# From Renting Software to Owning It: What Changes When AI Makes Building Cheap

# From Renting Software to Owning It: What Changes When AI Makes Building Cheap

**By Jaime Vasquez — founder of HUBi Studio, an AI Development Studio based in Edmonton, Alberta, building custom software for businesses across Canada.**

What's actually changing about business software?

For twenty years, most businesses got software the same way: they picked a SaaS product and adapted their own workflow to fit it. That's changing. A 2026 survey of 817 Retool customers and builders found that 35% of teams have already replaced at least one SaaS tool with something they built themselves, and 78% plan to build more this year — 60% of it outside official procurement, as shadow IT (Retool, 2026 Build vs. Buy Report). The shift isn't about a new app category. It's about who gets to decide how a business runs day to day.

Why did companies adapt themselves to software for so long?

Because building your own was expensive, and the expense was structural, not optional. Every rule a business used to make a decision, every exception a staff member handled by memory, had to be manually translated into code by someone who understood both the business and the codebase. That translation cost is what SaaS solved — at the price of the business bending itself around a product built for everyone, not for them.

What changed the economics of building your own?

AI collapsed the cost of that translation. A business no longer has to start from a blank screen to get software that fits how it actually operates. It can start from something it already has: its own blueprint — how it sells, how it serves customers, how it handles the exception nobody wrote down. For decades that knowledge lived in spreadsheets, in meetings, in the heads of the people who'd been there longest. The new part isn't that AI can write code. It's that a business's own operational knowledge can become the software, instead of a generic tool the business has to adapt to.

Does cheaper mean it works once it ships?

Not automatically, and this is the part that gets skipped in most of the "anyone can build now" conversation. A 2026 survey of 200 SRE and DevOps leaders at enterprises in the US, UK, and EU found that 43% of AI-generated code still needs manual debugging once it reaches production, even after passing QA and staging (Lightrun, State of AI-Powered Engineering 2026). Generating a working demo and shipping a system that survives real customers, real load, and real exceptions are two different skills. Building got cheap. Finishing didn't.

A tourism platform in Japan previously managed operations using spreadsheets, PowerPoint, and other tools. Working with us, the client now uses a system to gather travellers’ intentions, budgets, and destination cities, after which the system generates the necessary materials. Presentations are delivered to the client’s email, shared with the budget team and planning group, and stored internally, while the webpage serves as the front end where clients build their plans at no cost.

Should a business build this itself, or bring in someone who does it with them?

There are two real paths, and neither one is wrong.

Some businesses have the internal skill to turn their own blueprint into software directly — that's the Retool survey's shadow-IT number in practice: operations and product people building their own internal tools with AI, without waiting on a formal dev cycle.

Other businesses understand their operation in detail but don't have that internal capability, and don't want to build it just to ship one system. For them, the value isn't in who types the code — it's in someone who can sit with the business, understand the blueprint accurately, and turn it into software that holds up. That's closer to what an architect does: the client's judgment about how they want to live in the house doesn't disappear because someone else draws the plans and pours the foundation.

[FOUNDER EDIT POINT: name a real client whose "blueprint" (a specific workflow, exception, or decision pattern) became the actual spec for what you built — the concrete before/after]

Is SaaS going away?

No, and it shouldn't. SaaS still wins for standardized problems where a business genuinely doesn't need to be different from its competitors — payroll, email, the tools where sameness is a feature, not a compromise. The 35% replacement figure above is concentrated exactly where you'd expect: workflow automation, internal admin tools, and BI — the places where the gap between what a generic tool offers and what one specific business actually needs is widest (Retool, 2026).

So what's the real question now?

It used to be "which software should we buy?" For a growing number of businesses, it's becoming "which parts of our operation are worth owning as software, instead of renting as a feature list someone else controls?" That's not a question every business needs to ask about every process. But for the parts of a business that are genuinely its edge — the workflow, the exception-handling, the judgment that took years to build — it's worth asking once.

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*If you want to see what your own operation looks like translated into software, [hubi.ca/start](https://hubi.ca/start?utm_source=blog&utm_campaign=thesis) runs a free analysis — no pitch, just the tool.*