Understanding the Top-Five-Priorities Filter
The first filter for an AI project is whether the problem is one of the customer's top five priorities; the source says that if it is not, the engagement will fail.
A Good System That Never Ships
Imagine a team that has built an AI system which works well in testing. The model is accurate, the code is clean, and the demonstration impresses everyone who sees it. Yet the project never reaches daily use. Nothing in the technology is broken. This article answers two questions: why a well-built system can still fail, and what the source identifies as the first thing to check before effort is spent on building it.
The source puts the answer bluntly. The success of an AI project depends on its alignment with the organization's top priorities. Before asking whether the technology can work, a proposal has to be tested against what the organization has decided matters most. That test is the first filter, and it is the subject of everything that follows.
Tracing a Proposal Through the First Filter
The following scenario is an illustrative example written for this article, not a case from the source. It shows how the first filter is applied step by step. At each step, decide whether the proposal is still on track.
A proposal that reaches the priority check
A data team proposes an AI system that drafts routine status summaries. The model is accurate in testing. Does the proposal pass the first filter?
- 1Identify the problem the project addresses
The filter is a test applied to the problem, not to the technology. The first question is what business problem the project solves, here producing routine status summaries.
- 2Check the problem against the customer's top five priorities
Ask whether this problem appears among the customer's five most important priorities. Suppose leadership's list names other concerns and this problem is not among them.
- 3Apply the source's rule to the answer
The source is clear that if the problem is not one of the top five priorities, the engagement will fail. The model's accuracy does not change this outcome, because the filter comes before the technical evaluation.
The proposal fails the first filter and is likely to stall, however accurate the model is. Had the problem been high on leadership's list, the proposal would pass this filter and move on to the rest of the work, which still does not guarantee success.
What the Filter Actually Tests
The first filter for an AI project asks whether the problem is one of the customer's top five priorities. If it is not, the source says the engagement will fail.
The filter is a test you apply to the problem, not to the technology. It is applied before any question about whether the model works. It comes first because it decides whether the rest of the work has a path to production at all. A problem that fails this test has no route to deployment, so effort spent on the model cannot change the result.
Why the Test Is Organizational
The source gives its reason in one phrase: the reason is organizational physics, not technology. The point is that a project's fate is set by people and institutions, not only by the quality of the model. A system that is technically correct still has to be deployed, and deployment changes how an organization works.
This is why the filter asks about priorities. Changes that touch processes, systems, and daily routines are costly for an organization to absorb. The source notes that none of the support production deployment requires happens for problems that are not high on leadership's list. Priority is what makes the organization willing to spend the attention and political capital that deployment demands.
| Question | Technical view | Organizational view (the filter) |
|---|---|---|
| Is the system sound? | Is the model accurate and the code clean? | Does the problem matter enough for leadership to act on it? |
| What decides success? | Quality of the model and code | Alignment with the organization's top priorities |
| What is the risk? | A bug or weak model | A well-built system that never reaches daily use |
| What must change? | The software | Processes, systems, and daily routines |
The same proposal looked at through a technical lens and through the organizational lens of the first filter.
Four Groups Deployment Depends On
Once a problem has passed the first filter, the source describes what it takes to put an AI system into production. Four groups must act, and each contributes something different. The diagram below shows how these requirements connect to deployment.
The four groups are described in the sub-sections below. Each one is a separate requirement, so a project can lose momentum when any single group is missing.
Mistakes When Applying the Filter
Common mistake Treating a high model accuracy as proof that the project will succeed
What it looks likeA team reports a strong test score and assumes the project is on track.
Why it failsThe filter tests the problem against organizational priorities. A technically sound system can still fail to reach production.
Do this insteadCheck the first filter before judging the project's prospects by its technical results.
Common mistake Assuming that passing the filter guarantees success
What it looks likeA proposal clears the priority check and the team stops thinking about deployment.
Why it failsPassing is a necessary starting condition, not a guarantee. The four groups must still act.
Do this insteadAfter passing, check whether senior leadership, legal and compliance, the IT function, and the line workforce are each prepared to contribute.
Common mistake Applying the filter to the technology instead of the problem
What it looks likeA team asks whether a new model type is impressive enough to win priority status.
Why it failsThe source frames the filter as a test of the problem against the customer's top five priorities.
Do this insteadAsk whether the problem the system solves appears among the customer's five most important priorities.
Common mistake Ignoring the line workforce because the project was approved at the top
Predicting Whether a Project Will Stall
What do you think happens?
A proposal passes the top-five-priorities filter. Will it certainly reach daily use?
Reveal answer
No. Passing the filter is a necessary starting condition; it does not by itself guarantee success.
The project must still gain sustained senior leadership attention, legal and compliance agreement to the process change, IT function access to systems, and line workforce acceptance of daily routine changes.
A team proposes an AI system to improve a problem that leadership has never listed among its priorities. The model performs well in testing. Predict whether the project is likely to stall, and name the first filter result that supports your prediction.
Hints
- Start with the first filter, before considering the model's performance.
- The source says that if the problem is not one of the top five priorities, the engagement will fail.
- Model accuracy is an organizational-independent result, so it cannot rescue a project that fails the first filter.
Key Takeaways
- The first filter asks whether an AI problem is one of the customer's top five priorities; the source says a project that fails it will fail.
- The filter is organizational rather than technical: a technically sound system can still fail to reach production because deployment changes how an organization works.
- Production deployment requires senior leadership attention over months, legal and compliance agreement to a process change, IT function access to systems, and line workforce acceptance of daily routine changes.
- Passing the filter is a necessary starting condition, not a guarantee of success.