• The Midas Report
  • Posts
  • The Boring AI Strategy That Quietly Wins While Everyone Else Chases the Hype

The Boring AI Strategy That Quietly Wins While Everyone Else Chases the Hype

3 min read.

Author

Midas AI Research
July 22, 2025

While most executives race to show off the flashiest AI demo or chase the latest model release, a quieter group is running laps around the field.

They are not building chatbots or trying to clone ChatGPT. They are automating tedious work. They are solving boring problems. And they are seeing up to five times the return on investment.

This is not a theory. It is real data.

A new report from DataRobot and MIT Sloan shows that although nearly eighty percent of enterprise leaders rank AI as a top priority, more than half of AI initiatives stall before ever reaching production.

Why? Because they confuse innovation with distraction.

Most AI Projects Never Make It Out of the Lab

The data is clear.

Companies are running pilots. They are building prototypes. They are getting press.

But they are not deploying.

They are not aligning business and technical teams. They are not measuring the right outcomes. And they are not shipping products that actually work.

This is not a funding problem or a talent gap. It is a focus issue.

Most teams build for what looks good. Not what gets used.

The Winning Playbook Looks Completely Different

Here is how the top performers do it.

They start with one high friction workflow. Something simple but painful.

It might be expense approvals. It might be internal reporting. It might be routing support tickets.

They build a narrow tool to automate that single task.

Then they measure one thing. Time saved. Error rate. User satisfaction.

If the result is strong, they roll it out company wide.

If not, they stop. And pick a better target.

This is not about being right the first time. It is about moving fast with focus.

Invisible AI Is the Most Powerful AI

Forget avatars. Forget fancy interfaces.

The most impactful AI in production today is invisible.

It filters email. It categorizes documents. It extracts data from PDFs.

It runs inside CRMs. It works inside customer support tools. It powers dashboards that nobody even knows are smart.

And that is why it scales.

It does not require training. It does not require culture change. It just works.

And when it works, it sticks.

Why This Matters for Founders Right Now

If you are building AI tools, this is your moment of clarity.

You do not need to chase the next big thing. You need to solve one painful thing.

Enterprises want reliability. They want outcomes. They want AI that saves time, not AI that adds friction.

The next breakout product is not going to look revolutionary. It is going to look boring.

Because it will do something useful. And it will do it better than anything else.

What You Should Do Today

You can start by scannign your existing workflow. Pick the task everyone hates doing and write down the exactly steps that it takes to get it done.

Once you’ve got a clear idea of what’s needed, begin by designing a small agent or automation to handle it.

It’s important that you then test it in the real world. This means, measuring real results.

Once you have something that works, you can begin to scale it but only once the last step has been done thoroughly. While doing this it’s crucial that you move on from what does not work.

If you repeat this every month, you will have a smarter, faster, more efficient operation in under a year.

No AI lab. No flashy launch. Just real progress.

Sources