More than 75 % of working professionals worldwide use AI at least once daily for work, but far fewer trust AI-generated code, according to a survey of 3, 000 employees in Google’s 2024 Accelerate State of DevOps Report ( DORA ).

The study, published on Oct. 22, revealed that 76 % of professionals use AI to write code, summarize information, explain unfamiliar code, optimize code, and document code. It outlined the many advantages of relational AI implementation, including increased target, efficiency, job satisfaction, and script quality.

But, conceptual AI can also negatively influence software distribution efficiency, product quality, and the time staff spend on valuable work, the report indicated. It also found that using AI does not necessarily reduce time spent on” toilsome work”, or tasks that lack “meaningfulness”.

According to the report,” AI has positive effects on many important individual and organizational factors that foster the conditions for high software delivery performance.” ” But, AI does not appear to be a panacea”.

Google survey identifies benefits and drawbacks of generative AI.

This year’s study, the 10th iteration, focused on how AI impacts burnout, focus, job satisfaction, productivity, and the performance of products, organizations, and teams. DORA measures stability success through four key metrics: change lead time, deployment frequency, change fail rate, and failed deployment recovery time.

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In the course of their daily work, AI frequently came in the form of:

  • Chatbots ( 78.2 % ).
  • External web interfaces ( 73.9 % ).
  • AI is used in their integrated development environments ( 72.9 % ).

Some respondents reported using AI to combat market pressures, with one interviewee mentioning that businesses that do n’t embrace AI run the risk of being “left behind.” Another mentioned how their company views AI as” a significant marketing point.” More than 10 % of respondents claimed that AI had had a negative impact on their productivity.

Additional findings show:

  • According to 81 % of respondents,” their organizations have changed their priorities to improve how they incorporate AI into their applications.”
  • 67 % of respondents reported that AI makes it easier for developers to improve their code. This makes developers feel more productive when using AI.
  • Nearly 40 % of respondents said they had “little to no” faith in AI.

On the other hand, a majority of respondents said they only” somewhat” trust the quality of AI-generated code. Interviews, as well as the study’s authors’, indicate this may mean developers expect to use AI as a baseline from which to tweak and correct the results.

” However, respondents also reported expectations that AI will have net-negative impacts on their careers, the environment, and society, as a whole”, the report reads. Over 30 % of respondents think AI will be detrimental to the environment.

AI may also impact software delivery performance, stability, and throughput. This may be because there is such a large amount of AI-written code that can be produced. These larger changes are” slower and more prone to instability”, according to the report. Small batch sizes remain a crucial tenet of software development that has a direct bearing on quality.

Nearly 9 in 10 professionals use internal developer platforms

Platform engineering is a branch of the field that creates 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 repeatability of processes.

Despite the broad definition of the term being left out, DORA found that 89 % of respondents used internal developer platforms. The report also found:

  • Organizations typically experience performance gains at the start of a platform engineering initiative, followed by a dip and a leveling out. This pattern is consistent with other DORA studies on transformation initiatives.
  • When using an internal developer platform, employees were 8 % more productive.
  • When using an internal developer platform, organizations performed 6 % better.
  • Throughput and change stability fell by 8 % and 14 %, respectively, when using an internal developer platform.

Why such a large drop in change stability? The platforms may speed up rework, according to DORA. Or, this figure might be a sign of a different pattern: teams with high levels of burnout and change instability may adopt platforms to address those issues.

The importance of stable priorities is another finding.

The full report goes into more in-depth analysis of these subjects. Additional takeaways include:

    The organization’s ability to understand its customers ‘ needs is reflected in the quality of the goods. User-centered software development is advantageous because it benefits both employees and businesses by creating a sense of purpose and directly satisfying user needs.

  • Organizations should give developers the assurance that their projects are worthwhile because it requires user feedback.
  • Focus on creating quality documentation. This is documentation that is not necessarily comprehensive but instead is relevant, findable, and reliable.
  • Unstable priorities can lead to employee burnout. Namely, “move-fast-and-constantly-pivot” mentalities from leadership can hurt employees. This mindset creates unclear expectations, decreases employees ‘ sense of control, and increases their workloads.
  • Leaders should be positive. While they can still challenge their workers to think innovatively, leaders should also recognize employees ‘ successes.

According to the report, “rolling up your sleeves and getting to work is the key to success.” The organization and your teams should aim to be” just a little better than you were yesterday,” the statement goes.