Artificial intelligence has become an integral part of the development world. What started as a buzzword has evolved into a tangible tool that helps save time, improve quality, and sometimes even change the way we think about development. But make no mistake – it’s not a magic wand. At Quanti, we see AI as a smart assistant, not a one-size-fits-all solution. And we have a few good reasons why.

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What the numbers say – and why they matter

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Generative AI is no longer just a buzzword or a playground for startups. It’s being adopted by established corporations – and often with well-thought-out strategies. Already back in 2023, Goldman Sachs eported that in some cases, developers were accepting up to 40% of code generated by AI tools. Similarly Amazon, JPMorgan Chase, Morgan Stanley or IBM are integrating generative AI into internal systems to speed up software development, produce documentation, and answer internal queries more effectively.

According to a 2024 analysis by Gartner over 80% of enterprises are expected to use generative AI in production environments by 2026. A podle McKinsey's 2024 report further states that 63% of organizations already use generative AI for text generation, and over a quarter also apply it in software development.

It’s worth noting that these figures come from international research – primarily from large enterprises where AI is often introduced as part of broader digital transformation strategies. In the Czech Republic, companies are also exploring how best to integrate AI into their context and real-world projects.

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At Quanti, We’ve Built Our Own AI Community

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We didn’t wait around for someone to tell us how to use it. AI is a living topic across the company. We have AI ambassadors specializing in different areas – from QA to development. They serve as guides, test new tools, and help others find meaningful ways to integrate AI into their daily work.

We host monthly internal meetups and run a dedicated channel where developers, testers, and managers share tips and tricks. From generating test scenarios to experimenting with local LLM models – we enjoy it, and more importantly, it works.

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QA Example: AI as a “Temp Worker for Boring Tasks”

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Markéta from our QA team says she uses AI as a handy temp: it generates documentation, prepares XML scenarios for TestRail, and helps verify whether key parts of the requirements are covered. She even built her own AI bot to help prep for the ISTQB certification. More efficiency, less stress – a win-win

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Dev Example: AI-Assisted Code Reviews

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Vladimír created a simple AI agent that assists with code reviews in GitLab. After being triggered by a comment, it assesses code quality and clearly highlights what’s good and what needs improvement. And when something’s off, developers get timely, specific feedback.

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AI Is Here to Stay – The Question Is How to Tame It?

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Like any powerful technology, AI has its limits. It hallucinates. It may propose solutions that are common but not optimal. And it definitely can’t take responsibility.

That’s why we don’t treat AI at Quanti as an autopilot, but rather as a co-driver. People still lead development, testing, and documentation – they’re just faster, more focused, and more creative with AI by their side.

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So What’s the Takeaway?

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It’s not a question of whether to use AI – but how and why. Most importantly, whether you're open to trying new things.

At Quanti, we believe the future of development is hybrid: human + AI.

And those who master this partnership will gain a real advantage.

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