Mobile App Testing Statistics (2026): 12 Numbers You Can Use
Your release dashboard can show green tests while a customer hits a frozen checkout, an App Store rejection, or a device-specific crash. The useful mobile app testing statistics are the ones that connect testing activity to those delivery and production outcomes.The short answer: public 2025–2026 evidence points to growing testing spend, incomplete test observability, measurable stability variation, and substantial security exposure. The figures below distinguish market forecasts, vendor telemetry, surveys, and platform disclosures so you can cite the right number for the decision in front of you.
Key mobile app testing statistics for 2026
Use these figures as individually citable starting points. They do not all measure the same population, and several are vendor-reported rather than independent industry censuses.
The mobile application testing services market is forecast at $9.02 billion in 2026, up from a modelled $7.70 billion in 2025, according to Mordor Intelligence. This proprietary forecast covers testing services rather than the full tools and device-infrastructure category. Mordor Intelligence
The broader mobile application testing solutions market was modelled at $18.33 billion in 2025 and is forecast to reach $48.56 billion by 2031 by TechSci Research. Its solutions definition includes tools, platforms, device farms, and services. TechSci Research
The median crash-free session rate was 99.95% in Luciq’s app telemetry collected through Instabug in 2024 and published in its 2025 outlook. Luciq
Respondents reported that 57% of QA tests were automated in the Software Quality Pulse Report, published May 2026. The survey covered about 4,000 software QA engineers, developers, security professionals, and engineering leaders; it is not mobile-only. Ranorex
At least 45% of active Bitrise workspaces ran identifiable automated tests in CI in Q1 2026, based on more than 19 million anonymised builds among teams active in both Q1 2025 and Q1 2026. Bitrise
Only 34% of Bitrise workspaces had test reporting enabled in Q1 2026. Running a test and retaining structured pass-rate or flakiness data are different capabilities. Bitrise
49% of respondents said AI was already part of their mobile app testing strategy in a Tricentis-commissioned survey of 1,028 senior IT leaders and application developers in the US, UK, Germany, and Singapore, fielded December 1–20, 2023. Intelligent CIO Europe
Apple rejected 1.93 million of 7.77 million app submissions in 2024, according to Apple’s transparency data as reported by MacRumors. This is a store-review outcome, not a direct measurement of a testing failure. MacRumors
Google prevented more than 1.75 million policy-violating apps from being published on Google Play in 2025
, according to Google’s own ecosystem-security review. Google
HTTP URLs appeared in 94.3% of Android apps and 61.7% of iOS apps in Quokka’s scan of more than 150,000 Android and iOS apps throughout 2025, published in 2026. Quokka
67% of respondents said at least a quarter of their developers and engineers spent time on manual QA tasks, in Mobot’s survey of more than 500 mobile leaders conducted in 2023 and reported in January 2025.
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Market size estimates for mobile app testing
There is no single market-size number you can use without a scope label. The meaningful distinction is between testing services and testing solutions.Mordor Intelligence forecasts the testing-services market from $7.70 billion in 2025 to $9.02 billion in 2026, reaching $19.84 billion by 2031 at a modelled 17.09% CAGR over 2026–2031. In its 2025 segmentation, automated testing represented 46.05% of the services market, functional testing 41.30%, and North America 37.10%. These are proprietary market estimates and forecasts, not audited spending disclosures. Mordor IntelligenceTechSci Research uses a broader solutions category: $18.33 billion in 2025, forecast to reach $48.56 billion by 2031 at a 17.63% CAGR. That category includes tools, platforms, device farms, and services. Its larger estimate should not be compared directly with Mordor’s 2026 services estimate. TechSci ResearchFor your budget case, use a market forecast as context, not as evidence of your own tooling spend. The source’s category definition belongs beside the figure.
