Make Money With AI: I Tested 100 Tools — Only These Are Worth Using (2026)

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AI • Blogging • Affiliate Marketing

I made my first $100 with AI by using it to help create content, attract visitors, and monetize relevant articles with affiliate links. AI didn’t generate the money by itself. It helped me build the content workflow behind it.

I didn’t start with an audience or a complicated stack of AI tools. Instead, I focused on topics people were already interested in, used AI during the content-production process, published the articles on my site, and connected relevant tools to that content through affiliate programs.

That first $100 mattered because it showed me something more useful than a hypothetical AI side hustle: I had evidence that my own site could generate revenue.

This isn’t a promise that you’ll make $100 by following the same steps. Traffic, rankings, conversions, affiliate programs, niches, and execution vary. What follows is the process described in my own experiment and the lessons I’d take from it.

How I Made My First $100 With AI

The idea was fairly simple: rather than trying to sell “AI” itself, I used AI to help build content around subjects I wanted to cover on my website.

The basic model looked like this:

There are several difficult steps hidden inside that simple diagram. Content has to be useful enough to publish, people need to discover it, the recommended product has to fit the reader’s problem, and some of those readers have to decide the product is right for them.

AI helped with the production side. It didn’t remove those other requirements.

What I Used

I didn’t need dozens of subscriptions to test the idea. The workflow described in my original notes centered on a few basic pieces.

The biggest lesson here is that the tool stack wasn’t the business model. The website, content, audience, and affiliate relationship were the business pieces. AI supported the work required to build them.

Step 1: I Started With Topics People Were Looking For

I focused on subjects such as AI tools, making money with AI, and beginner AI questions.

Choosing a topic people care about is only the beginning, though. A broad phrase such as “best AI tools” can have several different search intents, so the article still needs a specific job.

Before publishing now, I’d ask:

• What is the reader actually trying to accomplish?
• Do I already have an article answering this query?
• Can I add testing, experience, screenshots, or analysis?
• Does the topic naturally connect to something I can recommend?
• Would the article still be useful without an affiliate link?

Step 2: I Used AI to Help Create the Content

AI reduced some of the work involved in moving from an idea to a draft.

I used it for tasks such as:

• Creating outlines
• Developing sections
• Rewriting unclear passages
• Organizing ideas

The important part was not treating the first output as the finished article. Generated text still needed editing so the page was useful and sounded like something I would actually publish.

If I were building the workflow from scratch today, I’d also put more emphasis on supplying source material, verifying current facts, and adding something AI can’t invent—real experience, screenshots, testing, observations, or results.

Step 3: I Published the Content on My Own Site

The next part was straightforward: the articles needed somewhere to live.

Publishing on my own website gave me a place to build content around related AI topics, connect those articles with internal links, and add relevant monetization where it made sense.

Consistency helped me build out the site, but I wouldn’t reduce the lesson to “publish as much as possible.”

Publishing ten overlapping AI articles isn’t automatically better than producing one strong guide. If several pages answer essentially the same question, they can compete with each other and make the site harder to understand.

Step 4: I Needed Traffic Before Affiliate Links Could Matter

An affiliate link sitting on an unread page doesn’t do much.

My original notes identify Google Search, Pinterest, and internal links as traffic sources that helped people reach the content. The larger lesson is that monetization happens after distribution, not before it.

A useful article therefore has two separate jobs:

1. Earn attention. Someone has to discover the page and find it relevant enough to read.
2. Earn trust. The recommendation has to make sense in the context of the problem they’re trying to solve.

That second part is especially important for affiliate content. A recommendation is more useful when you can explain why the product fits, where it doesn’t, and what you learned from actually using or researching it.

Step 5: Affiliate Commissions Produced the First $100

According to my original notes, the revenue came from affiliate recommendations inside the content.

I covered categories such as AI writing tools, automation platforms, and business AI products. When an eligible reader followed an affiliate link and completed the action required by that program, I could earn a commission.

That sounds simple, but I wouldn’t frame the formula as:

Each part of that equation can break.

More content can produce no additional traffic. More traffic can produce no affiliate clicks, while clicks can fail to convert. Even conversions may have different commission rates, attribution windows, eligibility rules, or reversals.

