7 common mistakes that companies make when developing AI solutions

In practice, we see countless reasons why AI projects and automations fail during the execution phase.

In this article, we discuss seven common mistakes companies make and how to avoid them.

1. Overcomplexity

What we see in practice is that the better a project is, the clearer and simpler it is. A good project or a strong solution is not the one with the most features and frills, but the one with a robust, solid foundation.

Too many features and 'nice-to-haves' make solutions unnecessarily complicated. They also cost your company a lot of extra money, while often adding little extra value.

So feel free to sketch out your ideal solution with all the ideas and functionalities you can think of, but then take a red pen and cross out everything that is not absolutely necessary to deliver a workable product.

What remains, you build first. And only when that runs successfully, do you gradually add the nice-to-haves.

2. Choosing the wrong partner

Choosing the right partner for your technical projects is likely the most important decision you will make.

If you choose the wrong one, you end up with frustration, wasted investments, and lost time, energy, and money.

If you choose the right one, it brings huge benefits: more efficient solutions that accelerate your growth, lower costs, and more time and energy to invest where it really counts.

So don’t rush into a collaboration if it doesn't feel right. Ask critical questions and trust your instincts. Does it feel right and logical? Go for it. If not, be cautious.

3. Poor communication

Regular updates and short communication lines are crucial for delivering projects that truly help your team and create value for your organization.

Projects without good communication quickly turn into an elusive black box and often lead to products that do not meet your needs.

Therefore, ensure that the communication structure and feedback loops are clearly established before the start of the project.

4. Hasty development

Before you start development, you need a solid and validated plan.

If you start without clear specifications and a clear Scope of Work (SoW), you are asking for trouble.

Make sure that before you enter into a collaboration, you have a concrete document stating exactly what is being developed, what the definition of “done” is, what timelines and investments apply, and what other important details are relevant.

5. Forgetting end users

An extra tip that ties into the previous point: involve end users in the scoping, concept, and testing phases.

There is nothing more painful than designing and building a solution that ultimately isn’t used.

Therefore, regularly share updates, ask for input, and allow users to test and provide feedback.

After developing more than 200 solutions, we can tell you: skipping this is one of the most expensive mistakes you can make.

6. Poor documentation

Another painful mistake is inadequate documentation. A project can be perfectly developed, but if the handover is not done well, it leaves a poor impression nonetheless.

Ensure that upon delivery you receive clear training or onboarding (you and your team), that the solution is hosted in your own accounts, and that for coded projects you receive documentation that explains the structure of the codebase.

Companies that skip this step often become too dependent on their development partner and lose flexibility. And that is something you definitely want to avoid.

7. AI obsession

The last, and perhaps most common mistake: too much focus on AI as a magic bullet.

The reality is that not every problem or process needs AI.

Sometimes a well-coded automation or another software solution is much more effective and suitable, for instance when predictability is important.

Always look at technology from the perspective of the process, and choose what fits best.

Do not be convinced to use a certain technology just because that is the only thing an agency can build.