How to Make Money With AI: What the Gold Rush Can Teach You About Business
✨ Key Takeaways
- The AI gold rush is making money for the people selling the tools. While startups compete to build the next big AI product, companies supplying chips, software, infrastructure, and services can earn revenue regardless of which startups succeed.
- The AI boom is fueled by real demand, massive expectations, and fear of missing out. Companies are investing billions because they believe AI will transform their industries. But the recent stock market selloff shows that investors are starting to question whether those investments will actually pay off.
- You can make money with AI without building an AI product yourself. The opportunity is to identify what businesses genuinely need, solve a problem they’re willing to pay for, and use market research and marketing analytics to validate demand before investing.
Everyone wants to get rich from AI. And some people are already making an extraordinary amount of money from it.
AI startups are attracting billions in investment. Nvidia is selling the chips that power the whole industry.
Microsoft is pouring billions into AI infrastructure while building AI into products used by millions of businesses.
Naturally, everyone wants a piece of the action.
But there’s a rather expensive problem. Spending billions on AI and making billions from AI are two very different things.
And last week, Wall Street started asking some uncomfortable questions.
On October 30, 2026:
- Nvidia fell 4.2%.
- AMD dropped 10.9%.
- Intel plunged 28.6%.
- The Nasdaq lost 2.86%.
Investors are worried that companies are spending enormous amounts on chips, data centers, and AI products without a clear idea of when those investments will pay off.
Some are even asking whether the AI bubble is about to burst.
And yet, businesses keep buying AI tools. Startups keep building new products. Companies keep investing because nobody wants to miss what could become the biggest technological shift in decades.
Which raises an interesting question: if even the biggest technology companies are struggling to convince investors that their AI investments will pay off, how are the rest of us supposed to make money with AI?
Maybe the answer is hiding in the way the AI boom works.
After all, the AI gold rush is also a brilliant marketing story. It convinces people to buy tools, software, and computing power in the hope that these investments will eventually make them rich.
And while thousands of businesses compete to create the next breakthrough AI product, someone is already making money selling them everything they need to try.
So perhaps the opportunity isn’t always in building the next big AI company. Perhaps it’s in understanding what all those companies need and finding a profitable way to supply it.
But does that strategy actually work?
To find out, we need to go back nearly 180 years, to another period when people were convinced that a fortune was waiting for anyone brave enough to chase it.
California, 1848. Gold had just been discovered, and thousands of people were preparing to risk everything for a chance to get rich.
How to Make Money During a Gold Rush: Sell Shovels, Not Dreams
In 1848, gold was discovered in California. By 1849, roughly 80,000 newcomers had arrived, hoping to strike it rich.
But finding gold wasn’t cheap. Prospectors had to pay for transportation, food, accommodation, and equipment before they could even start digging. And finding gold was never guaranteed.
Sam Brannan figured out how to make money from the gold rush without finding a single ounce himself.
He bought up mining supplies and helped spread the news of the discovery. As thousands of hopeful miners arrived, they needed exactly what he was selling.
The numbers tell the story:
- $36,000 in sales in just nine weeks: Historical accounts credit Brannan’s store with generating this extraordinary sum during the early rush.
- Up to $150,000 a month in revenue: At the height of the boom, some accounts report that Brannan’s businesses were bringing in this much.
- California’s first millionaire: Brannan built his fortune supplying prospectors rather than mining gold.
Levi Strauss spotted a similar opportunity. He arrived in San Francisco in 1853 to sell clothing and other dry goods.
In 1873, Strauss and tailor Jacob Davis patented riveted work pants, creating the foundation of the Levi’s jeans business.
Neither needed to predict where the next gold deposit would be.
They understood something more useful: miners might never find gold, but they would still need equipment, clothing, and supplies.
That’s the business lesson behind every gold rush, including today’s AI boom. When thousands of companies chase the same opportunity, look at what they all need to buy along the way.
Three examples of businesses that profited from major economic booms
- California Gold Rush: Sam Brannan sold mining equipment to prospectors who needed supplies before they could begin digging.
- Internet boom: Cisco supplied networking equipment that businesses needed to connect computers and build internet infrastructure.
- Cryptocurrency boom: Cryptocurrency exchanges earned transaction fees, while hardware manufacturers sold equipment used for mining.
The business model is commonly called selling picks and shovels. Instead of competing directly for the main prize, a company supplies products or services that participants need.
This strategy can reduce dependence on predicting individual winners, although suppliers still face competition and changing demand.
How to Make Money With AI Without Building AI Technology
You don’t need to develop the next ChatGPT to make money with AI. Think about what people have always paid for: food, entertainment, education, convenience, and solutions to everyday problems.
AI hasn’t changed those basic needs. It has made creating products and delivering services easier.
Look at Nvidia. While thousands of companies compete to build successful AI applications, Nvidia sells the chips many of them need. Small businesses can follow a similar principle: find existing demand and use AI to serve it.
Five Practical Ways to Make Money With AI
- Publish books on Amazon. Use AI to research topics, outline books, and help create original activity books, educational guides, or puzzle collections. Publish through Kindle Direct Publishing, which offers print-on-demand. The challenge is finding a topic people actually search for and producing something worth buying.
- Create entertainment products. Use AI to help produce short videos, printable party games, personalized illustrations, or digital downloads. Sell the products directly or monetize an audience through sponsorships and advertising.
- Offer services to food businesses. Restaurants and bakeries constantly need customers. Use AI to help create menus, social media content, promotional campaigns, or customer-service systems. Sell the finished service rather than the AI tool.
