Rethinking software development in the AI era

Data is fast replacing code as the foundation of software development. Here’s how leading organizations anticipate processes and tools transforming as developers navigate this paradigm shift.

As companies look to artificial intelligence to drive their digital transformation, software development will change dramatically as well.

Companies are prepared for the fact that developers will have to get up to speed on machine learning algorithms and neural networks, and are looking forward to seeing how AI will automate many development and testing functions.

But what many enterprises are missing is that the nature of software itself is changing.

Today, applications are deterministic. They are built around loops and decision trees. If an application fails to work correctly, developers analyze the code and use debugging tools to track the flow of logic, then rewrite code in order to fix those bugs.

That's not how applications are developed when the systems are powered by AI and machine learning. Yes, some companies do sometimes write new code for the algorithms themselves, but most of the work is done elsewhere, as they pick standard algorithms from open source libraries or choose from the options available in their AI platforms.

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