When to use AI to build your product vs. AI in your product

At Livewall we hear a version of the same question regularly: 'Should we add AI to our product?' What people mean by that varies enormously. Sometimes they're asking about using AI during the build, to develop faster and smarter. Sometimes they mean embedding AI as a feature in the product itself, something the end user directly experiences.

Those are two fundamentally different decisions. They require different trade-offs, different investment, and different expertise. Conflating them wastes time and budget.

The first decision, AI as a build tool, is in our experience almost always worth exploring. We use AI in rapid prototyping, generating boilerplate code, writing test scenarios, and accelerating iteration cycles. It lowers the barrier to getting something working. Our MVP development process has become faster and more affordable as a result, without compromising on quality.

AI as a product feature: a different question, a higher bar

Building AI into a product as a feature is a separate decision entirely. The question shifts from how you build to what the product does for the user. And the bar is higher: does this solve a real problem, or are you adding technology because you can?

For InShared we built an AI-driven visual platform that generates on-brand imagery at scale. The AI sits inside the product, and the value is direct: less manual work, more consistency across a large content operation. For KLM Scalable Growth we built an AI workflow that accelerates campaign production across 50+ markets. There, AI lives partly in the production process and partly as logic inside the system itself.

That distinction matters. At Mach8, our sister label for AI automation, the pattern is consistent: the AI applications that work start with a specific process that is too slow, too expensive, or too error-prone. Not with a desire to 'do something with AI'.

For Zorg van de Zaak we built a B2B platform that matches health interventions to the right employees using smart logic. It could have included AI, but the complexity wasn't justified at that stage. Sometimes a well-designed algorithm is enough. The choice to add AI as a product feature should always come back to one question: does this make the product measurably better for the user?