AI Adoption in Business: “Buy, Don’t Build”?
The “Buy, Don’t Build” conclusion is a bit of an oversimplification of the famous recent “State of AI in Business” report by MIT.
The study indeed found that companies buying AI solutions succeeded 66% of the time, while internal builds succeeded only 33% of the time.
But if you read the paper, it says the success gap is driven by learning capability, not procurement strategy.
Most internal AI builds create static systems that can’t adapt. They’re built once, deployed, and expected to work forever with the same prompts and processes. When they inevitably break down or produce inconsistent results, teams abandon them.
Successful external partnerships work differently. The best vendors build systems that learn from feedback, remember context, and improve over time. What they provide can be called adaptive intelligence.
This explains why ChatGPT dominates for quick tasks but fails at mission-critical work in companies. It’s excellent for one-off requests but forgets everything between sessions.
The companies crossing what the study calls the “GenAI Divide” are choosing learning-capable systems over static ones. Some build these internally, but most partner with vendors who specialize in adaptive AI.
So “buy versus build” is a bit misleading – it’s actually “learning versus static”.
Three questions for your next AI investment:
• Does this system learn from our feedback?
• Will it remember our preferences and context?
• Can it adapt as our processes change?
If the answer is no, you’re probably looking at another failed pilot, regardless of whether you build it or buy it.
