92% of US-based developers already use AI-powered coding tools at work: GitHub report

A recent survey conducted by GitHub in partnership with Wakefield Research sheds light on the impact of artificial intelligence (AI) on the developer experience. The survey, which involved 500 US-based developers at companies with more than 1,000 employees, focused on key aspects of their careers, such as developer productivity, team collaboration and role of AI in enterprise environments.

According to the results, 92% of developers are already using AI-powered coding tools in their work. Yet despite investments in DevOps, developers still face challenges. They report that their most time-consuming task is waiting for builds and tests. They also expressed concerns about repetitive tasks such as writing boilerplate code. They aspire to allocate more time to collaborate with their peers, learn new skills and create innovative solutions.

GitHub said these statistics indicate a growing need to improve the efficiency of the development process.

“We found that developers spend most of their time writing code and testing and then waiting for code to be reviewed or releases to complete,” Inbal Shani, chief product officer at GitHub, told VentureBeat. “We’ve also found that AI-powered coding tools enable individual developer productivity and greater team collaboration. This means that generative AI helps developers drive greater impact, increase satisfaction and to create more innovative solutions.”

The company suggests that business leaders put their developers first by identifying areas of friction, removing obstacles to productivity, and fostering growth and momentum. Developer experience, according to the study, has a major influence on productivity, satisfaction and impact.

Collaboration emerged as an essential aspect of the developer experience. Enterprise developers typically collaborate with an average of 21 engineers on projects, making their collaborative skills important in their performance reviews. Over 80% of developers believe that AI-powered coding tools can improve team collaboration, improve code quality, speed project completion, and improve incident resolution.

“Collaboration is the force multiplier for larger engineering teams to benefit and drive results for customers. Every organization should use this equation to put developers at the center of customer empowerment,” added Shani from GitHub.

In the study, developers also expressed a desire for more opportunities to develop and make an impact. They ranked learning new skills, receiving feedback from end users, and designing solutions to new problems as key things that positively impact their workday.

What Developers Need in Today’s Growing AI Ecosystem

The survey looked at the impact of AI-powered coding tools on individual performance. An overwhelming majority of developers (92%) said they use AI-powered coding tools, with 70% believing these tools gave them an advantage at work.

Developers said they see AI as an opportunity to focus on solution design and skill development, such as learning new programming languages ​​and frameworks. They also claimed that the integration of AI coding tools aligns with the goal of improving the developer experience.

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

Shani said AI has the potential to dramatically improve various aspects of the developer experience. These include accelerating code delivery, facilitating smart code reviews, improving collaboration within the codebase, and overcoming development process disruptions that typically require more cognitive effort. .

According to her, as AI models advance and additional features are developed, we can anticipate a fundamental redefinition and improvement of the developer experience, developer productivity, and team collaboration.

Skills development and productivity, the main benefits of AI tools

The study identified skills development as the top benefit, followed by productivity gains. Integrating AI-powered coding tools into the developer’s workflow was seen as an opportunity to improve performance and better meet existing standards.

Developers said learning new skills and creating innovative solutions had the greatest positive impact on their work.

“AI development tools will soon become table stakes, and organizations that do not embrace this change will be left behind. Having AI tools will become an expectation of all developers as a central tool for do their job,” Shani added. “If industries want to hire and retain the best talent, they need to be able to provide the best tools to make developers more productive.”

The survey also highlighted the disconnect between current performance metrics and developer expectations. Code quality and collaboration were identified as the most important performance metrics, with developers expecting to be evaluated based on these criteria. Yet, according to Shani, executives traditionally gauge performance based on the amount of code and output. The developers claim that code quality and collaboration are at least important factors to evaluate.

“I know that from my own experience as a developer! We developers prefer to be measured by how well we resolve complex incidents and deliver impact, rather than the number of incidents resolved, which the developers in our survey echoed,” she said. declared.

Effective collaboration is said to improve code quality. The developers highlighted a number of factors as critical to successful collaboration; regular points of contact, uninterrupted working time, access to fully configured development environments, and mentor-mentee relationships.

They noted ineffective meetings and excessive communication as distractions that negatively impacted their work.

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

Shani thinks the widespread adoption of AI-based coding tools among developers indicates that most organizations likely have developers using these tools without an enterprise solution or clear policies in place to effectively govern their use.

She said that while generative AI tools such as ChatGPT and Stable Diffusion have grown in popularity, they continue to grow rapidly, with concerns about the appearance of false outputs or hallucinations, as well as the data confidentiality.

Therefore, Shani highlighted the importance for organizations to invest in enterprise-grade AI coding tools that align with their criteria for efficiency and data privacy. Additionally, she highlighted the need to help developers integrate and optimize their workflows around these trusted tools.

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

How organizations can improve the developer experience

Shani advises organizations to start at the cultural level to identify workplace programs and policies that support increased collaboration. She stresses the importance of establishing regular check-ins for work teams, scheduling meetings, and providing platforms for asynchronous communication through pull requests, issues, and chat applications.

Engineering managers should also explore methods to standardize development environments, such as using cloud-based IDEs or workarounds, according to Github. These initiatives aim to minimize the time spent on machine setup and allow developers to focus more on collaborative problem solving.

The study reveals that developers place a high value on mentor-mentee relationships and want more of such relationships in their work environment. GitHub suggests that organizations can seize this opportunity to invest in cost-effective metrics that make it easier to grow and develop their development teams.

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