Artificial intelligence has quickly become part of modern software development—often faster than it has been fully thought through. But more AI doesn’t automatically mean better software. Building sustainable systems today starts with a simple question: Where does AI actually add value – and where doesn’t it?

AI has quickly become the default

In many projects, AI is now used by default — whether for writing code, generating documentation, or producing content. What starts as a productivity boost often turns into standard practice, without much reflection on its actual value.

That’s where the real challenge lies: not every task needs AI – and not every use of AI makes sense.

Sustainability starts with conscious decisions

Using AI has real implications — both technically and organizationally. Behind every AI-powered feature are resource-intensive infrastructures, rising costs, and increased system complexity.

At the same time, a familiar pattern is emerging: content is generated, refined, and condensed again — often without delivering real value.

Architecture over hype

Integrating AI into a system is always an architectural decision. Using large models typically introduces dependencies — on cloud providers, proprietary technologies, or specific platforms.

These dependencies affect not only how systems are built, but also how flexible they remain over time. Sustainable software development therefore means actively managing these trade-offs, rather than focusing only on short-term gains.

Conclusion

Artificial intelligence is a powerful tool but not an end in itself.

Sustainable software is built where technology is applied deliberately and decisions are made consciously. Sometimes, that also means choosing not to use AI where it doesn’t provide real value.

This article is based on the April edition of our column “Schlicht und einfach” in the Swiss IT Magazine Inside IT. The original text was written by Markus Schlichting, CEO of Karakun, who regularly explores fundamental technology topics and their real-world implications in this column.

If you’re looking to integrate AI into your software architecture in a sustainable and meaningful way, we’d be happy to support you — from concept to implementation.

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FAQ

What does sustainable software development mean in the context of AI?

Sustainable software development means using AI deliberately and responsibly. It focuses not only on functionality, but also on resource consumption, system complexity, and long-term maintainability.

When does it make sense to use AI in software projects?

AI is particularly useful for handling large volumes of data or automating repetitive tasks. For simple or well-structured problems, its use is often unnecessary.

What risks come with using AI in software systems?

Common risks include dependencies on cloud providers and proprietary models, as well as increased system complexity. These factors can limit flexibility and long-term control.

Why can AI lead to higher resource consumption?

AI applications rely on powerful data centers that require significant energy and cooling. Large models in particular consume substantially more resources than traditional software solutions.

How can AI be integrated into software in a sustainable way?

By using it selectively, choosing smaller or specialized models where possible, and designing architectures that minimize dependencies while maintaining transparency around cost and resource usage.