Buy AI tools, or build your own?

The decision rule is shorter than the tool listicles suggest: buy for generic capabilities, build when the workflow crosses your systems. Buying AI licenses is not a strategy, it is a receipt. What makes AI pay is the fit between the model and one specific workflow, and fit is exactly what off the shelf tools cannot promise.

	Buy a tool	Build into your stack
Right when	The capability is generic: transcription, drafting, meeting notes, generic chat	The workflow crosses your database, your email, your vertical systems
Time to value	Days	Weeks: sandbox by day 60, production by day 90
True cost	Licenses per seat, forever, plus the workflows it almost fits	Build cost plus model usage plus maintenance, owned once
Accuracy	Whatever the demo showed	Measured against your real cases before anything ships
When it breaks	A support ticket to the vendor	Your team reads ordinary code and fixes it
Failure mode	Shelfware: another portal your team ignores	Overbuilding what a $30 per seat tool already does well

The four questions that decide it

Does the workflow touch systems only you run? Does the output need your data to be right, not just plausible? Will the volume justify owning it? Is there a person who owns the output and can define good enough? Four yeses: build. Fewer: buy, or wait. Most companies should do both, in that order of scrutiny, and the ranked answer for your specific operation is what the AI Readiness Assessment produces in two weeks.

Not sure where you stand? The 20 question checklist takes one meeting, or download the free AI Readiness Playbook.