RDEL #55: Analyzing the 2024 Stack Overflow Developer Survey: How Engineers use AI (Part 2)
This week we continue our three-part series on the 2024 Stack Overflow Developer Survey by looking at AI adoption across engineering organizations, and what engineers really use AI for.
Welcome back to Research-Driven Engineering Leadership. Each week, we pose an interesting topic in engineering leadership, and apply the latest research in the field to drive to an answer.
This is the second installment of our three part series analyzing the 2024 Stack Overflow Developer Survey (first installment on productivity here). In this installment, we take a look at the usage and overall sentiment of AI tools, as well as how optimistic engineers feel about AI (and their jobs).
The context
The Stack Overflow Annual Developer Survey is conducted to gather insights into the developer community's preferences, challenges, and trends. It covers various topics such as popular programming languages, tools, and technologies, as well as work environments, education, and demographics. The survey aims to provide a comprehensive overview of the developer landscape, helping inform industry practices and highlighting emerging trends.
Each year, thousands of developers participate, making it one of the most significant surveys in the broader tech industry. This year, 65,437 responses from 185 countries are used in these survey results.
The research
The data for the 2024 Stack Overflow Developer Survey was collected through responses from over 65,000 global engineers who completed the main survey. Researchers collected data on AI sentiment and usage to capture insights on how AI tools are being adopted and perceived. Below are the key findings:
1. Engineers generally enjoy using AI, and don’t feel their jobs are threatened by the rise of AI.
62% of engineers currently use AI somewhere in the development process. This is a huge increase from last year, where only 44% of engineers were using AI.
65% of respondents expressed positive sentiment about AI, feeling optimistic about AI’s impact on their work.
The greatest benefit of AI tools are increased productivity (81%), and speeding up learning (62.4%).
Over 68% of engineers do not perceive AI as a threat to their job.
2. Trust in AI remains as an issue.
AI favorability has slightly decreased from 77% in 2023 to 72% in 2024.
Developers remain split on how much they trust AI output. 43% trust the accuracy of AI output, but 30.4% of engineers distrust the accuracy.
45% of professional developers believe that AI tools are bad at handling complex tasks.
67.8% responders believe the greatest challenge for AI at work is not trusting the output or answer.
Misinformation or disinformation is the top ethical concern for engineers in using AI.
3. In general, engineers see AI as only becoming more prevalent in their workflows in the next year.
Currently, AI is most used for writing code (82%), searching for answers (67.5%), and debugging/getting help (56.7%).
Developers believe AI will most likely be more integrated in the ways they are documenting code (81%), testing code (80%), and writing code (76%).
The application
This study reveals a strong adoption of AI tools among developers, despite lingering concerns about their accuracy and ethical implications. For managers thinking about AI adoption within their engineering organization, there is a balance between leveraging AI to enhance team productivity while proactively addressing the ethical and trust-related concerns developers have about AI usage. To address this, managers should consider the following processes:
Promote Ethical AI Practices: Develop a perspective on guidelines and best practices for ethical AI usage within your team, emphasizing the importance of data accuracy, proper attribution, and mitigating biases to foster responsible AI integration
Implement Feedback Mechanisms: Establish regular feedback loops where developers can share their experiences and concerns about AI tools, allowing for continuous improvement and addressing trust issues proactively.
Be flexible to change. The AI landscape is rapidly evolving, so it becomes critical to be open to adopting those changes to improve the software development lifecycle. This means being mindful of what AI tools are easy to include, and what tools become more entrenched (and therefore require deeper evaluation for consideration).
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We hope this discussion contextualized your own teams experience using AI in software development. Wishing you a Happy Research Monday!
Lizzie