App stability benchmarks
Luciq’s 2025 outlook analysed telemetry from apps using Instabug during 2024. Its median crash-free session rate was 99.95%; the 25th percentile was 99.77% and the 75th percentile was 99.99%. The population is apps represented in Luciq’s platform telemetry, not a random sample of all mobile apps. LuciqThe 2024 telemetry showed a 99.91% iOS median crash-free session rate and a 99.80% Android median. At the 25th percentile, iOS was 99.66% and Android was 99.32%. Your own crash-free metric becomes more useful when you compare like-for-like release cohorts, devices, and session definitions.For Android-specific failure modes, Luciq reported median rates per 10,000 sessions of 2.62 ANR errors, 1.12 out-of-memory errors, 64–103 app hangs, and 134 forced restarts. An ANR is an application-not-responding failure. These are observed telemetry benchmarks, not universal acceptance thresholds.If a stability issue appears only on physical hardware, a generic aggregate metric will not locate it. Pair your benchmark with a deliberate real-device test matrix that reflects your actual traffic, OS versions, and device families.
Automation and test-reporting statistics
The Software Quality Pulse Report, published by Ranorex in May 2026, reports an average of 57% of QA tests automated among roughly 4,000 QA engineers, developers, security professionals, and engineering leaders. Because this is all-software survey data, it is not a mobile automation benchmark. RanorexThe same respondents reported that only about 26% of QA teams were mostly or fully integrated with DevOps pipelines, while 44.7% described themselves as understaffed. Both are respondent assessments; the report does not disclose its fieldwork date beyond its May 2026 publication.Bitrise offers an observed mobile delivery counterpoint. Across its more than 19 million anonymised builds, at least 45% of active workspaces ran identifiable CI tests in Q1 2026, and those workspaces accounted for about 86% of builds. Yet only 34% had test reporting enabled. BitriseThat reporting gap matters operationally. You cannot improve flaky-test behaviour, recurring failure categories, or release-to-release pass rates if your pipeline leaves no structured record. Define the test scenarios worth measuring before you scale the suite; this guide to mobile test cases and test scenarios can help you separate the two.Among Bitrise workspaces with more than 5,000 builds per quarter, at least 81.9% ran automated tests, 96.8% used build caching, and 80.6% used caching, test reporting, and observability together. Those numbers describe very high-volume Bitrise users, not every mobile engineering organisation.
AI adoption in mobile testing
A Censuswide survey commissioned by Tricentis gathered responses from 1,028 senior IT leaders and application developers in the US, UK, Germany, and Singapore between December 1 and 20, 2023. It found that 49% said AI was already part of their mobile app testing strategy, while 21% planned to implement AI testing tools within six months. Intelligent CIO EuropeRespondents expected AI and low-code or no-code tools to save about 40 hours of productivity per month compared with traditional manual processes. That is an expectation reported in a survey, not a production measurement of time saved.The same 2023 survey found that 47% used manual testing for mobile applications and only 27% believed their mobile development and testing strategy exceeded expectations. If you are evaluating AI-assisted testing, treat these as adoption and sentiment signals, then validate outcomes in your own pipeline. For implementation choices, see Quash’s practical overview of AI-powered mobile app testing.Bitrise recorded a different AI signal in build telemetry: AI-attributed builds grew 161 times year over year from Q1 2025 to Q1 2026. Bitrise attributes a build only when it finds a co-author line, bot trigger, or agent branch name, making this a minimum baseline rather than a complete measure of AI-generated work. Bitrise
What app-store enforcement reveals
Apple reviewed 7.77 million app submissions in 2024 and rejected 1.93 million, according to Apple’s 2024 App Store transparency data reported by MacRumors. The leading rejection categories were performance, legal, design, business, and safety. MacRumorsGoogle reported that it prevented more than 1.75 million policy-violating apps from being published on Google Play in 2025 and banned more than 80,000 bad developer accounts. It also reported that Play Protect scanned more than 350 billion Android apps daily. GoogleNeither disclosure proves that a rejected or blocked app skipped QA. Store decisions also involve legal, business, design, and policy requirements. They do show why your release checks should include performance, permissions, policy-sensitive flows, and security conditions rather than UI behaviour alone.A separate Tricentis-commissioned survey found that 90% of its 1,028 respondents estimated poor mobile app quality cost their business up to $2.49 million in lost revenue per year. This is a respondent-supplied ceiling estimate from four markets in 2023, not an audited average or independent mobile cost-of-quality benchmark.
