More than 75% of working professionals worldwide use AI at least once a day for work, but far fewer trust AI-generated code, according to a survey of 3,000 employees in the Accelerate State of Business Report. DevOps (DORA) 2024 by Google.
The study, published on October 22, revealed that 76% of professionals use AI to write code, summarize information, explain unknown code, optimize code, and document code. He outlined the numerous benefits of adopting generative AI, including increased focus, productivity, job satisfaction, and code quality.
However, generative AI can also negatively impact software delivery performance, product quality, and the time employees spend on valuable work, the report stated. It also found that using AI does not necessarily reduce time spent on “hard work” or tasks that lack “meaning.”
“AI has positive impacts on many important individual and organizational factors that foster the conditions for high performance in software delivery,” the report states. “But AI doesn't seem to be a panacea.”
Google survey outlines the pros and cons of generative AI
This year's study, the tenth iteration, focused on how AI affects burnout, focus, job satisfaction, productivity, and the performance of products, organizations, and teams. DORA measures stability success across four key metrics: change delivery time, deployment frequency, change failure rate, and recovery time from failed deployments.
SEE: Choose from our list of the 10 best project portfolio management (PPM) software and tools for 2024.
Interactions with AI in daily work tended to come in the form of:
- Chatbots (78.2%).
- External web interfaces (73.9%).
- AI tools integrated into their integrated development environments (72.9%).
Some respondents reported adopting AI in response to competitive pressures, with one interviewee noting that companies that do not adopt AI risk “being left behind.” Another mentioned that their organization saw AI as “a big marketing point.” Less than 10% of respondents said their productivity had been negatively affected by AI.
Additional findings show:
- 81% of respondents said that “their organizations have changed their priorities to increase the incorporation of AI into their applications.”
- Developers feel more productive when using AI: 67% of respondents say AI helps them improve their code.
- Nearly 40% of respondents said they had “little or no” confidence in AI.
On the other hand, most respondents said they only have “some” confidence in the quality of AI-generated code. The interviews, as well as those of the study's authors, indicate that this may mean that developers hope to use AI as a basis for modifying and correcting the results.
“However, respondents also reported that they expected AI to have net negative impacts on their careers, the environment, and society as a whole,” the report reads. More than 30% of respondents believe that AI will be harmful to the environment.
AI can also impact software performance, stability, and delivery performance. This may be because code written by AI can be generated in such large quantities. These larger changes are “slower and more prone to instability,” according to the report. Small batches remain an important principle in software development that directly relates to quality.
Almost 9 out of 10 professionals use internal development platforms
Platform engineering is a discipline for creating workflows to promote self-service and collaboration. DORA describes it as the intersection of social interactions between teams and technical performance, such as automation, self-service, and process repeatability.
DORA found that 89% of respondents used internal development platforms, although the definition of the term was quite broad. The report also found:
- Organizations tend to see performance improvements at the beginning of a platform engineering initiative, followed by a decline and leveling off. This pattern coincides with other transformation initiatives studied by DORA.
- People were 8% more productive when using an in-house development platform.
- Organizations performed 6% better when using an in-house development platform.
- Change performance and stability dropped by 8% and 14%, respectively, when using an in-house developer platform.
What is the cause of such a large drop in exchange stability? DORA suggests that platforms could increase rework time. Or, this number could be indicative of a different pattern: teams with pre-existing high instances of burnout and change instability may adopt platforms to solve those problems.
Additional findings include the importance of stable priorities.
The full report goes into more detail on these issues. Additional findings include:
- Product quality is proportional to how well the organization understands the needs of its users. User-centered software development is beneficial because gaining a sense of purpose (directly meeting users' needs) benefits both employees and organizations.
- Organizations must give developers confidence that their projects are meaningful. a process that requires feedback from users.
- Focus on creating quality documentation. This is documentation that is not necessarily exhaustive, but relevant, easy to find and reliable.
- Unstable priorities can cause burnout in your employees. That is, the “move fast and constantly pivot” leadership mentality can work against employees. This mindset creates unclear expectations, decreases employees' sense of control, and increases their workloads.
- Leaders must be positive. While they can still challenge their workers to think outside the box, leaders must also recognize employees' successes.
“The key to success is to roll up your sleeves and simply get to work,” the report states. “The goal of the organization and its teams should simply be to be a little bit better than yesterday.”
