How to gain real control over productivity when your teams use AI

Nov, 27, 2025 | Read 3 min.

Let’s start with this premise: generative artificial intelligence has already entered your team. Is it possible to gain real control over productivity now that your teams are using AI? That’s the question we’ll try to answer next.

But before that, let’s recall a first article in which we explored the impact of AI on software development productivity, where tools such as GitHub Copilot, Amazon CodeWhisperer or LLMs such as GPT can speed up tasks, generate tests, document … And a later one where we examined the most common mistakes when implementing it, such as blindly trusting AI or implementing it without a strategy.

Because, as we said from the start, the use of generative AI is a fact. Whether we like it or not, whether it’s done with corporate tools or not, it’s becoming more and more difficult to find team members who don’t use them to speed up and automate part of their work. But real improvement only exists if it can be demonstrated.

And that’s where the problem begins. Many organizations are convinced that AI is boosting their performance, but their data tells another story, or they don’t even have data at all because it’s difficult for them to measure the before and after.

If you don’t know how you were producing until today, how will you know if generative AI is actually helping you deliver value?

Measuring changes everything (with and without AI)

Let’s recall some figures from recent studies on the use of AI among development teams and its impact on productivity:

According to the DORA/Google Cloud 2025 report, 90% of developers already use AI in their work, and more than 80% say it has improved their productivity.
However, not everything is positive: a significant part points out that they do not fully trust AI-generated code.
PwC’s 2025 Global AI Jobs Barometer reveals that productivity has grown almost fourfold in the sectors most exposed to AI, including IT.
Despite these trends, it’s not uncommon to find controlled studies that show otherwise: in a recent experiment with open-source developers, a group using AI took 19% longer to complete their work than those who worked without it.

These data clearly show something: AI can boost productivity, but it can also create a false sense of improvement. There is a gap between perception and reality that can make us lose control.

How Quanter measures and controls productivity for real

Quanter was born precisely to close that gap. Whether you’re using AI in your development or not, it’s not enough to believe that your productivity is increasing, you need numbers to verify it.

Let’s see how Quanter helps you gain better control over your development processes:

Solid baseline before AI

Before deploying AI tools, Quanter allows you to record your starting point: actual productivity, speed, defects, cost per functionality… These benchmark metrics, based on international standards, are key for comparing results later and seeing whether AI is doing what you expected.

Measuring real value

AI can generate a lot of code, but that doesn’t mean it produces value. Quanter measures delivered functionality, its cost and effort, making it the foundation for assessing your real progress.

Risk detection

Quanter also helps you identify problems. If AI is introducing errors or rework, you will see it reflected in your metrics: defects per functionality, drop in productivity… You will get real insight into the hidden cost of AI.

Comparing teams

You can see which teams are leveraging AI better and which aren’t. Are your internal teams accelerating thanks to AI? Are your external vendors truly delivering faster? Quanter enables internal and external benchmarking to detect strengths and areas for improvement, comparing your results with real market data from more than 105,000 development projects.

Evolution analysis

AI adoption often follows a curve: at first it may slow things down, then speed up, and eventually stabilize. Quanter measures this progression continuously and displays it in a clear, visual dashboard. You’ll see whether your AI models are scaling well or whether adjustments are needed.

Clear reports for management

With Quanter you can generate reports before vs. after the use of AI that validate your hypotheses, justify investment and show with data the real return or the need for correction. You’ll no longer say “we think it’s going well”: now you can state it with complete confidence.

Good AI is the one that proves it works

The adoption and use of AI can clearly transform software development. But without a measurement system, you risk being carried away by illusions of improvement.

With Quanter you will have metrics that bring clarity and control, thanks to its data that will lead you not only to improve, but also to certify that improvement.

If you’re ready to see if AI is really boosting your productivity, Quanter is the tool you require. Contact us and see it for yourself.

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