The device fragmentation test matrix
Statcounter’s worldwide mobile web-traffic data for August 2026 showed six Android versions above 8% share: Android 16 at 26.01%, Android 15 at 17.15%, Android 13 at 14.88%, Android 14 at 12.96%, Android 12 at 10.12%, and Android 11 at 8.17%. This measures web traffic, not installed devices or your application’s user base. StatcounterDrizz cites DeviceAtlas and Scientia Mobile for an estimate of more than 24,000 Android device models in active global use. Its recommendation to test the top 15–20 device and OS combinations, typically covering 80–90% of an app’s active users, is a vendor rule of thumb based on traffic-weighted selection, not an independent prevalence study. DrizzYour device list should therefore follow your analytics and crash data. Global fragmentation tells you why a single reference phone is insufficient; it cannot tell you which devices your customers use.
Mobile app security findings
Quokka’s 2026 report analysed more than 150,000 Android and iOS apps scanned throughout 2025. It found HTTP URLs in 94.3% of Android apps and 61.7% of iOS apps, plus unencrypted sockets in 89.1% of Android apps. These are vendor-reported scanner findings in Quokka’s analysed population, not prevalence estimates for every app-store listing. QuokkaThe same scan reported SQL injection vulnerabilities in 87.9% of Android apps and 63.7% of iOS apps; hardcoded cryptographic keys in 47.8% of Android apps and 17.6% of iOS apps; and weak ECB encryption mode in 68.1% of Android apps. Use those findings as a reason to examine your own exposure, not as a prediction of your app’s defect count.The OWASP Mobile Top 10 provides a framework for categories including insecure communication, inadequate supply-chain security, insecure data storage, and insufficient cryptography. For a test plan that turns those categories into checks, use this guide to mobile app security testing.
Manual QA workload statistics
Mobot’s survey of more than 500 mobile leaders, conducted in 2023 and reported in January 2025, found that 67% said at least a quarter of their developers and engineers spent time on manual QA tasks beyond dedicated QA work. Around 75% said more automation would significantly improve release cadence, exploratory-test capacity, and automation-scripting output. MobotThis is the oldest evidence in this round-up. It remains useful because comparable newer public research on developer time spent specifically on mobile manual QA is scarce, but it should not be presented as a 2026 workforce census.
What the public evidence does not measure
The statistics above describe the category more reliably than they describe your next release. Four gaps remain material.
There is no independent mobile cost-of-quality benchmark.
The $2.49 million figure is a vendor-commissioned, four-market survey result from 2023. A multi-company study using audited remediation cost, lost revenue, and release data would answer the question more credibly.
There is no mobile-only automation rate in this source set.
The 57% figure is general software QA data. A useful mobile survey would distinguish unit, integration, UI, device, and exploratory testing.
There is no public emulator-versus-real-device failure distribution in this evidence.
A controlled study that runs identical suites in both environments could identify defect classes that appear only on hardware.
No first-party Quash data covers this question.
Quash has no supplied telemetry, recurring bug-pattern dataset, customer-language evidence, or completed experiment for mobile app testing statistics. A published, repeatable comparison of emulator and real-device results would fill a gap that public reports currently leave open.
Methodology and source limits
This report prioritises 2025–2026 publications where available and retains the date of older underlying data. Market figures from Mordor Intelligence and TechSci Research are proprietary estimates with different scopes. Luciq and Bitrise describe platform telemetry; their populations are their represented apps and workspaces, not all mobile development.Ranorex/Sembi, Tricentis/Censuswide, and Mobot report survey responses. A self-reported automation rate, an expected productivity gain, and a respondent-estimated financial impact are not observed production outcomes. Google’s figures are first-party enforcement disclosures, while MacRumors reports Apple’s transparency data. Quokka’s percentages are scan results from its measured app population, and OWASP supplies a risk taxonomy rather than prevalence data.
Conclusion
The most actionable mobile app testing statistics do not point to one universal automation target. They show a more practical operating problem: test execution is widespread, but reporting is incomplete; stability differs by platform and cohort; and device, store, and security risk extend beyond a scripted happy path.Use the external figures to frame your budget and coverage decision. Then make that decision against your own crash-free sessions, device-specific failures, test-reporting completeness, release rework, and manual QA time.
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