Test automation is becoming a central part of software delivery, but adoption is uneven. Recent mabl research found that 60% of teams were using AI in some way in testing and DevOps, while 80% of companies were not delivering software at high velocity, defined as weekly or daily deployments. The figures below cover adoption, workflow placement, maintenance, coverage, and reported customer outcomes. Each result retains the year and source context of the original study.
Contents
- Adoption and DevOps priorities
- Which tests teams plan to automate
- Where automated tests run
- The time cost of testing
- Automation, coverage, and delivery
- Testing and customer happiness
- Roles, QA sourcing, and enterprise testing
Adoption and DevOps priorities
The 2024 mabl Testing in DevOps Report surveyed more than 500 development and quality professionals in the United States. Roughly 40% of respondents held leadership roles in software development and QA, while 60% were practitioners on the front lines of development. That mix matters: the results reflect both strategic priorities and day-to-day testing work.
DevOps transformation was a clear priority. According to the 2024 mabl report, 89% of teams were prioritizing DevOps transformation. Yet delivery speed remained a challenge: 80% of companies were not delivering high-velocity software, where high velocity was defined as weekly or daily deployments.
Testing environments were also becoming more complex. The same report found that 44% of fully DevOps teams were using five or more testing tools. Tool count alone does not show whether a process is effective, but it does indicate that test automation often operates across multiple systems, stages, or test types.
AI adoption was already widespread in the 2024 results. Sixty percent of teams were using AI in some way in testing and DevOps. This is an adoption measure, not a claim that AI replaced existing automation or that all teams used it for the same purpose.
Maintenance was a growing concern. The 2024 mabl report recorded a 138% increase, compared with the prior report, in teams ranking test maintenance as their top pain point. The comparison is a change in how respondents ranked the issue; it is not a percentage of tests or a measured increase in maintenance hours.
Which tests teams plan to automate
The 2022 mabl Testing in DevOps Report measured planned implementation for 2023 across several testing categories. Automated API testing led the list, with 43% of respondents planning to implement it. Automated regression testing followed at 40%.
The planned priorities then moved toward user-facing and broader workflow coverage. Thirty-seven percent planned to implement automated end-to-end UI testing, and 32% planned to implement automated UI or functional testing. Twenty-nine percent planned to adopt automated performance or load testing.
Accessibility testing was planned by 21% of respondents. Its lower position in this list should not be interpreted as lower importance; the statistic describes planned implementation in that survey period.
| Planned testing capability for 2023 | Respondents |
|---|---|
| Automated API testing | 43% |
| Automated regression testing | 40% |
| Automated end-to-end UI testing | 37% |
| Automated UI or functional testing | 32% |
| Automated performance or load testing | 29% |
| Accessibility testing | 21% |
Source: mabl, 2022 Testing in DevOps Report. These are plans reported in 2022 for implementation in 2023, not a later measurement of completed adoption.
Where automated tests run
The 2022 mabl report also described where teams placed automated functional testing in the development workflow. Forty-two percent of respondents ran automated functional tests at the pull request stage. This places feedback after a proposed code change and before the change is merged, according to the workflow label used by the report.
Thirty-five percent had shifted automated functional testing all the way to the code stage. The two figures are not necessarily mutually exclusive: a team can run different tests at more than one point in a pipeline, and the survey categories describe reported practice rather than a universal process model.
Testing responsibility was distributed more broadly in some organizations. One quarter of respondents, or 25%, said everyone in their organization had a role in testing. That result suggests that testing was not always treated as an activity owned only by a specialized QA group, although it does not establish how much testing each role performed.
The time cost of testing
The 2022 mabl report asked respondents which testing activities were among their most time-consuming tasks. Test planning and test case management ranked first at 56%. Test maintenance was next at 39%, followed by test execution at 29%.
Adding test coverage was selected by 28% of respondents, while 26% selected test analysis. Defect reporting was selected by 22%. These figures show how effort was distributed across several activities; they should not be added together because respondents could identify more than one time-consuming task.
| Testing activity | Share ranking it among the most time-consuming |
|---|---|
| Test planning or test case management | 56% |
| Test maintenance | 39% |
| Test execution | 29% |
| Adding test coverage | 28% |
| Test analysis | 26% |
| Defect reporting | 22% |
The pattern helps explain why automation is not simply a matter of adding more scripts. Planning, maintenance, analysis, and reporting can remain significant workload areas even when execution is automated. It also provides context for the 2024 finding that test maintenance had become a more prominent pain point compared with the prior mabl report.
