Everyone is excited about AI building business software. You should be, too. But there’s something important nobody is saying. In the last few weeks, I have had more conversations about AI building business software than in the entire previous year combined.
The excitement is valid. The possibilities are real, but there is a gap between what people are seeing in demos and what happens when a real business depends on that tool six months later.
That gap is what I want to talk about.
There are internal tools and operations systems for small and medium businesses. Some are learning to use AI every single day in my work.
It makes the user faster at work.
It helps to deliver better results for clients. I am not here to tell you AI is overhyped.
You are reading what is on the ground, so you can make decisions that actually protect your business.
What AI can genuinely do right now, and do almost perfectly well.
It can generate scripts, automations, and formulas that used to require a developer.
It can help a non-technical founder prototype an idea and visualise what they want to build.
It can build simple, single-purpose tools quickly.
It can cut a developer’s build time by 30 to 50 per cent.
It can explain technical concepts so that founders can make smarter decisions. That is real value. Celebrate it.
What AI still cannot do reliably:
It cannot build secure multi-user systems with proper roles and permissions without significant technical oversight.
It cannot understand your actual business logic; the exceptions, the edge cases, the way your team really operates on the ground.
It cannot maintain a live system when your business evolves, and requirements change six months from now.
It cannot integrate cleanly with local payment systems, Nigerian banking APIs, or the existing tools your business already depends on.
And critically, it cannot tell you when the requirement you gave it is wrong, incomplete, or will cause serious problems later.
This last point matters more than people realise.
What to always bear in mind:
AI builds what you describe. Not what you need.
If you do not know how to specify a system correctly, the output will reflect your gaps, not your goals. And this brings me to something nobody is saying out loud.
Most of the impressive AI-built tools you are seeing right now were not built by the business owner sitting alone with a chatbot.
There is a person behind the process. The real question is: what kind of person?
There is a difference between someone who prompts AI until something looks good and someone who understands the system they are building.
Both can produce a beautiful interface, but only one of them knows whether the database structure will hold when transaction volume doubles.
Only one of them catches the security gap in the authentication logic before it becomes a breach.
Only one of them can look at what AI-generated and say, “This is wrong, and it won’t scale,” and here is why only one of them can maintain, update, and evolve the tool as your business grows.
Looking good on a screen is not the same as working reliably in your business as you scale.
Now, here is what actually happens in practice: A founder gets a tool built. It works beautifully for a while. Then an edge case breaks it.
A staff member enters data in an unexpected format. Two users try to edit the same record simultaneously.
The business logic does not hold when volume increases, and there is nobody to call, or the time cost turns out to be hidden ─ prompting, testing, fixing, and re-prompting.
Building something truly reliable with AI alone can quietly consume weeks, whereas someone who understands the system would have resolved it in days.
The question was never AI versus developers. That is a false choice.
The real question is: do you understand your problem clearly enough to know which tool it needs, and who should be holding that tool?
A hammer and a scalpel are both useful. Knowing which one your situation requires and putting it in the right hands is the actual skill.
AI is an extraordinary tool. I personally consider it to be one of the best things to have happened in our generation. That said, it is not yet a replacement for someone who understands your business deeply, asks the right questions, and takes responsibility for what gets built.
When you need something your whole team will depend on, something like handling real money, real client data, and real operations, accountability matters.
Nobody is accountable to you when the system breaks at 8am on a Monday and your team cannot log a single transaction.
Anyone can describe what they want and accept what AI produces when it comes to building a product, but a technically skilled person reads the output critically and knows when it’s wrong before it causes problems.
That gap shows up in security. AI will generate an authentication code that looks fine but has vulnerabilities a non-technical person cannot spot.
It shows up in database design. A poorly structured system works at 50 records and breaks at 5,000.
It shows up in integrations. Connecting to Paystack or Nigerian banking APIs requires handling edge cases that AI often gets wrong.
It shows up in maintenance when the tool breaks. Specifically, a non-technical person goes back to AI and hopes for the best. A technical person diagnoses and fixes.
As you feel excited about using AI to build your business software, bear these issues in mind.
Barakat Awoyemi, the founder of Barola Technologies Ltd and a business systems developer, writes via [email protected]