Summary of the Key Points
The central argument of this article is that, rather than the “model illusions” associated with AI technology itself (such as generating incorrect information), what is more frightening are the “cognitive illusions” held by business owners regarding AI. These illusions lead them to treat AI as a quick-profit-making “god of wealth,” overestimating its short-term commercial value while ignoring the practical conditions and limitations for its implementation. Such misconceptions can result in poor decision-making, waste of resources, and even operational risks for businesses.
1. What exactly are these owner illusions? — Treating AI as a magic wand that turns stones into gold
The illusion of business owners essentially stems from an excessive deification of AI: they believe that simply investing in AI tools and launching AI projects will instantly solve all their company’s problems—such as boosting sales, cutting costs by half, or doubling profits. They see AI as a “panacea” but forget that it is just a tool that must be integrated with specific business processes, data, and human expertise to be effective. For example, a restaurant owner who heard that AI could optimize the supply chain spent hundreds of thousands on an AI system, only for it to fail to generate a reasonable procurement plan due to the limited number of stores and insufficient data, resulting in a waste of money.
2. Why are owner illusions more dangerous than model illusions? — Small bugs vs. major strategic errors
The “model illusions” associated with AI are technical issues that can be addressed through manual review and technological improvements (e.g., errors in AI-generated copywriting or data calculations). However, the illusions of business owners represent strategic misjudgments:
- Blind investment: Pouring large amounts of money into unsuitable AI projects (for instance, a traditional manufacturing owner trying to use AI for content creation without any real benefit to their business).
- Wrong substitutions: Replacing critical roles (such as research and development or customer service) with AI, leading to decreased quality and loss of key talent.
- Ignoring the foundation: Using AI without proper data accumulation and employee training, effectively rendering it useless.
These strategic mistakes can have a more profound impact on a company’s direction than technical flaws.
3. Common manifestations of owner illusions — Many companies fall into these traps
1. Follow-the-mania investment: Simply because others are using AI, a business decides to adopt it without considering whether it fits their needs. For example, a small supermarket owner installs smart shelves only for them to be unpopular with customers and increase maintenance costs.
2. Short-term return anxiety: Expecting immediate results from AI projects; giving up when no benefits are seen quickly. However, the value of AI often requires long-term development (e.g., analyzing customer data to identify effective marketing strategies).
3. Total automation fantasies: Believing that AI can replace all human tasks; for instance, replacing customer service with robots, which leads to increased complaint rates when customers encounter complex issues.
4. Neglecting supporting capabilities: Buying AI tools without the necessary high-quality data (e.g., incomplete customer information or chaotic production data), preventing the AI from functioning effectively.
4. How to break these illusions? — A rational approach to the capabilities and limitations of AI
1. View AI as a tool, not a miracle-worker: While AI can improve efficiency (e.g., by quickly processing customer feedback), it cannot generate profits out of thin air. Determine which aspects of your business truly benefit from AI (e.g., smart recommendations in e-commerce or quality inspections in manufacturing).
2. Start with small experiments before scaling up: Don’t implement AI across the entire company at once; start with a small test to validate its effectiveness before expanding.
3. Lay the groundwork: AI requires data to function effectively; organize your business data (e.g., customer consumption records, production process data) and train employees to work alongside it (e.g., teaching customer service representatives to use AI for simple issues while handling complex ones manually).
4. Be patient: The value of AI is gradual; don’t expect immediate success. For example, using AI in research and development may take 1-2 years to see results, but it can save significant time in the long run.
In summary, AI is not a savior. Instead of fantasizing about instant wealth creation, business owners should integrate AI into their operations wisely, utilizing its strengths (e.g., automating repetitive tasks and data analysis) while focusing on human skills where AI falls short (e.g., creativity, decision-making, and emotional customer communication). This approach will maximize the true potential of AI.