If AI Makes Software Faster, Should Clients Pay Less?

I’ve been using AI heavily in software development for a while. Now that I run a software agency, one question keeps coming back.

If something used to take a developer five days and now takes two, what should the client pay?

My first instinct is less. If the effort has genuinely fallen, it feels difficult to argue that the client should never see any of the saving.

But the more I’ve thought about it, the less I think faster code gives us the whole answer.

How the work was sold matters. On time and materials, it is fairly obvious. If something takes two days, the client pays for two days.

Fixed-price work is different. The agency agreed to deliver an outcome and took the risk that it might take longer than expected. If it finds a better way and finishes early, I think it is reasonable for the agency to keep some of that benefit.

What doesn’t really work is knowing the job now takes eight days and continuing to quote twenty next time.

#AI is fast. That doesn’t mean the work is finished

I use these tools myself. They can explore an unfamiliar codebase, trace how something works, produce a decent first pass and write tests without starting from a blank screen.

The difference is real.

The thing is, someone still has to decide whether the answer is any good. Does it solve the right problem? Does it fit the rest of the system? Has it copied a pattern that looks right but is wrong here? What happens when it meets real production data?

Sonar’s 2026 State of Code survey asked more than 1,100 developers about their use of AI. They estimated an average personal productivity gain of 35%, but only 4% said they completely trusted AI-generated code to be functionally correct.

That feels about right to me.

AI can produce a convincing answer very quickly. Sometimes it has genuinely removed hours of work. Other times it has moved the work into checking, testing and correcting what it produced.

At this point in my career, I spend less time typing code and more time judging it. Twenty years of experience is more useful when I’m deciding whether an approach makes sense than when I’m writing another controller by hand.

That judgement still takes time. More importantly, somebody still owns what happens when the software goes live.

#So where should the saving go?

I don’t think there is one neat pricing model that suddenly fixes this.

If the work is clear and repeatable, fixed pricing makes sense. The agency can improve how it delivers, the client knows what it will pay and the agency keeps some of the upside if it performs well.

Product work is often less tidy. Sometimes neither side knows what will be uncovered until the work starts. Charging for a team or an agreed amount of time can still be the honest answer because the uncertainty is real.

Either way, clients should benefit when AI makes delivery faster. That could be a lower price, an earlier launch, more useful work within the same budget or more time spent testing the thing properly.

I also think the agency needs to benefit. Using AI well involves more than buying a licence. Teams have to change how they work, review more carefully and know when not to trust the answer. The agency is still responsible if it gets that wrong.

My view at the moment is that clients should not expect every AI-assisted project to cost half as much. Faster code is not the same as cheaper software.

But agencies cannot pretend nothing has changed either. If we know something that used to take twenty days now takes eight, we should not keep quoting twenty.

That part seems fairly obvious.