- Automate small-business tasks. For example, a property management company might receive hundreds of maintenance requests each month. You could build a simple AI-assisted system that organizes requests, sends confirmations, and alerts employees to urgent issues.
- Help companies implement AI. A marketing agency might have several AI subscriptions but no idea how to use them efficiently. You could help choose tools, automate reporting, train employees, and improve workflows.
The common principle is simple: people pay for useful results, not for the fact that AI was involved.
Before creating anything, research what customers already buy, what problems they complain about, and how much they’re willing to spend. That’s how you turn an AI idea into a business opportunity.
How to Find Profitable AI Business Ideas: Learn From the Man Who Sold the Shovels
Sam Brannan didn’t just sell mining equipment during the California Gold Rush. He helped create demand for it.
In 1848, he walked through San Francisco shouting, “Gold! Gold! Gold from the American River!”
He had already stocked his store with mining supplies, so every new prospector was a potential customer.
Brannan understood marketing: attract attention, anticipate what customers will need next, and be ready to sell it.
Today’s AI companies use a similar playbook. Headlines promise that AI will transform entire industries, businesses rush to adopt it, and suppliers sell them software, chips, and consulting services.
But excitement alone doesn’t tell you which AI business will be profitable. For that, you need market research.
Here’s where I’d start:
- Analyze search demand. Use Google Trends and keyword research to find problems people actively search for. For example, repeated searches for automated invoicing suggest a potential opportunity to sell bookkeeping automation to small businesses.
- Study customer complaints. Read competitor reviews, Reddit discussions, and industry forums. If restaurant owners repeatedly complain about expensive booking software, investigate whether they’d pay for a simpler alternative.
- Check willingness to pay. Compare competitor prices, interview potential customers, and offer a paid pilot before building anything. Ten paying customers tell you more than 10,000 views on an AI demo.
Brannan didn’t wait for miners to ask for shovels. He understood what they’d need before they arrived.
That’s the advantage marketing research gives you
Why Marketing Analytics Is Essential for AI Business Success
Once you’ve identified a potential AI business opportunity, you need evidence that customers actually want the solution.
This is where marketing research and analytics become especially valuable.
Marketing analytics helps businesses understand customer behavior, evaluate demand, identify profitable customer segments, and measure whether marketing investments produce results.
AI can accelerate parts of this analysis, but the quality of the decisions still depends on the underlying data and how it’s interpreted.
Three ways marketing analytics helps businesses find opportunities
1. Identify customer demand through search data.
Imagine you’re considering an AI appointment scheduling service for healthcare clinics.
Before developing the product, you could research relevant search queries, analyze competing solutions, and investigate common customer complaints.
Keyword research might reveal interest in automated appointment reminders, scheduling software, or reducing missed appointments.
This information helps identify potential demand, although customer interviews and willingness-to-pay research are still necessary.
2. Understand why customers aren’t converting.
Suppose an AI software company attracts 10,000 website visitors each month but generates only 50 trial registrations.
Instead of immediately spending more money on advertising, the company could examine visitor behavior.
Marketing analytics might reveal that most visitors leave the pricing page or abandon the registration process.
Improving the pricing explanation or simplifying registration could increase conversions without increasing advertising spending.
3. Identify which marketing channels generate profitable customers.
Imagine a business spends $5,000 monthly on Google Ads, LinkedIn advertising, and email marketing.
Google Ads generates 100 leads, LinkedIn generates 40, and email generates 30.
At first glance, Google Ads appears most successful.
But further analysis reveals that LinkedIn leads convert into paying customers at a much higher rate and generate greater revenue.
Without marketing analytics, the business might continue investing in the channel producing the most leads rather than the most profitable customers.
Understanding these differences helps companies allocate marketing budgets more effectively.
How to Use AI and Marketing Analytics to Build a Profitable Business
The biggest lesson from the Gold Rush is that profitable opportunities often emerge from understanding what a growing market needs.
Today, AI is creating demand across almost every industry, but that doesn’t mean every AI product will find paying customers.
Before launching a business, you need to identify a specific problem, evaluate customer demand, and understand how competitors are already addressing it.
Marketing analytics provides information that can support those decisions.
Three steps to evaluate your next AI business idea
- Research the market before developing the product. Use keyword research, competitor analysis, and customer interviews to identify problems people actively want to solve.
- Test whether customers will pay. Create a simple offer, demonstrate the proposed solution, and speak with potential customers before committing substantial resources.
- Measure performance and improve your approach. Track customer acquisition costs, conversion rates, revenue, and customer retention to understand whether your business model is working.
These steps help you make decisions based on evidence rather than excitement around the latest technology.
Turn Market Insights Into Business Opportunities
AI is changing how companies operate, but understanding customers remains essential to building a successful business.
You can have excellent technology, efficient automation, and an impressive product.
However, if you don’t understand your target audience or how to reach them, generating consistent revenue becomes difficult.
That’s why I focus on marketing analytics.
I help businesses understand their marketing performance, identify growth opportunities, and make better decisions using data.
Whether you’re exploring an AI business idea, launching a new service, or improving an existing business, marketing analytics can help answer important questions.
Which customers are most valuable? Which marketing channels generate profitable results? Where are potential customers dropping out of the buying process? And which opportunities deserve further investment?
Through market research, customer behavior analysis, and marketing performance measurement, I help businesses turn complex data into practical insights.
Because the next big opportunity may already exist in your market. Recognizing it requires understanding what customers need, how they behave, and what they’re willing to pay for.
If you want to understand where your business can grow and which marketing activities are actually driving results, let’s connect and explore how marketing analytics can help.
