Two pieces of advice get handed to every team starting with AI. "Just buy a tool, do not reinvent the wheel." And "build your own, that is your moat." As blanket rules, both are wrong. The right answer depends on whose problem you are solving.
Buy when the problem is common
If thousands of companies have the same need, transcription, email, scheduling, general-purpose chat, someone has already built it better than you will, and they maintain it for a living. Buying is faster, cheaper, and lower risk. Reinventing it is ego, not strategy.
Build when the problem is yours
Build when the workflow is specific to how your business runs, when stitching your existing systems together is the hard part, when an off-the-shelf tool would force you to change how you work, or when your own data is the advantage. In those cases a generic tool will always almost fit, and almost fitting is its own expensive problem.
A test that settles it
Ask one question: can you get eighty percent of the result from an off-the-shelf tool without changing how you work? If yes, buy it and move on. If the last twenty percent is exactly where your advantage lives, build that part and integrate the rest. You rarely have to choose all-build or all-buy.
- Buy: the need is common, the tool fits your workflow, the data is not your edge
- Build: the workflow is specific, integration is the hard part, the data is your advantage
Buy the commodity. Build the part that is yours. Integrate the rest.
Our consulting work starts here, with build-versus-buy called for each opportunity, because building the wrong thing costs far more than any subscription.