The New Wealth Window: How AI Is Creating a Once-in-a-Decade Opportunity

The Recurring Pattern of Wealth Creation

Roughly once every 10-15 years, a window of opportunity opens during which people build significant fortunes — the 1990s were one such era. According to the speaker, Maxim Spiridonov (who has built and sold multiple businesses worth billions of rubles and now aims to build a billion-dollar company), we are living through exactly this kind of moment right now. The encouraging part is that this particular opportunity is unusually accessible: it doesn't require capital, connections, or even a brand-new profession to take advantage of it.

The Great Redistribution of Money Driven by AI

The largest redistribution of wealth in history is currently underway, driven by the rise of artificial intelligence. Money is flowing away from people who work the old way toward those who have already adopted new ways of working. This shift is most visible in salary data.

PricewaterhouseCoopers, one of the world's largest consulting firms, analyzes nearly a billion job postings globally every year.
Comparing pay for identical jobs held by people with AI skills versus those without, the wage premium was 25% a couple of years ago, rose to 57% the following year, and reached 62% this year.
In some industries, the gap exceeds 100%.

Importantly, this premium isn't paid for knowledge of how the technology itself works — it's paid because the person completes the same job faster and cheaper than a colleague at the next desk. Employers aren't buying the technology; they're buying the resulting difference in speed, cost, and quality.

Finding Your Own Gap: A Practical Exercise

To make this concrete rather than abstract, open any AI chat tool and submit a prompt describing your industry, your role, and what you actually do and observe. Ask the AI to identify ten tasks in your field that are currently paid for in money but performed by hand, and that could now be done faster and cheaper using AI. For each task, ask it to specify who pays for it, what it currently costs, and what would change in the process — and, crucially, instruct the AI to first ask you clarifying questions before answering. Skipping this last instruction typically produces a generic, superficial list; including it produces analysis tailored to your specific situation, provided you answer the follow-up questions thoughtfully.

Two Ways Business Owners Can Benefit

If you run a business, there are two distinct ways to capture value:

Margin on what you sell — Clients don't care whether you use AI to deliver a result; they pay for the outcome and the deadline. This means the price you charge stays the same while your cost of delivery drops, directly increasing your margin.
Internal cost savings — Every business has manual internal processes it pays for repeatedly: report preparation, first-line support, document checks, request processing. Redesigning these processes with AI stops recurring costs you may have been paying for years. Money saved this way is functionally identical to money earned, except it doesn't require finding new clients.

Where the Real Money Is — And Where It Isn't

It's important to be realistic about where opportunity lies. Making money directly from AI infrastructure — chips, data centers, model training — is not realistic for an average person; hundreds of billions of dollars are being invested there by governments and major corporations, and that arena is closed to individuals.

The real opportunity lies elsewhere: in work that still commands high prices because everyone around you is still doing it manually, even though it can now be done far faster and cheaper. The strategy is to charge the old market price while operating at a new, AI-enabled cost basis. Nothing needs to be invented — you simply need to be among the first to enter that niche, much as people did with websites in the late 1990s or targeted advertising in the early 2010s. A few months of hands-on experimentation can be enough to build a waiting list of clients; a few years later, it becomes an ordinary profession, but by then you may have already built a business on it.

The speaker illustrates this with his own experience: in 2007 he launched a bookmarking service called Memori, allowing users to collect and share links to interesting content — something obvious in hindsight, but novel when browser bookmarks were private and invisible to others. He didn't invent anything; he simply noticed rising interest in social services in the Russian internet space before major players caught on. The project was built in two months with a small team, and sold four months after launch for several hundred thousand dollars — leading to the memorable image of walking out of the office with cash under his arm, unable to catch a taxi, and taking the metro home instead.

Today, he argues, there are more such windows of opportunity than at any other point in his memory, because AI touches virtually every domain — text, video analysis, documents, digital systems. The only real question is which of these domains overlaps with your own expertise, experience, and connections.

The Four-Step Formula: From Insight to First Paying Client

Turning insight into income requires four steps, achievable in a matter of days to a week with sufficient persistence.

Step One: Choose a Market You Deeply Understand

Pick a market you know from the inside — one where you already have contacts saved in your phone and understand how things really work there. This kind of insider knowledge cannot be bought. In a business context, this is called "founder-market fit"; in an employment context, it can be called "employee-market fit" — your personal connection to the market, accumulated observation of how it operates, and the relationships that help you navigate it.

Step Two: Identify a Specific, Manual, Recurring Task

From the list generated earlier, select one task that people currently pay for and that is still done mostly by hand. Good candidates are boring, regular tasks — this is actually advantageous, since recurring tasks generate repeat clients. Look for work that is billed for and still performed roughly the way it was five years ago: reports, translations, video editing, cold calling, recruitment, document verification.

Step Three: Design the Full AI-Powered Workflow

Design the complete execution of this task using AI, from start to finished, presentable output. This is the most delicate step, because the result must be good enough to hand to a client without embarrassment. You don't need to know in advance how to do the task — in fact, you likely won't. Ask the AI to propose a plan and begin executing it. The first attempts will probably be rough, and that's expected. What matters is the process of iterative dialogue with the AI — described as "accelerating together" with the model — through which you learn things no course can teach: where the AI tends to lie or express itself imprecisely, what needs manual correction, and what must be checked every time. This skill of working in dialogue with AI as a "co-pilot" is itself the real product. People who have only read about AI typically lack this practical skill, because knowledge and hands-on ability are fundamentally different things.

Step Four: Sell to People You Already Know

Sell what you've built to people already in your network. Call contacts in the relevant industry and offer to complete in a day something that currently takes them a week, proposing a trial on one project. It's fine — even preferable — to charge little for the first engagement; the priority is gaining real implementation experience and testimonials that can later serve as evidence for future clients.

For employees, the same formula applies, except the first "client" is your manager: rather than pitching an idea, you present completed work — for example, showing that a task which took a team 20 hours a month now takes you two hours working alone. This is a fundamentally more persuasive conversation than simply asking for a raise after completing an AI course.

Entrepreneurial Mindset as a Long-Term Career Advantage

This proactive, results-oriented approach — broadly described as an entrepreneurial mindset — isn't limited to business owners. For employees as well, adopting this mindset in the coming years could produce remarkable gains in career growth, opportunity, and income.

The Window Won't Stay Open Forever

An important caveat: this window of opportunity is temporary. While it's open, your speed and fluency with AI tools can be converted directly into money, but eventually the broader market will catch up, and most people will be doing similar work at similar speed and price.

To prepare for that inevitable convergence, it pays to apply entrepreneurial thinking now and act more strategically:

Negotiate differently while you still have an edge — instead of charging a fixed project fee, ask for a percentage of what the client earns or saves through your work.
Rather than repeatedly delivering one-off projects, package your method into a product that sells itself without your direct involvement.
If it becomes clear that the client genuinely cannot achieve results without you, consider negotiating for equity or a partnership stake — many traditionally minded entrepreneurs currently need technologically capable partners, and this kind of opening exists in various places right now.

Adopting this entrepreneurial mindset is a key tool for building a lasting competitive advantage within the currently open window of opportunity.

Closing Challenge

As a final exercise: write down three tasks from your industry that are paid for in money but performed manually — ideas that likely surfaced while watching this content. Choose one you can tackle in a new way this week, and start solving it with AI.

Finally, it's noted that even excellent completed work doesn't sell itself — people need to understand within a minute why they need you, a topic covered separately in a four-part self-presentation framework designed to work better than any business card.