How can Generative AI help you?

Small and medium-sized businesses often face the same problems: too little time, too little budget, and too much manual work that should really be automated. And then an IT vendor comes along and says: “We can solve that!” Followed by a five-figure quote and a six-month implementation timeline.

Sound familiar?

The reality of custom software

Let’s be honest: custom software has always been expensive. Rightfully so, because every line of code needs to be written, tested, documented and maintained. A simple web application to support your business processes? Easily 20,000 to 50,000 euros. And then you still don’t have integrations, no mobile app, and no fancy features.

For many SMBs, this meant: either you settle for a standard package that doesn’t quite fit, or you keep working manually in Excel and email. Both options are far from ideal.

And then came generative AI

I’m not an AI evangelist shouting that everything will be better and that developers will soon be obsolete. As I wrote in my earlier article: expectations and the right prompt are crucial. AI is not a miracle cure, but it is a game-changer for a specific category of problems.

Which problems?

Relatively simple business applications where:

• Requirements are clear
• It doesn’t concern critical systems (think: no financial transactions or patient records)
• Speed is more important than perfection
• Budget is limited

A concrete example

Take the “Notepad” I built for my wife. A planning tool for healthcare, because the standard package didn’t do what she needed. Instead of programming for weeks:

• 30 minutes spent setting up the context
• 15 prompts given to Claude Code
• Result: a fully functional single-page web app

Total cost if this had been a commissioned project: a few hundred euros instead of tens of thousands.

What does this mean for your business?

If your business is facing one of the following situations, generative AI could be a solution:

1. Excel madness

You have an Excel sheet that everyone uses, but nobody understands anymore. It contains macros from 2003, and every time someone goes on vacation, work stops.

AI solution: A simple web application that does what that Excel did, but accessible to everyone, with a clear interface.

2. The manual process

Every week you spend three hours copying data from one place to another. It’s annoying, error-prone, and a waste of time.

AI solution: A script or small application that automates this. No major integration needed, just practical automation.

3. The internal tool nobody builds

You’d like to have a tool with which employees can quickly look up, register or plan things. But it’s too small for a big software project and too specific for standard software.

AI solution: A custom-made tool, specifically for your process, without the overhead of a traditional development trajectory.

4. The proof-of-concept

You have an idea for a new service or product, but want to test if it works first before investing big.

AI solution: A working prototype within days instead of months, for a fraction of the cost.

What it CANNOT do

Let’s also be realistic. Generative AI is (IMHO) not (yet) a solution for:

• Complex, critical systems where security and reliability are essential
• Large, integrated platforms with dozens of users and complex workflows
• Mission-critical applications where errors are unacceptable
• Situations where you don’t know exactly what you want – garbage in, garbage out

AI makes good developers faster, but doesn’t replace them. And for complex projects you still need experienced professionals who determine the architecture and ensure quality.

The honest costs

Where traditional custom software quickly runs into tens of thousands of euros, I can often deliver a working prototype within a few days with generative AI for €1.000 to €5.000, depending on complexity.

Not because I’m cheaper, but because the technology enables me to work 5 to 10 times faster for certain types of projects.

This means that solutions that were previously financially unfeasible for SMBs are now suddenly within reach.

How does such a trajectory work?

Week 1: exploration (4-8 hours)

• Conversation about what you need
• Determine if AI development is the right approach
• Sketch the solution
• Agreement on approach and costs

Week 2-3: development (16-40 hours)

• Iterative building with regular feedback
• You see progress in real-time
• Adjust where necessary
• Testing with real users

Week 4: completion (4-8 hours)

• Final adjustments
• Documentation
• Possible training
• Delivery

Total: 24 to 56 hours instead of 200+ hours with traditional development.

A different way of working

The beautiful thing about generative AI is that it enables a different way of working:

Traditional: “Here are all the requirements, come back in 3 months.”
With AI: “Let’s start with the core, and review every week what else needs to be added.”

This provides much more flexibility and certainty. You don’t invest everything upfront, but build step by step, with the ability to adjust.

The nuance

I don’t want to be yet another person shouting that AI solves everything. It doesn’t solve everything. But for a specific category of problems – relatively simple, well-defined business applications – it’s a revolution in accessibility and affordability.

The question is no longer: “Can we afford this?”
The question is: “Have we defined this well enough to have it built?”

Do you recognize this?

If after reading this article you think: “Actually, we have such a situation too…”, then it might be worthwhile to explore whether generative AI offers a solution.

No promises of paradise. No buzzword bingo. Just honestly looking at whether the technology fits your problem, and if so, solving it quickly and affordably.

That’s what it’s about: pragmatic solutions for real business problems, without the bullshit.

Interested in exploring whether generative AI can help your business? Get in touch for a no-obligation conversation. I’ll tell you honestly whether it’s a good fit – or not.