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Costco CEO Ron Vachris said that AI will never replace people in purchasing decisions. The company with $275 billion in revenue chose the path of augmentation, not replacement. What monetization models does this open for entrepreneurs?
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What happened
Costco CEO Ron Vachris spoke at the Economic Club of Chicago and outlined the retail giant’s principled position on artificial intelligence. According to him, the company with annual revenue of more than $275 billion uses AI as an auxiliary tool, not as a replacement for human labor. Costco has implemented the technology in its pharmacy, gas stations, accounting, and IT department, and the results exceeded expectations: the business is growing faster, while employees are moving to more complex tasks. Vachris emphasized that product purchasing decisions will remain with people forever. “I don’t see AI making merchandise decisions for Costco,” he said. The company currently has 81 million paid members, 90% of whom renew their membership, and 55% of employees have worked at the company for more than five years.
How this is useful for business
Costco’s approach demonstrates that fear of people being replaced by machines is often exaggerated. For business, this means several practical conclusions. First, AI works best in the role of an assistant: it accelerates routine processes, but cannot replace strategic thinking and market understanding. Second, companies that implement the technology correctly grow faster and create new, higher-level jobs. Third, the trust of customers and employees becomes a competitive advantage that is difficult to copy. Costco, with a market capitalization of $440 billion, shows that an adequate attitude toward technology correlates with financial success.
How to make money from this
The “AI as an assistant” model opens several directions for monetization. First, you can create solutions for businesses that augment employees rather than replace them. Second, the market for educational programs on human-AI collaboration is growing: companies need training on how to use the technology effectively. Third, consulting in ethical AI implementation is becoming sought-after as regulators tighten oversight. Fourth, developing hybrid systems where AI performs analytics and a human makes decisions is in high demand. Fifth, outsourcing processes that can be partially automated allows costs to be optimized without losing quality.
Business ideas
First idea: a platform for selecting AI assistants for small businesses. Entrepreneurs pay $200-500 monthly for setup and management of a system that helps employees but does not replace them. Second idea: an online school “Human Plus Machine” for managers. A course priced at $800-1200 teaches how to delegate routine tasks to AI and focus on strategy. Third idea: an agency for auditing AI solutions. Companies pay $3000-10000 for an independent assessment of whether their AI is replacing critically important employees. Fourth idea: a marketplace of ready-made prompts for specific industries. Selling libraries for $50-200 per set to increase productivity without replacing staff. Fifth idea: a service for outsourcing routine tasks using AI. Clients pay $1500-5000 monthly for operations that previously required hiring employees.
Risks and limitations
There are objective risks in the “AI as an assistant” model. Technologies develop quickly, and what is considered an assistant today may become an autonomous solution tomorrow. Competitors that aggressively automate processes may gain a short-term advantage in the form of lower costs. It is also difficult to scale an approach where each implementation requires individual customization for a specific team. Integrating AI into existing processes often requires significant investment in retraining staff. Finally, dependence on specific AI providers creates risks if their policies or prices change.
7-day action plan
Day 1: Analyze your business processes and identify which tasks take more than 30% of employees’ time but do not require unique skills. Day 2: Research the AI solutions market for your niche, compare implementation costs and expected ROI. Day 3: Interview the team and find out which tools they would like to use to accelerate their work. Day 4: Choose one area for a pilot implementation of an AI assistant, prepare an integration plan. Day 5: Launch a one-week experiment, collect productivity metrics and feedback. Day 6: Analyze the pilot results, adjust the approach or scale the successful experience. Day 7: Develop an internal AI usage policy and train the team in the principles of effective interaction with the technology.
Original news: Fast Company · See other news in the news section.
