Enterprise software developers anticipate the transformative impact of generative AI on productivity

## The Revolution of Generative AI in Software Development

Daniel Saroff, the group vice president of consulting and research at International Data Corp., shared the story of a client who is undergoing a modernization project to rewrite applications created in Pick, an operating system and programming language from the 1960s, to run on modern infrastructure. Surprisingly, they discovered that OpenAI LP’s ChatGPT, a generative artificial intelligence (AI) model, had knowledge about the Pick environment and was able to assist significantly in the process. The AI model helped the client find errors, write documentation, and even migrate to Visual Basic. This incident highlights the disruptive potential of generative AI models like ChatGPT in the field of software development.

Another example comes from Joe Reeve, an engineer at Amplitude Inc., who noticed that customers were submitting code written in the company’s proprietary query language that had been generated by the Generative Pre-trained Transformer-4 (GPT-4) multimodal large language model. Reeve was surprised to find that GPT-4 had already learned how to use their tools through internet training data. It became clear that generative AI models like GPT-4 are already proving helpful to customers in building software.

Although generative AI models such as Microsoft’s Copilot and Amazon Web Services’ CodeWhisperer are gaining popularity for their ability to automate mundane programming tasks, their real value lies in their capability to generate code. Developers have been amazed at the quality of code produced by these AI engines. While they may not excel in creating new solutions, generative AI tools are excellent at automating repetitive tasks, making them highly valuable in areas like software testing. This ability allows them to quickly generate multiple test scenarios, improving efficiency in the testing process.

In a survey conducted by IDC, developers identified software quality testing and security and vulnerability testing as the two greatest benefits of generative AI. Language translation is another area where generative AI models have shown promise. They can translate software written in outdated languages like Cobol into modern dialects, making it easier for a larger pool of developers to support.

The impact of generative AI on software development is expected to be profound. A recent survey by GBH Insights LLC revealed that 78% of companies anticipate using AI for software development within the next three to five years. The use of AI is projected to save U.S. companies over $15,000 per IT employee annually by automating repetitive tasks, according to Freshworks Inc. Gartner Inc. predicts that by 2025, more than half of software engineering leader job descriptions will explicitly require oversight of generative AI.

Companies of all sizes are recognizing the potential benefits of generative AI. Large enterprises believe it will help overcome the persistent shortage of skilled developers, while smaller firms expect it to reduce spending on software-as-a-service applications by enabling them to build their own software. The advent of generative AI signals the onset of a productivity revolution. Prasad Ramakrishnan, Chief Information Officer at Freshworks, describes it as one of the most exciting advancements in the field. The speed with which generative AI has captivated IT professionals is astounding, considering that it was relatively unknown just a year ago.

Organizations already using generative AI tools like Microsoft Copilot have witnessed a significant increase in productivity. Amplitude Inc., for example, has reported a 20% to 25% reduction in time to value since implementing Copilot. As generative AI models continue to improve, they will be capable of handling more complex tasks such as testing, debugging, and identifying security flaws. This shift has the potential to transform the role of software developers and accelerate the democratization of development tasks through the use of low-code and no-code tools.

The long-term impact of generative AI on the software development industry may result in a shift in how users interact with software. Currently, applications are built with complex interfaces that hide underlying complexity, requiring developers to anticipate how the software will be used. However, as generative AI advances, much of this complexity could be eliminated. Graeme Thompson, CIO at Informatica, envisions a future where users can have a conversation with the data instead of relying on developers to create user interfaces. This simplification of software development has the potential to transform IT departments from cost centers to revenue drivers, improving customer engagement and retention.

## Editor Notes

Generative AI models like ChatGPT and GPT-4 are revolutionizing the field of software development. Their ability to automate repetitive tasks and generate high-quality code has caught the attention of developers worldwide. With the potential to save companies significant amounts of money and improve software quality, it’s no wonder that generative AI is rapidly gaining popularity.

As the use of generative AI in software development continues to grow, it’s crucial to stay updated on the latest advancements and trends. GPT News Room is an excellent resource for exploring the latest developments in generative AI and its impact on various industries. Be sure to check out GPT News Room for insightful articles, expert opinions, and comprehensive coverage of generative AI.

Visit [GPT News Room](https://gptnewsroom.com) for the latest news and insights on generative AI.

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