AI in software development

AI in software development

AI in software development: Artificial intelligence (AI) is the tech trend of our time. Recently, everyone was still talking about buzzwords such as digitalization, but the wheel has quickly turned and reached the masses with the ChatGPT tool at the latest. Optimists see generative AI and digital business models as the problem solvers for everything that can be digitally generated and processed. However, some bold AI visions also give rise to fears, for example when it comes to job losses.

What impact does AI have on the development of individual software solutions: game changer or pipe dream? In any case, AI has the potential to revolutionize individual software development. Whether AI tools in applications, automated testing or AI-supported code writing: the potential seems enormous. At the same time, there are many questions about the challenges and risks of artificial intelligence.

Auswirkungen von KI auf die Software-Entwicklung

Artificial intelligence (AI) has a wide range of effects on individual software development:

  • Automation of routine tasks: AI can automate repetitive and time-consuming tasks in software development. AI tools can already automatically perform tests, generate code or identify bugs.
  • Accelerating the development process: By using AI, developers can create prototypes more quickly. This shortens the development time.Improved code quality: AI can help to detect and correct errors in the code at an early stage.
  • Innovative functionalities and applications: AI opens up new possibilities for the development of software with advanced functions such as speech and image recognition, natural language processing (NLP) or predictive analytics. These functions can help to make software solutions smarter and more efficient.
  • Changing the role of the developer: The introduction of AI into software development can change the role of the developer. They may need to acquire new skills to work effectively with AI technologies and focus on higher-value tasks while routine tasks are taken over by AI.Ethics and responsibility: The use of AI in individual software development also raises ethical issues, e.g. in relation to data protection, the bias of algorithms and the potential impact on society. Developers need to consider these aspects and act responsibly.

    Did you notice anything? The last section of text was created with the help of several AI tools. First, the generative AI ChatGPT was asked and the answer was then refined by an AI language assistant. But in the end, the (human) author of this text had to shorten, structure and slightly edit the results of the AI.

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Customized software turns ideas into reality

On the one hand, this demonstrates the impressive capabilities of generative AI assistants; on the other hand, such practical examples also quickly show the current limits of artificial intelligence. For example, the AI-generated texts still contained errors or irrelevant information in the previous text section, which then had to be corrected by the author. The situation is similar when it comes to software development. Yes, AI helps with the automation of routine tasks, such as writing code based on already documented programming examples. Providers such as GitHub, who have launched AI tools such as Copilot, are talking about huge productivity gains in software development thanks to AI.

According to GitHub, Copilot increases productivity by 88% and even 96% faster results for repetitive tasks. However, AI reaches its limits when it comes to developing individual software solutions. Intelligent and structured summaries of available knowledge are the strengths of AI. The weaknesses of artificial intelligence become apparent when it comes to creating something new and being creative. This is particularly evident in the design and development of customized software. In contrast to standard applications, individual solutions that are developed specifically for customers do not yet have any content that can be learned by AI.

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More efficiency thanks to AI?

For developers of individual software, the use of AI can therefore automate routine tasks, for example, which can speed up the development process. However, a weakness of current AI solutions, which we have already identified in voice assistants, is also evident in AI in software development. Generative AI can test, change and update existing code – in other words, it can access knowledge and data that was previously created by human or artificial intelligence. But AI cannot yet be creative and think outside the box.

What’s more, the development of individual software involves far more than just writing code. The core of software development is not the actual programming. When developing individual software solutions, it is primarily about understanding exactly what the customer-specific application should do and which code and software architecture are the best choice for this. Before programming and during the development process, it is therefore primarily a matter of working with the client to crystallize technical requirements and efficiently implement them in code. In this respect, although AI helps to increase efficiency in the production of code, it only makes sense if the requirements of the future users of the application are bundled together in a coherent software concept beforehand. Software development is not an end in itself. It is not about programming new code as quickly as possible. It is about solving a specific problem. And when it comes to solving this task, humans (still) have advantages over AI.

AI will not completely replace the developer

AI will not completely replace the developer

AI can be used to increase productivity in software development. AI will not replace human developers and software designers in the foreseeable future. This is because the use of AI in software development also raises questions about data security and copyright.

On the other hand, companies will no longer be able to do without AI in the future – the increase in productivity is already a weighty argument for this. AI can help speed up processes and increase work efficiency not only in software development, but also in sales & marketing, human resources and many other office areas.

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