Every operations leader dealing with AI right now faces the same early decision: do we buy a platform or build something ourselves? The question sounds simple. The answer is more nuanced than most vendors want it to be.
The default instinct is to buy. Procurement feels safer. There is a demo, a contract, a vendor to call when something breaks. Building feels risky and expensive. But the calculus has shifted in the last two years. Building is faster and cheaper than it used to be, and the hidden costs of platforms are larger than they appear in the sales deck.
Here is how to think through the decision clearly.
What "Buy" Actually Means Now
The AI platform market has fractured into three distinct categories, and they are not the same thing even though vendors often blur the lines.
General AI platforms like Microsoft Copilot or Google Workspace AI are embedded into tools you already use. They handle commodity tasks: summarizing documents, drafting emails, generating first cuts of reports. They are broadly useful and broadly shallow. They do not touch your workflows. They assist the people inside them.
Point solutions target specific verticals. A healthcare platform for clinical documentation, a legal platform for contract review, a finance platform for expense categorization. These go deeper than general platforms but narrower. They work well when your problem matches their intended use case and poorly when it does not.
Agent builders are the newest category. Platforms like Relevance AI, Lindy, or Microsoft Copilot Studio let non-engineers assemble agents from prebuilt components. They are flexible but surface-level. You can connect to your systems, but the logic is constrained to what the platform's building blocks support. Anything outside that requires workarounds or custom code, at which point you are essentially building anyway, just with more overhead.
The Hidden Cost of Platforms
Platform pricing looks reasonable in year one. It stops looking reasonable in year two.
Per-seat pricing scales badly. A tool that costs $50 per user per month is $60,000 per year for a hundred-person team. That number does not include the implementation cost, the integration work your IT team has to do, the ongoing configuration as your workflows change, or the consultant the vendor recommends you hire to get full value from the product.
Integration tax is real. Every platform promises integrations with your existing systems. What they mean is that they have a connector. What the connector actually does, how deeply it reads your data, what it can write back, how it handles edge cases, is almost always more limited than the demo suggested. Getting a platform to work the way your workflow actually runs takes engineering time, and that time does not appear in the per-seat price.
Lock-in compounds over time. The longer you run on a platform, the more your team builds institutional knowledge around its quirks, the more your processes bend to fit its constraints, and the harder it becomes to leave. When the platform raises prices, adds a tier above you, or deprioritizes features you depend on, your options narrow.
When to Buy
Buying a platform makes sense in three situations. The workflow you are trying to automate is genuinely commodity: something thousands of businesses do the same way and for which a well-established platform exists. The problem fits the point solution closely enough that minimal customization is needed. Or the expected volume is low enough that a monthly subscription is cheaper than a build, even accounting for all the hidden costs above.
If you are spending under $500 per month solving a problem that a platform handles well, buy the platform. The economics favor it. Use your engineering resources elsewhere.
The test is fit. Does the platform do what you need out of the box, or does getting to your actual workflow require a sequence of workarounds? If the sales demo required the AE to say "we can customize that" more than twice, that is a signal.
When to Build
Building is the right call when your workflow is proprietary, when getting it right creates a competitive advantage, or when the cost at scale makes the platform math ugly.
Proprietary workflows are the clearest case. If your intake process, your underwriting logic, your compliance review criteria, or your claims triage rules reflect years of institutional knowledge specific to your business, a generic platform is not going to capture that. You will spend months trying to make the platform fit, and you will end up with something that is worse than what you had before, plus a recurring subscription.
Competitive differentiation is the second case. If the thing you are building is actually part of what makes your business better than competitors, putting it on a shared platform means the platform vendor can offer the same capability to your competitors tomorrow. Owning the code means owning the capability.
Scale math is the third. Run a simple projection: if the platform costs X per month now, what does it cost in three years at twice the volume? Compare that against the annualized cost of a custom build amortized over three years. For many organizations with meaningful transaction volume, the custom build pays for itself inside 18 months.
The Middle Path: Build with a Partner, Own the Output
The part most organizations miss is that "build" does not have to mean "hire a full engineering team and spend six months in a requirements process." The build vs buy framing has a third option that has become viable: commission a custom build from a specialist, get it delivered in weeks, and own the code outright.
This approach gives you the output of a build without the organizational overhead of running a software project. You get something tailored to your workflow. You pay a fixed price for a defined scope. When the project ends, you own what was built. There is no ongoing license fee. There is no platform lock-in. If something needs to change in a year, you change it.
The tradeoff is that you need to maintain what you own. That means someone on your team understands it well enough to manage it, or you have a relationship with the team that built it for ongoing support. That is a real responsibility. But for most organizations, it is a much better problem to have than dependency on a platform that does not quite fit.
Five Questions Before You Decide
First: is this workflow standard or proprietary? Standard workflows with off-the-shelf fits point toward buying. Proprietary logic points toward building.
Second: what is the three-year total cost of each path? Include implementation, integration, customization, and scaling in the platform number. Include build cost, maintenance, and support in the custom build number. The honest comparison usually surprises people.
Third: does getting to your actual workflow require significant customization of the platform? If yes, you are already halfway to building. You might as well own the result.
Fourth: would a competitor benefit from this capability? If yes, owning the code matters more than the cost difference.
Fifth: what happens if the platform changes its pricing or discontinues the feature you depend on? If the answer is "we are stuck," that is a risk worth pricing into the decision now rather than discovering it in two years.
Most of the time, the right answer is clear once you work through these questions honestly. The mistake is skipping the analysis and defaulting to whichever path feels more familiar.