Last checked: 7 November 2026
In short: Build vs buy AI is the choice between creating an AI tool in-house, with your own staff or developers, and paying for a ready-made product from a supplier. Many firms end up mixing the two.
Table of Contents
How it works
- Define the need. Write down the task, the data involved and how much it matters to your edge over rivals.
- Compare options. Price a ready-made tool against the cost of building and running your own, including staff and upkeep.
- Decide and review. Often firms buy for common tasks and build for unique ones, then review as products change.
Where you’ll meet it
Buying means tools such as Microsoft Copilot, ChatGPT Enterprise or the AI features inside Salesforce. Building often means connecting a model such as Claude or Gemini to your own data through an API.
What it means for your business
- Buy for common jobs. Email drafting, meeting notes and standard support are cheaper to buy than to build.
- Build where you differ. Consider building only where your data or process gives you an advantage.
- Count running costs. A home-built tool needs people to fix, secure and update it for years.
Watch out for
- Hidden effort. Building looks cheap at the start, then maintenance grows.
- Supplier lock-in. Bought tools can raise prices or change features, so check contracts and data export terms.
Example
Klarna. In August 2024 Klarna told investors it had shut down Salesforce as a provider and expected to drop Workday too, linking the move to AI. Its chief executive, Sebastian Siemiatkowski, later clarified that “we did not replace SaaS with an LLM”. Klarna had combined its data, built some tools of its own and moved other work to suppliers such as Deel.
Build vs buy AI vs AI strategy
| Build vs buy AI | AI strategy | |
|---|---|---|
| Scope | One sourcing decision per tool | The firm’s overall plan for AI |
| Decides | Make it or pay for it | Where AI should help and why |
| How they relate | A choice made inside the strategy | The plan that guides the choice |
Frequently asked questions
Is building AI only for large companies?
Mostly. Building and maintaining tools needs developers, data skills and budget. Small firms usually buy, then add small extras with low-code tools or simple API connections.
Can you start by buying and build later?
Yes. Buying first lets you learn quickly what works. Once you know which tasks matter most, you can build for those and keep buying for the rest.
What costs do people forget when building AI?
The ongoing ones. Model usage fees, security checks, fixing errors, updating for new models and the staff who keep the tool working all continue after launch.