AI in the workplace: Adoption and impact in this DORA report preview

This blog has been adapted from the DevOps Research and Assessment team’s preview of the upcoming DORA report for 2024.

We’re just starting to see the impact of artificial intelligence, from treating disease to talking with animals. In an effort to better understand how this technology has become a part of work routines, our annual DORA Report has expanded its mandate in 2024 to include how AI is changing work, the impact of those changes, and overall organizational performance.

The report will look into the relationships between AI adoption, developer practices, and organizational outcomes, using more sophisticated statistical models to uncover the complex interplay of factors shaping this dynamic landscape.

In this preview of some of the aspects of AI that we studied, we’ve organized some of our AI adoption findings into four categories:

• Reliance: How much does AI contribute to specific developer tasks?
• Surfaces of interaction: Where do developers interact with AI in their work?
• Attitudes: How do developers feel about the impact of AI on their productivity, career, and the world?
• Future reflections: What predictions do developers have about the impact of AI on various aspects of their lives?

Reliance: a shift in the development landscape

This year’s report examines the extent to which developers rely on AI for various tasks related to software development. Comparing this year’s results to last year’s demonstrates that AI adoption has — and this might not be surprising to you — continued on a steady rise. Last year's questions, however, are different from this year's questions, making a direct comparison difficult.

The majority of respondents reported at least some reliance on AI for tasks including code explanation, documentation, writing code, and code optimization. This finding suggests a growing acceptance and integration of AI tools into the core activities of software development.

Surfaces of interaction: where AI meets development

We investigated the “surfaces” where developers interact with AI, focusing on the environments and tools where AI is most commonly encountered.

AI was prevalent in integrated development environments (IDEs) and internal web interfaces, which suggests that organizations want to streamline workflows and enhance productivity by incorporating AI features directly into the tools that developers use daily.

However, we also noted roughly half of respondents reported not interacting with AI as an automated part of their tool chain.

Attitudes: trust and transparency in the age of AI

We also explored developer attitudes towards AI, focusing on trust and transparency. We asked respondents about their level of trust in the quality of AI-generated code, and their organization’s transparency regarding AI implementation.

There is a relatively low level of trust in AI-generated code, with only 24% of respondents saying that they trust AI-generated code “a lot” or “a great deal”. This indicates a significant degree of skepticism and cautiousness among developers when it comes to relying on AI-generated outputs.

When asked if their organization is being transparent about how AI is being used, the majority of respondents agreed or somewhat agreed, but a substantial portion expressed neutral or negative sentiments. This suggests room for improvement in terms of how organizations communicate their AI strategies and plans to their development teams.

Google Cloud’s Office of the Chief Information Security Officer (CISO) published How to craft an Acceptable Use Policy for gen AI (and look smart doing it). This article recommends having a well-defined Acceptable Use Policy (AUP) to help with risk mitigation, strategic organizational alignment, and promoting compliance.

Future reflections: navigating the impact of AI

Beyond its current applications, AI’s potential impact on the future of work, productivity, and society is a topic of much discussion and speculation. To explore developer sentiments on this issue, we asked them to predict the impact of AI on various aspects of their lives in the next year, the next five years, and the next ten years.

• Many developers perceive a negative impact on career trajectories over longer timeframes, with more respondents expressing concern about the long-term effects of AI on their career a decade from now. This could reflect anxieties about job displacement or the changing skill sets required in an AI-driven workplace.
• Developers were also concerned about AI’s negative impact on product quality and software delivery processes remain relatively low across all timeframes. This suggests that they have a degree of confidence in AI’s ability to enhance these aspects of software development.
• Developer concerns are more pronounced on the broader societal and environmental impacts of AI, especially in the long term. This aligns with wider public discourse surrounding the ethical implications and potential risks associated with AI development and deployment.

The 2024 DORA Report will include a deeper exploration of the impacts AI is having in the workplace. The report will look into the relationships between AI adoption, developer practices, and organizational outcomes, using emerging methods in causal inference to help uncover the complex interplay of factors shaping this dynamic landscape.

As AI continues to reshape the software development landscape, understanding these nuances will be essential for maximizing the benefits of AI while mitigating potential risks.

To take action today, we offer a guide with insights on how to enable your software delivery teams to innovate with generative AI. You can also join the DORA Community to learn more, and be notified when the 2024 DORA Report is published.