Automation, coverage, and delivery
Several mabl findings connected automation with test coverage and delivery outcomes. In the 2022 report, teams that accelerated deployments by 50% to 100% were more than three times as likely to have good or excellent test coverage. A related comparison found that teams accelerating deployment frequency by 50% to 100% were 2.5 times more likely to describe test coverage as good or excellent.
The same report found that teams with all automated workflows were over seven times more likely to have good or excellent test coverage. At the other end of the spectrum, teams with very few automated workflows were four times more likely to have almost no test coverage.
Coverage was also associated with handoffs. Teams with good or excellent test coverage were almost three times as likely to say their handoff process was good or seamless. These are reported relationships, not proof that automation alone caused the coverage or handoff result.
| Reported relationship | Relative result |
|---|---|
| Accelerated deployments by 50%–100% and good or excellent coverage | More than 3× as likely |
| All automated workflows and good or excellent coverage | Over 7× as likely |
| Very few automated workflows and almost no coverage | 4× as likely |
| Good or excellent coverage and good or seamless handoffs | Almost 3× as likely |
| Accelerated deployment frequency by 50%–100% and good or excellent coverage | 2.5× more likely |
The practical reading is that delivery speed and testing maturity appeared together in the survey results. Faster deployment was not presented as a substitute for coverage; the strongest comparisons linked faster delivery with stronger reported coverage.
Testing and customer happiness
The 2022 mabl report also associated automation and coverage with customer satisfaction. Teams that accelerated deployment frequency by 50% to 100% were almost twice as likely to report good or amazing customer satisfaction. Teams with fully automated pipelines were three times more likely to rate customer happiness as good or amazing.
Teams with the most automated pipelines were 3.2 times more likely to say customers were very happy. Teams with high test coverage were 1.6 times as likely to report high customer happiness.
Earlier mabl research provides additional context. In the 2021 Testing in DevOps Report, 31% of fully DevOps teams described customer happiness as amazing, compared with 7% of DevOps aspiring teams. More than 50% of fully DevOps teams said they had a culture of quality, and 43% of DevOps teams said they caught bugs early in development.
The 2020 mabl DevTestOps Landscape Survey reported that four to five different types of tests were cited as the minimum needed to strengthen customer happiness. This is a survey finding about the number of test types respondents considered necessary, not a universal testing standard.
Roles, QA sourcing, and enterprise testing
The 2020 mabl DevTestOps Landscape Survey described the professional mix of its respondents. Testers, QA professionals, engineers, and SDETs accounted for 59%; developers or engineers accounted for 34%; managers, directors, and CEOs accounted for 23%; and operations, DevOps, or SRE roles accounted for 11%. Because role categories can overlap in survey reporting, these percentages should not be treated as a complete workforce distribution unless the source defines them that way.
The 2022 mabl report examined how QA work was sourced. Forty percent said some aspects of QA were supported externally. Thirty-five percent reported that all QA work was handled by internal employees. Fourteen percent said most QA effort was executed by third parties, and 7% said all QA was fully outsourced.
Views of testing’s organizational importance also varied. Forty-eight percent said testing and QA were very important, while 7% said testing was insignificant. These responses capture perceptions in the 2022 survey period and do not describe every organization’s formal quality policy.
Enterprise software testing showed substantial automation as well. In Tricentis’ 2023 State of Worldwide Business Assurance for SAP solutions, 74.6% of organizations surveyed were using an automated or mixed approach for SAP testing. More than 40% of those SAP organizations had automated half or more of their test suites in 2023. These figures apply specifically to the surveyed SAP testing population and should not be generalized to all software teams.
Together, the results point to a measured view of test automation: adoption spans tools, pipeline stages, and enterprise platforms, while maintenance, planning, and coverage remain important constraints. The strongest reported associations are between broader automation, stronger coverage, faster delivery, and better customer outcomes, but the source figures describe relationships and survey responses rather than guaranteed causal effects.