There’s a striking disconnect happening in software development right now.

According to the 2025 Stack Overflow Developer Survey, 84% of developers are using or planning to use AI tools in their workflows. Over half of professional developers are using AI daily. The adoption is real, it’s fast, and it’s accelerating.

But here’s what engineering leaders tell us when we talk to them: “We’ve invested heavily in AI tools, but we have no idea if they’re actually making us more productive.”

That’s the AI productivity paradox. Adoption is easy. Proving and quantifying impact is hard.

Why Measuring AI Impact Is Different

Traditional engineering metrics weren’t built for this moment. DORA metrics can tell you if deployment frequency changed, but they can’t tell you why. Pull request counts might go up, but is that because developers are more productive, or because AI is generating code that requires more review cycles?

The challenge goes deeper than just measuring velocity. AI tools can simultaneously improve certain aspects of productivity while introducing new risks—increased code duplication, technical debt, or even decreased code quality in some cases. Without the right instrumentation, you’re flying blind.

Engineering leaders are under immense pressure to justify these investments. CFOs want ROI numbers. CTOs need to make decisions about which AI tools to standardize on. But the data simply isn’t there—or it’s scattered across git logs, survey tools, and anecdotal Slack conversations that don’t paint a complete picture.

Why GitKraken Is Uniquely Positioned to Solve This

We’ve spent the last decade building tools that 40 million developers trust. That foundation matters, because measuring developer productivity requires something most analytics platforms don’t have: developer trust.

Here’s what makes this different for us. In just six months, GitKraken’s AI-powered features—things like intelligent merge conflict resolution and AI-generated commit messages—have given developers 82,341 hours back. We didn’t just talk about AI productivity gains. We proved them. We measured them. And now, we’re helping you do the same.

Today, we’re announcing GitKraken Insights—software engineering intelligence built to help engineering leaders measure and optimize AI’s true impact on developer productivity.

What Makes GitKraken Insights Different

GitKraken Insights brings together everything you need to understand what’s actually happening across your development lifecycle. We’re talking about comprehensive metrics spanning DORA performance, code quality analysis, technical debt tracking, AI impact measurement, and developer experience indicators—all in one place.

But here’s what really sets it apart: we’re combining workflow data with Voice of the Developer feedback. When you see velocity decline or code quality issues emerge, you can immediately understand whether it’s a process problem, a tooling issue, or something else entirely. That context is what turns data into decisions.

We built this in partnership with GitClear, whose engineering analytics technology powers some of the most sophisticated development organizations in the world. Their SEI capabilities, combined with our developer experience expertise and the trust we’ve earned with millions of developers, create something unique in the market.

Intelligence That Teams Actually Want

One thing we’ve learned over the years: developers are incredibly sensitive to tools that feel like surveillance. And rightfully so. Productivity measurement done wrong destroys trust, hurts morale, and ultimately gives you bad data because teams game the system.

GitKraken Insights was built with a different philosophy. We’re measuring teams and workflows, not individuals. The goal is to surface systematic bottlenecks, identify friction points, and help teams improve—not to create performance review ammunition.

When developers trust the measurement system, they engage with it. They provide honest feedback through Voice of the Developer surveys. They want their leaders to see the data because it helps make their work lives better. That’s when you get real insights, not just metrics.

Accessible Intelligence for Every Team

Here’s something that shouldn’t be controversial but somehow is: engineering intelligence shouldn’t cost $200,000 a year and take six months to implement.

Traditional SEI platforms were built for Fortune 500 companies with enterprise budgets and dedicated implementation teams. That might work for some organizations, but it leaves the vast majority of development teams without access to the insights they need.

GitKraken Insights delivers enterprise-grade intelligence at 80% less than legacy platforms. Setup takes minutes, not months. You get immediate insights from your existing development data without complex integrations or engineering overhead.

For teams that have been cobbling together custom dashboards or making decisions based on gut feel, this changes the game. For teams evaluating expensive enterprise platforms, it’s a wake-up call about what’s actually possible.

What This Means for GitKraken

This launch represents an important evolution for us as a company. We started as a Git client that developers loved. We grew into a comprehensive DevEx platform spanning desktop, IDE, terminal, and now AI-powered workflows.

GitKraken Insights completes the picture. We’re not just providing tools that make developers more productive—we’re helping teams prove it, measure it, and continuously improve it. That’s the full DevEx platform promise.

It also reflects something deeper about how we think about AI. We’re not chasing hype. We’re not promising AI will replace developers. We’re building practical tools that make developers more effective, and now we’re helping teams understand whether those tools—and all AI tools—are actually delivering value.

The Road Ahead

The AI productivity paradox isn’t going away. If anything, it’s going to intensify as more AI tools flood the market and pressure to justify investments increases. Engineering leaders need better data, better context, and better tools to navigate this transition.

We think GitKraken Insights provides that foundation. It’s built on technology that works, from a company that developers trust, at a price that makes sense for real teams.

I’m excited to see what engineering leaders do with this. When you can finally see the complete picture—AI impact, delivery performance, code quality, and developer satisfaction all in one place—you can make better decisions. You can optimize what’s working and fix what isn’t. You can prove value instead of defending it.

That’s the kind of intelligence that moves teams forward.

If you’re ready to move beyond guesswork and start measuring what actually matters, start your free trial of GitKraken Insights today. Or join our webinar on October 29 to see it in action and learn how other engineering leaders are quantifying their AI investments.