A better model is:

What Worked for Me

My original notes identify four things that helped during this first experiment:

Choosing Topics People Were Already Interested In

I wasn’t trying to invent demand from scratch. Starting with existing questions gave each article a clearer purpose.

Keeping the Workflow Simple

I didn’t need every AI tool available. A smaller workflow made it easier to learn what each part was actually contributing.

Publishing Consistently

Publishing gave me opportunities to learn what worked, but consistency only helps when the pages are worth publishing. I’d rather improve a promising article than hit an arbitrary content quota.

Connecting Related Articles

Internal links helped readers move between relevant pages and gave the site’s related topics a clearer structure.

What Didn’t Work

The failures are just as useful as the first commission.

Overcomplicating the Process

Adding more tools and steps can feel productive while making the actual workflow harder to manage.

Jumping Between Too Many AI Tools

Trying every new product creates a lot of experimentation without necessarily improving the work. A tool earns its place when it solves a defined problem.

Expecting Results Too Quickly

Publishing an article doesn’t guarantee immediate search traffic, affiliate clicks, or revenue. Those outcomes depend on factors beyond the AI tool used to create the content.

What I Would Do Differently Now

If I were starting this experiment again, I wouldn’t focus primarily on increasing article count.

I’d spend more time on:

• Checking existing content before choosing a new topic
• Understanding the exact search intent
• Testing the products I’m recommending when practical
• Adding original screenshots and examples
• Comparing products around real decisions
• Updating promising pages instead of constantly starting new ones
• Tracking which pages and recommendations actually produce results

Those additions make the content harder to reproduce with a generic prompt, which is exactly what I want.

Can This Method Scale Beyond $100?

The first $100 showed that the model could produce revenue for me. It didn’t prove that revenue would automatically increase by publishing more pages.

Scaling responsibly means improving the parts of the system that already show evidence of working.

That might involve:

• Updating an article that already attracts relevant visitors
• Adding better product testing or comparisons
• Strengthening a content cluster with a genuinely different supporting topic
• Improving internal links between related pages
• Testing another relevant traffic source
• Improving calls to action without making the article feel like a sales page
• Removing tools or affiliate offers that don’t help the reader

The goal isn’t simply more. It’s a better connection between the content, audience, and recommendation.

What This Experiment Did—and Didn’t—Prove

Making Money With AI: FAQ

Can a beginner make money with AI?

AI can help a beginner perform work connected to potential revenue, including content production, services, research, design, automation, and digital products. Earning money still depends on producing something useful and finding customers or an audience for it.

How long does it take to make your first $100 with AI?

There isn’t a reliable timeline. The source material for this article documents my first $100, but it doesn’t provide evidence that other people should expect to reach the same milestone within a particular number of days or weeks.

Do you need a website to make money with AI?

No. AI can support freelance services, client work, products, automation, and other business models that don’t require a website. For the method described in this article, however, my website was a central part of publishing content and generating affiliate revenue.

Can AI create passive income?

AI can reduce work in some processes, but calling the result “passive income” can hide the ongoing work involved. Websites need maintenance, articles need updates, products change, traffic can fluctuate, and affiliate programs can change their terms.

Do you need expensive AI tools to start?

Not necessarily. My original workflow was intentionally simple. Before paying for another tool, I’d identify what part of the process it needs to improve and test whether the benefit justifies the cost.

What’s the biggest mistake when trying to make money with AI?

Starting with the tool instead of the value you’re creating. AI can make production easier, but it doesn’t eliminate the need for a useful product, service, article, audience, or business process.

Final Thoughts

Making my first $100 with AI didn’t convince me that AI is a money machine. It showed me that AI could support a real workflow that eventually produced revenue.

The distinction matters.

I used AI to help create and improve content, but the website still needed useful topics, traffic, relevant recommendations, and readers who decided those products were worth exploring.

If I were starting again, I’d keep the basic system simple while putting more effort into original value: better research, real testing, screenshots, stronger comparisons, and clearer evidence of what worked.

That’s a slower story than “use AI and make money.”

It’s also a much more useful one.