Tricentis released the findings of its most recent AI report, "AI-augmented DevOps: Trends Shaping the Future."
This year's research aims to understand to what extent the anticipated
benefits of AI in DevOps have been realized today, and how a lack of
trust, skills, or other challenges could affect its adoption.
When asked to evaluate the most impactful areas for AI investments
across the delivery cycle - such as planning, coding, deploying and
releasing - DevOps practitioners ranked testing as the most valuable (60%). This result was foreshadowed in the Tricentis' 2022 study,
which found that testing is where organizations expected the greatest
value from AI-augmented DevOps, with nearly 70% of respondents having
rated the potential of AI-augmented testing as extremely or very
valuable.
The research finds that DevOps teams are realizing the benefits of AI,
with mature DevOps teams who have adopted AI significantly more likely
(30%) to rate their teams as either extremely or very effective. The
biggest challenges DevOps teams are using AI to address are developer
team efficiency (60%), reducing the skills gap (54%), cost reduction
(47%), and software quality (42%). In fact, almost one third (32%) of
respondents estimate AI-augmented DevOps tools will save teams over 40
hours per month-equivalent to an entire workweek.
The 2024 results show that teams use AI to augment a wide range of
testing tasks, including test planning/deciding what to test (47.5%),
test case generation (44%), and analyzing test results (32%).
Additionally, nearly half (42%) of respondents expect AI to perform a
risk analysis of code changes, helping QA teams focus on code areas with
the greatest risk of errors to quality.
The report surveys 500+ DevOps practitioners, managers, and executives
from small, mid-size, and enterprise organizations across the globe and
in several industries, including financial services, healthcare, and
manufacturing.
Other 2024 findings reveal:
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Regulation is expected to help build trust, but others worry it will stifle innovation and outcomes.
Nearly two thirds (63%) of those surveyed view increased regulation as a
way to build confidence in AI across their organization, while a
smaller-but not insignificant-number of DevOps practitioners (16%) feel
increased regulation will hinder or stifle the potential impact of AI in
organizations.
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Humans remain vital to ensure software quality, but there's a shortfall in AI skills. Data
shows that humans are still very much "in the loop," with over two
thirds (71%) of respondents checking outputs at least half of the time,
and almost one in five (19%) claiming to check AI outputs all of the
time. However, a lack of AI skills (28%) is seen as the greatest hurdle
to AI adoption in DevOps.
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Generative AI (Gen AI) and AI copilots are key drivers of AI adoption:
GenAI (45%) is now the most widely adopted type of AI used by DevOps
practitioners. In particular, AI copilots are also on the rise, with use
cases in planning, code development, and software testing.
"AI is an exciting technology and growing at a pace unlike anything
we've seen in our industry," said Mav Turner, Chief Product and Strategy
Officer, Tricentis. "As AI technology is further developed, however,
training software development and quality engineering teams with the
necessary skills to effectively work with AI will be absolutely
critical."
"DevOps teams looking to get started with AI should look no further than
their testing processes. AI in testing helps to detect, auto-heal and
predict defects during development, as well as identify which tests need
to be run based on high risk. When coupled with low-code/no-code
technology, this means that, regardless of a team's technical expertise,
AI can significantly contribute to overall software quality. As DevOps
teams continue to mature, testing will be pivotal to realizing their
investment in AI-augmented DevOps tools and practices."