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My family wanted an application to help us coordinate work around the house.
We wanted a reward system, family goals, calendar information and some meal-planning capability. Maybe my daughter earns enough points to choose the movie. Maybe we all hit a goal and go to the lake.
There were products that solved pieces of the problem.
I could not find one that fit the way we wanted everything to work. To be honest, I also did not want to pay for several tools and still end up with a partial solution.
So I built it.
Using AI, I put the application together in less than a day. We figured out how to host it cheaply, and now we have something designed around our family.
The best part is that when we want another capability, I can add it.
That is a small personal example, but I think it points to a major change in software.
AI is changing the traditional build-versus-buy decision by lowering some of the barriers to creating targeted software. Organizations still need to consider security, maintenance, scale and ownership, but AI can make building a focused internal solution realistic in situations where custom software might previously have been too expensive or difficult to justify.
AI makes targeted software cheaper to create
For years, the build-versus-buy decision started with the assumption that custom software was expensive.
If no commercial product fit the workflow, the organization often had to accept the limitations, invest heavily in customization or change the workflow to match the product.
AI is changing the labor side of that decision.
People with domain knowledge can increasingly participate in creating targeted solutions. They may not be able to build a massive commercial platform, but they can solve a narrow problem that is valuable to them.
The application does not need to satisfy an entire market.
It only needs to solve the problem it was designed for.
I have seen the same thing happen in business
One organization needed a threat-modeling tool that fit its workflow.
Commercial platforms existed, but they did not align well enough with what the organization wanted. The available products would have required cost, compromise and changes to the existing process.
The organization had a community of security champions and access to AI.
So they built what they needed.
That does not mean the tool was free or that ownership came without responsibility. Someone still has to maintain it, secure it and make decisions about how it evolves.
But the option to build had become realistic in a way it might not have been before.
This is not an argument to replace every vendor
Commercial products still provide significant value.
A vendor may offer scale, support, maintenance, security expertise and years of development that an internal team cannot reasonably reproduce.
There are also systems that are too sensitive or too central to treat as quick internal projects.
The point is not that buying software is now the wrong answer.
The point is that the calculation has changed.
A small internal tool that would once have been too expensive may now be practical. An organization may be able to build around its workflow instead of reshaping the workflow around a vendor’s assumptions.
“It has AI” is no longer enough
AI is becoming a standard feature in software.
Having an assistant, copilot or agent inside the product is no longer a meaningful differentiator by itself.
The question is whether the product solves the problem.
Organizations should be careful when the person explaining the urgent AI problem is also selling the platform that supposedly solves it. That does not mean the product has no value. It means the company needs enough internal capability to evaluate the claim.
Does the tool fit the workflow?
Does it work with the information we have?
What measurable result should it improve?
Could we solve the problem more simply?
Would a small internal solution be more appropriate?
An AI-literate workforce is better prepared to answer those questions.
The value is having another option
Sometimes the right answer will still be to buy.
Sometimes it will be to build.
Sometimes the organization will realize the problem never required AI in the first place.
The important change is that people have more options than they did before.
AI is lowering the cost of creating software around specific needs. That gives organizations an opportunity to rethink not only how they buy technology, but how closely the technology should fit the work.
The build-versus-buy decision is not disappearing.
It is becoming more interesting.
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