You’re Doing AI Automation WRONG (Fix It Now!)

If you’ve been trying to jump into the world of AI automation, but you’re struggling to make it work — either for your own business or by selling services — you are not alone. Many beginners are approaching this space with a strategy that is suboptimal.

The good news? The secrets to monetizing AI are not complicated. They simply require a mindset shift. We’re breaking down the four non-obvious lessons learned by an expert who has successfully sold AI workflows for thousands and scaled their own agency, True Horizon, to $2.5 million this year by building effective AI systems.

Get ready to stop chasing shiny tools and start chasing real leverage!

Lesson 1: Stop Automating Everything — Start Leveraging When AI automation first hit the scene, everyone assumed the goal was complete automation: building agents to replace every human. Back in 2022, tools like AutoGPT created a massive hype cycle around “giant end-to-end agents” that supposedly handled entire workflows with zero human input.

Here’s the reality check: Those fully automated systems often broke, created bottlenecks, and caused more problems than they solved in the real world. Businesses quickly learned that full automation is not the goal. The core lesson is this: AI automation is actually about leverage.

Implement the Golden AI Ratio Leverage means finding the optimal mix where AI and humans work together. Instead of trying to automate 100%, focus on the “golden AI ratio”:

Automate the Repetitive (The First 60%): Use automation for the boring, repetitive tasks, like logging data into a CRM or scheduling calls. (You might not even need advanced AI for this part).
AI Assists Human Judgment (The Next 30%): Use AI to assist tasks that require some context or judgment, such as drafting personalized outreach messages or generating draft financial summaries. A human can then tweak the draft and send it off.
Human Touch (The Last 10%): Leave high-touch tasks, like closing a deal, building company culture, or providing the final creative sign-off, fully manual.

The Key Takeaway: The real question is not “How do I automate everything?” but “Where does AI give me the most leverage?”. Remember, if a system automates 70% of a 10-hour process, you’re still saving 7 hours. That’s massive value, and that’s leverage.

Lesson 2: Depth Builds Authority (Don’t Do Too Much!) When you’re new to AI, your instinct is to go wide: learn every new tool, build every type of workflow, and say yes to every client. While this sounds like it increases your chances of winning, it actually kills your leverage.

Stop Tool Hopping Many beginners hop constantly — using one tool one week, and a new viral agent the next. This results in knowing a little bit about tons of things, but not enough depth to solve real business problems. The successful approach is the opposite: Pick one tool and stick with it. Go deep, not wide. If you become the expert who deeply understands a single tool and its capabilities, that depth builds authority, and authority brings clients. You want to go “an inch wide and a mile deep” because that’s where you find the “diamonds” of expertise.

Stop Chasing Every Niche The same principle applies to clients and marketing platforms. Many beginners think a bigger market means more money, so they try to serve everyone: gyms, e-commerce, real estate, dental clinics. This spreads you too thin and ensures you stay a generalist.

The Winning Strategy: Pick one lane. Solve one specific problem for one type of client, and double down. When you build depth in a niche, you know their exact pain points and solutions better than anyone else. Similarly, for marketing, pick one main platform, go deep, and only expand once you have built real authority there.

Lesson 3: Complexity Kills — Simplicity Scales When new people enter the AI space, they often love building flashy, complex systems: workflows with 15 steps stacked together like a Jenga tower, or 10 different agents talking to each other. These demos look impressive and grab attention online. However, in the real world, these complex systems will break. Businesses aren’t paying for “advanced”; they are paying for reliable. They don’t care how many API calls or nodes your system has. They care if it saves them time, makes them money, and doesn’t constantly need to be fixed.

Boring Is Beautiful You might think creating something “cool” is what adds value, but the true value is in how usable the tool is. A simple, “boring” workflow that reliably saves a company 100 hours a month will always be worth more than a flashy, complicated agent that requires constant babysitting.

Actionable Tip: When building, always ask: What is the simplest possible version of this that still delivers the required result?. This mindset creates systems that are easier to manage and far more scalable. Predictability is truly your best friend in automation. Stop overbuilding and start creating simple, stable systems that deliver obvious value, because that is what businesses actually pay for.

Lesson 4: Focus on the Process, Not Just the Prompts Beginners often get stuck obsessing over prompts, tweaking them for days, or stacking tools endlessly. But prompts and tools are easy to change; the real challenge is understanding the process that these tools are meant to improve. If you plug the smartest workflow in the world into a broken business process, you’re just going to make that process break faster or worse. It’s like a doctor prescribing medicine without understanding the patient’s system — it might work for one person, but harm another. If you don’t understand the business process at its core, your system will be misaligned from day one.

Study, Don’t Just Build

Your main job isn’t to build flashy AI systems; it’s to study.

Before designing anything, study:

How the process currently works.
What parts are repetitive (ripe for automation).
What parts require human judgment.
Where the human touch actually adds unique value.

Sometimes, when you truly understand the core problem, you realize you don’t even need a custom AI solution; maybe they just need a cleaner CRM or a simple $20/month SaaS product. You don’t need to force AI into every scenario.

Ship and Iterate Fast

Finally, stop chasing perfection. You won’t know what you don’t know until a system is live and exposed to real-world scenarios.

Focus on getting an MVP (Minimum Viable Product) or a Proof of Concept (PC) out there fast so it starts adding value. Real learning begins when the system is live and feedback starts rolling in. The formula for success is simple: 20% of your time building, 80% of your time understanding. Prompts give you output, but process gives you leverage.

Quick Recap of the 4 Keys to AI Automation Success:

It’s about Leverage, not full automation.
Depth in one area gets results, not juggling multiple tools.
Simplicity is what clients value, not complexity.
Understanding Business Processes matters more than the specific AI solution.

Read the full article here: https://medium.com/@aakash_7/youre-doing-ai-automation-wrong-fix-it-now-8b75a865ab5d