Understanding the Real Problem in AI Initiatives

When someone explains a problem to you, the words they use feel like the problem itself. In a sales conversation, a customer says what is wrong, you write it down, and the rest of the process is built around that sentence. The sentence becomes the anchor for proposals, meetings, and decisions.

This article examines why that sentence is often a poor guide to what actually needs fixing. It also shows how to tell the difference between the problem as it is described and the problem as it exists in the work. The source makes a direct claim here: sales conversations almost always produce a stated problem that is not quite the real one. The word almost matters, because it tells you this is the normal case rather than an occasional accident.

The key point is that these are two different objects, even when they are about the same situation. The stated problem is something a person said. The real problem is something that is true about the work. Keeping these apart matters because a sentence can be accurate as a description of how someone feels about a situation while still missing the mechanism that produces the difficulty.

Describing a problem is not a neutral act. Each person who speaks about a problem passes it through their own position, their incentives, and their expectations about what a solution could look like. The result is usually useful but incomplete. Read as a chain, the problem is reshaped at each handoff: first by the person doing the work, then by the decision-makers above them, and finally by the vendor who hears the summary in a sales conversation.

Notice what is lost along the way. The person doing the work knows which steps repeat, which files change hands, and where things stall. By the time the problem reaches a vendor, that detail has usually been compressed into a sentence about goals. The sentence is easy to repeat, and that is exactly why it can drift so far from the work.

The source names three forces that push a stated problem away from the real one. They can operate separately or together, and each is worth understanding on its own. Together they explain why the sentence a customer speaks so rarely matches the work underneath it. The concept map below shows how each force pulls on the stated problem, which in turn sits at some distance from the real one.

The following scenario is an original illustration written to show how the two kinds of problem can diverge. It is not drawn from the source, so treat the specific details as invented teaching material that follows the source's principles.

The source observes that people often speak in the language of the executive summary rather than the language of the workflow. An executive summary compresses a process into outcomes, categories, and conclusions. A workflow is made of concrete actions, handoffs, files, and repeated steps. The same problem sounds very different in each register.

This difference is useful as a diagnostic signal. When a description uses broad outcome words, the real problem is probably still hidden inside the process. When the description names specific steps, people, and tools, the stated problem is probably closer to the work.