategy isn’t about optimization, but about choosing the least fatal risks.
One of the biggest misconceptions investors have when using AI is believing that strategy is the ultimate solution. In reality, strategy is never optimal. Strategy is about choosing risks.
Not scaling quickly is a risk. Scaling incorrectly is also a risk. Not investing in marketing is a risk. Investing in marketing too early is also a risk. Strategy doesn’t eliminate risk, but chooses the risks the business can tolerate.
AI can list risks, but it cannot sense which risks are fatal to a particular organization. AI cannot distinguish between a business that “can be fixed with money” and a business that “cannot afford to make a single mistake.”
Meanwhile, for professionals, understanding a business’s tolerance for error is fundamental to all strategic decisions.
Why Many AI-Written Strategies Fail to Implement
In our consulting practice, Mind Connector frequently encounters strategies that are considered “excellent” but cannot be implemented, not because of a lack of ideas, but because of a lack of order and discipline.
AI can suggest many good things to do, but it doesn’t know which things should be done first, which absolutely shouldn’t be done prematurely, and which, if done incorrectly, will have a chain reaction of consequences.
True strategy doesn’t answer the question “what should be done,” but rather “if you could only do three things in the first year, what would those three things be?” This is a question that AI finds very difficult to answer without real-world operational, cash flow, and human data.
AI doesn’t understand “ugly” decisions.
Another key difference is that AI tends to avoid decisions that sound ugly. It doesn’t scale up. It doesn’t run massive marketing campaigns. It doesn’t capitalize on trends. It doesn’t participate in hot games.
Meanwhile, many successful real-world strategies are built on decisions like these. Decisions that frustrate the reader. Decisions that are difficult to convince investors of. But these are the decisions that help businesses survive and build trust.
AI has no incentive to write strategies that force the reader to confront their own limitations. Experts, however, are compelled to do so.
AI can write part of the strategy.
That’s not to say AI has no role in strategic planning. On the contrary, AI is a very powerful tool if used correctly.
AI can help systematize market information, synthesize data, check logic, and even simulate scenarios. AI can help experts see perspectives that humans might easily miss. But AI should not be the one making the final decisions.
Strategy requires an entity to be accountable. A person or group of people who understand that if the strategy fails, they will pay the price. AI doesn’t have that responsibility.
In conclusion: the issue isn’t whether AI is good or not.
The right question isn’t “Can AI write strategies?”, but rather “Are businesses using AI as a tool or as a replacement brain?”.
When AI is used to write strategic plans instead of human thinking, businesses receive plans that are correct, aesthetically pleasing, and safe, but lacking in survivability. When AI is used to support the thinking of those who understand the limits, constraints, and costs of each decision, it becomes a very powerful leverage.
Therefore, strategy isn’t something to read for enjoyment – strategy is something to live with for many years. And that, until now, remains the responsibility of humans.
