EY Tech Trend 01: AI turbocharges software development for efficiency and innovation

Generative AI tools are revolutionizing software development by enhancing efficiency and innovation. These tools, like GitHub’s Copilot and Jasper, can analyze extensive data and generate user stories, propose prototype design ideas, and recommend suitable technologies. They can also generate code based on contextual cues from input code or natural language, speeding up the coding process. Additionally, AI is automating various aspects of the software development and delivery processes in DevOps and optimizing workload in cloud resources. Gartner predicts that by 2028, 75% of enterprise software engineers will use AI coding assistants. GenAI is reshaping software development in four key areas: requirement planning, developer productivity, DevOps and deployment, and workload optimization. In requirement planning, GenAI tools can analyze customer requests, market trends, and user feedback to generate user stories and propose design ideas. For developer productivity, these tools can swiftly produce code for routine tasks, saving time for developers to focus on more complex tasks. In DevOps, GenAI can automate testing and deployment processes, streamline the development pipeline, and reduce development costs. Finally, GenAI can optimize workload in cloud resources by analyzing historical data and generating actionable recommendations for resource allocation. Despite challenges such as data privacy concerns and biased outputs, GenAI has the potential to significantly improve the efficiency and innovation of software development. However, it is important to note that GenAI cannot function autonomously and requires human input and oversight.