• The company suggests that business executives prioritize their developers by identifying areas of friction, removing obstacles to productivity, and encouraging growth and momentum.
  • The survey examined how AI-powered coding tools impact individual performance. 92% of developers use AI-powered coding tools, and 70% believe they provide a competitive edge.

Recent research by GitHub and Wakefield Research sheds light on the influence of artificial intelligence (AI) on the developer experience. The survey, which included 500 U.S.-based developers from organizations with more than 1,000 employees, focused on important aspects of their professions, including team collaboration, developer productivity, and the impact of AI in enterprise environments.

The reports found that 92% of developers currently use AI-powered coding tools at work. Yet despite investments in DevOps, developers still confront challenges. They report that waiting on builds and testing consumes the most time. In addition, they were concerned about repetitive tasks like writing boilerplate code. They desire to devote more time to collaborating with colleagues, acquiring new skills, and developing innovative solutions.

According to GitHub, these statistics indicate a growing need to improve development process efficacy.

The company suggests that business executives prioritize their developers by identifying areas of friction, removing obstacles to productivity, and encouraging growth and momentum. The study discovered that developer experience significantly impacts productivity, satisfaction, and impact.

Collaboration emerged as a fundamental element of the developer experience. Developers in enterprise environments collaborate with an average of 21 engineers on projects, making their collaborative abilities essential for performance evaluations. More than 80% of developers believe AI-powered coding tools can enhance team communication, project completion, code quality, and incident handling.

Inbal Shani, Chief Product Officer at GitHub, said, “Collaboration is the force multiplier for larger engineering teams to benefit and drive customer results. Every organization should use this equation to place developers at the center of empowering customers.”

Developers wanted greater upskilling and impact possibilities in the survey. They valued acquiring new skills, getting end-user feedback, and solving new challenges throughout their workday.

Need of Developers in Today’s Growing AI Ecosystem

The survey explored how AI-powered coding tools affect individual performance. Most developers (92%) reported using AI-powered coding tools, with 70% believing that these tools give them a competitive edge at work.

Github’s Shani anticipates that the 92% figure has increased since the March 2023 study. “We’ve already seen this impact from our customers using GitHub Copilot. These developers feel 75% more fulfilled with their work and are already writing code more than 55% faster,” said Shani.

Shani said AI might improve the developer experience. These include accelerating code delivery, enabling intelligent code reviews, improving codebase collaboration, and overcoming cognitively demanding development process disturbances.

She says that developer experience, productivity, and teamwork will change as AI models improve and new features are added.

Upskilling and Productivity are the Top Benefits of AI Tools

Integrating AI-powered coding tools into the developer’s workflow was viewed as an opportunity to enhance performance and better adhere to existing standards.

According to developers, acquiring new skills and developing innovative solutions had the most significant positive effect on their work.

Furthermore, the survey found a mismatch between current performance indicators and developer expectations. Developers expect to be evaluated based on code quality and collaboration, designated as the two most significant performance metrics. According to Shani, however, executives have traditionally evaluated performance based on code quantity and output. Developers argue that code quality and collaboration are essential evaluative factors.

It is believed that effective collaboration improves code quality. Developers cited several factors essential to effective collaboration, including regular contact, uninterrupted work time, access to completely configured developer environments, and mentor-mentee relationships.

They reported that unproductive meetings and excessive communication have negatively impacted their work.

Shani explained, “Given that developers now work with an average of 21 other engineers on projects, collaboration is more important than ever to efficiency and productivity. Developers in our survey said they want their organizations to make collaboration a top performance metric, which suggests organizations can do a better job of incentivizing greater collaboration among their engineering teams. Organizations should proactively incentivize developer collaboration as the true force multiplier on mission-critical results.”

Importance of Governance Standards for AI Tools

Shani thinks most firms have developers utilizing AI-powered coding tools without an enterprise-grade solution or defined regulations.

She added that while generative AI technologies like ChatGPT and Stable Diffusion have become popular, they continue to proliferate, raising issues about misleading outputs, hallucinations, and data privacy.

Shani emphasized the significance of organizations investing in enterprise-grade AI coding tools that meet their efficacy and data privacy requirements. In addition, she underscored the importance of assisting developers in integrating and refining their workflows with these approved tools.

Shani explained, “In our experience with customers deploying GitHub Copilot and GitHub Enterprise, such technology investments require organization-wide cultural change and proactive change management. You can’t turn on new AI coding tools and expect teams to seamlessly adapt their workflows around them. Technical agility requires operational agility.”

Enhancing Developer Experience

Shani recommends starting at the cultural level to discover workplace initiatives and policies encouraging cooperation. She stresses the need for team check-ins, meetings, and asynchronous communication via pull requests, problems, and chat applications.

Github advises engineering executives to standardize developer environments via cloud-based IDEs or other techniques. These efforts reduce machine setup time and let developers focus on collaborative problem-solving.

The study demonstrates that developers value mentor-mentee relationships and desire more in the workplace. GitHub suggests that businesses should grasp this opportunity to invest in cost-effective measures that facilitate the growth and upskilling of development teams.

Shani said, “Programs and processes that incentivize effective collaboration and communication, whether through documentation, effective meetings, or team components like mentor-mentee relationships, can help developers work together, enter a flow state and even grow their skills. Through AI-powered coding tools, teams can start with simple things like code reviews or pair programming to stand up effective mentors across their organizations to help their more junior developers grow.”