Make or buy: why building your own software costs more than it looks

The "build vs. buy" debate isn't new, but it resurfaces every technology cycle with the same arguments and, often, the same miscalculation: treating in-house development as a one-time cost, and buying software as a recurring subscription that piles up over time. In reality, both are recurring — only one of them shows up clearly on an invoice.

The myth of "free" in-house software

Software built in-house is never free, even when it doesn't show up on any dedicated budget line. It ties up engineering time that could have gone elsewhere, a maintenance load that grows with every new feature, and a security burden (dependency updates, vulnerability patches) that a SaaS vendor spreads across hundreds of customers while a single company carries it alone. Building an internal expense-tracking tool, for instance, looks like a finished project. In reality, it's a product that needs indefinite upkeep, with a single team absorbing the entire cost of ownership.

The technical debt nobody budgets for

The real risk of home-grown software doesn't show up at launch — it shows up two or three years later, once the engineer who built it has left and nobody fully understands how it works anymore. The tool keeps running, but every change gets slower and riskier, until it eventually gets treated as a black box nobody wants to touch. A software vendor, by contrast, has a dedicated team whose full-time job this is — continuity doesn't rest on one person.

The opportunity cost, the hardest one to see

Every week an engineering team spends building an internal reporting, expense-tracking, or contract-management tool is a week not spent on the product that actually generates revenue. That cost never shows up on any software spend dashboard — it appears nowhere, precisely because it isn't a cost, it's a forgone opportunity. It's often the strongest argument in favor of buying: a company that isn't a software vendor rarely benefits from becoming one, even for a single internal use case.

AI is speeding up vendors faster than it's speeding up in-house teams

AI coding assistants genuinely make building an internal tool faster — but they speed up SaaS vendors just as much, if not more, since vendors amortize that same productivity gain across hundreds or thousands of customers at once, rather than a single internal use case. Gartner forecasts that 40% of enterprise applications will feature task-specific AI agents by 2026, up from less than 5% in 2025 — a pace of innovation that an internal team, already busy running the company's core product, can't structurally match on a side tool.

Tougher competition between vendors means better pricing for buyers

McKinsey finds that enterprise adoption of AI agents is accelerating sharply, and Gartner already documents how multi-agent architectures are becoming a competitive differentiator among vendors. That shift works in the buyer's favor, not against it: the more vendors differentiate on AI rather than contractual lock-in, the easier it becomes to compare, renegotiate, or switch providers along the way — an option in-house software, by definition, never offers.

Buy, but keep control

The real risk of "buy" isn't the model itself — it's losing visibility into what's been bought over time: the same companies that choose to buy rather than build are also the ones that accumulate dozens of SaaS tools the fastest, without any overview. The right question isn't "should we buy," but "how do we buy without losing control" — a visibility problem, not an argument for building in-house.