Strategy (formerly MicroStrategy) founder Michael Saylor has shared his vision for a career strategy in the era of widespread artificial intelligence adoption. His main advice for the younger generation sounds paradoxically simple: don't try to master what AI can already do better than you. Instead, look for opportunities that others haven't noticed yet. He calls his method "finding a new S-curve."
The essence of the approach: don't replicate, create
Saylor claims that AI is increasingly taking over routine operations related to data processing. Therefore, learning such skills is a dead-end path. "Don't learn to do what AI already knows how to do," he emphasizes. In his opinion, it is far more productive to learn how to set tasks for neural networks that no one has solved before. This could involve creating a fundamentally new product or radically reducing the cost of an existing service through AI implementation.
Saylor's key thesis is maintaining deep expertise in your field. Without this, it is impossible to properly formulate requests and evaluate the results of algorithms' work. The simple ability to "ask ChatGPT the right questions" does not provide a sustainable advantage—it quickly depreciates.
The S-curve as a compass
Saylor compares technological progress to an S-shaped curve: a slow start, a sharp rise, and subsequent stabilization. In his view, AI and related digital technologies are currently in the acceleration phase. The point of the strategy is to spot a field that has just become possible and take a place in it among the first. This requires courage and a willingness to act ahead of the curve when the majority is still doubting.
By the way, he applies the same logic to investments. Saylor explains why traditional assets, such as real estate, do not appeal to him: "You take on a huge tax and operational burden. The real estate business is complex. Starting your own company is hard. Investing in others' is too. That's why bitcoin is such an interesting instrument. Why not simply put money into an asset that grows in value by 15% a year and forget about the problems."
My analysis
Saylor once again demonstrates his signature ability—turning complex technological trends into simple and actionable life principles. However, it is worth remembering that his own company is currently going through tough times: Strategy shares have lost nearly 40% since the beginning of the year, and a net loss of $8.22 billion was recorded in the second quarter. This is a reminder that even the boldest strategies come with risk. Nevertheless, his advice about the "new S-curve" is universal: in the AI era, the winners are not those who replicate best, but those who see the new first.