There are real ways to earn from AI right now — and most of the loudest advice online is wrong. Here are seven approaches that actually work, ranked by how realistic they are if you're starting today.
The "make money with AI" content online is overwhelmingly bad. Most of it is recycled advice from people whose actual business is selling you the course about making money with AI. After spending the past two years helping companies in Romania and across Europe actually integrate AI into their operations, I want to share the seven paths that I've watched generate real revenue — and the two that I'd avoid.
This post is heavily inspired by Dan Martell's recent piece on real AI monetization, but the angle here is different: I'm writing from the perspective of someone who builds these systems for clients, not someone selling a system to you.
The single highest-ROI path I've seen: pick one industry, find one repetitive task that everyone in that industry hates, and sell a focused automation. Real estate agents drowning in lead follow-ups. Dental clinics buried in appointment reminders. Law firms manually drafting standard contract clauses. These problems are boring, well-defined, and worth real money to the people who have them. You don't need a novel AI breakthrough — you need to know one industry well enough to identify the right pain.
Notice I said B2B. Consumer content is a brutal commodity market now. But B2B companies still pay €2,000 to €8,000 a month for ghostwritten LinkedIn content, technical case studies, SEO articles, and email sequences. AI doesn't replace the writer here — it makes one good writer 5x faster. The margin is in knowing which clients value quality and will pay for it, not in producing the most articles per hour.
The Fortune 500 has consulting firms. Startups DIY everything. The 50-to-500-employee middle is where the unmet need lives. These companies have real budgets, real inefficiencies, and no internal AI team. They will pay €10K-€50K for a focused project: a knowledge base that actually answers employee questions, a sales-ops agent that updates the CRM, a customer support copilot that drafts responses. This is where I spend most of my client time.
Instead of selling "AI consulting" (vague, hard to buy), sell "We will set up your AI-powered lead intake system in 14 days for €2,500" (concrete, easy to buy). Nick Saraev has written extensively on this approach in his automation agency content, and it works because B2B buyers prefer fixed scope over hourly billing. You're trading some upside for much faster sales cycles.
If you have the runway and patience for a 2-3 year build, vertical AI SaaS still has open lanes. Examples that are working: AI for medical billing, AI for construction takeoffs, AI for legal discovery, AI for veterinary clinic notes. The pattern is always the same — deep domain knowledge plus a workflow-specific model wrapper. This is high effort, high reward, and not the path I'd recommend if you're trying to make money in the next 90 days.
There's a huge market of consultants, coaches, agents, and small business owners who want to use AI but don't have time to learn it. Sell them a complete setup: their personalized prompts library, a custom Claude or ChatGPT workspace, automations connecting their email/calendar/CRM to AI, and a 60-minute training session. Charge €500 to €1,500 per setup. It's repeatable, you can do one per day with a process, and the customer leaves visibly happier.
Companies are finally getting serious about training, and most existing AI training is either too academic or too superficial. A two-day, hands-on workshop where a sales team builds three working AI workflows that they use the next Monday is worth €5K-€15K to a mid-sized company. Pair it with a follow-up retainer for ongoing questions and you have a stable revenue base. This works especially well if you're already known in a specific industry.
Selling courses about making money with AI. Saturated, low trust, and the market for it is people who couldn't afford to pay you anyway.
Generic prompt-engineering services. This was a real opportunity in 2023. In 2026, models are smart enough that "prompt engineering" alone isn't a differentiator. You need to be selling an outcome, not a technique.
My take: The honest pattern across all seven working paths is the same — pick a narrow audience, solve a specific problem, charge for an outcome. The hype industry sells generality. The actual money is in specificity.
If you're trying to figure out which path fits your situation, I do a free 30-minute call where we talk through your background and pick the most realistic next step. You can book one here.
