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Software continues to grow larger and more interconnected with every release. A single application might span dozens of services, devices, and user paths — and each one requires testing before launch. For QA teams, the sheer scale of that work can slow down delivery and strain resources. AI is starting to give QA teams a real way to manage that scale.
The AI-enabled testing market was worth (insert link) about $857 million in 2024. Analysts predict that it will reach $3.8 billion by 2032 — an impressive 20% annual growth. The results are already tangible. Caesars Entertainment modernized its automation strategy with AI-powered UI and API testing. The casino giant now saves more than a million dollars a year.
As adoption speeds up, the focus has changed. It's no longer a question of whether AI should be in QA. Now, it's about determining which platforms add the most value and how to pair them with the skills of human testers.
How Can AI Tools Be Used for QA Testing?
AI tools are reshaping QA workflows in five key areas:
- Test case generation: Platforms can build test cases from requirements or user behavior data, saving teams hours of manual scripting (DigitalOcean).
- Automated testing: AI agents execute and maintain tests, adapting when interfaces change.
- Test data generation: Generative models create realistic data while protecting sensitive information.
- Test optimization and prioritization: Algorithms determine which tests to run first, striking a balance between speed and coverage.
- Test planning and scheduling: Some platforms forecast workloads and plan runs to maximize efficiency.
Analyst reports indicate that AI automation enhances coverage and reduces repetitive maintenance. That said, human oversight remains crucial for accuracy and context. The tools are most powerful when they extend, rather than replace, the work of QA teams. Here are some of the best AI platforms QA testers use to boost their efficiency and impact.
Tool #1: Jetify
Jetify's TestPilot is an AI testing agent designed to generate, maintain, and run tests with minimal setup. In January 2025, Jetify launched Test Pilot, its own AI QA Engineer.Previously called Jetpack.io , Jetify currently works on desktop and their agent is able to navigate your app and develop a test plan as a user would do. TestPilot offers itemized reports for every test their AI agent runs.
Key Features:
- Plain-English test writing
- Self-healing scripts
- Maintain and updates test suite on every run
- Provides screenshot and detailed traces for each run
- Automatic updates when code changes.
- Simulation of real human interactions
Pricing: Tiered plans; free trials are available.
Website: jetify.com
Tool #2: testRigor
TestRigor uses AI to change natural language steps into executable end-to-end tests.Their platform allows you to write automated test scenarios in plain English instead of coding UI selectors and low-level interactions.One of the advantages Test Rigor offers is their support for web on desktop and mobile, on mobile and desktop applications.According to TestRigor test suites can be triggered from CI/CD or other automation workflows. TestRigor appears as a good solution if you have a testing team with low coding expertise. Individuals can create and maintain test cases without deep programming. In addition to that their platform includes an accessibility testing feature to flag A11y violations.
Key Features:
- Low-maintenance scripts
- Integration with CI/CD
- Plain-English authoring.
- Accessibility testing feature
Pricing: Free starter tier, with business and enterprise pricing on request.
Website: testrigor.com
Tool #3: Applitools
Applitools is an AI powered testing platform best known for its Visual AI technology, which goes beyond functional checks to catch layout shifts, rendering issues, and accessibility problems. Applitools supports end-to-end testing from creating test cases, execution, validation and maintenance. According to Applitools, if you can integrate your existing test automation into their SDK and add visual checkpoints to existing tests.
Key Features:
- Visual validation
- Cross-browser testing
- Functional and API support
- Integration/SDK support
- Integration with popular CI/CD tools.
Pricing: Usage-based; free developer accounts are available.
Website: applitools.com
Tool #4: Tricentis Testim
Tricentis Testim is an AI-powered test automation platform designed to streamline end-to-end testing for web and mobile applications. It uses machine learning to create, execute, and maintain automated tests with minimal manual effort. Testim’s core strength lies in its self-healing smart locators, which adapt to UI changes to reduce flaky tests and maintenance time. It integrates with popular CI/CD tools, supports both coded and codeless testing, and helps QA teams accelerate release cycles while maintaining high software quality.
Key Features:
- AI-driven test authoring
- Self-healing
- Analytics
- Integration with dev pipelines
Pricing: Enterprise-focused; quotes on request.
Website: testim.io
Tool #5: Mabl
Mabl isa low-code test automation platform that helps teams continuously test web applications and APIs. It uses AI and machine learning to automatically detect UI changes, identify regressions, and maintain tests with minimal manual effort. Mabl integrates seamlessly with CI/CD pipelines and collaboration tools like Jenkins, GitHub, and Slack, enabling efficient end-to-end testing across the development lifecycle. Its cloud-based architecture and visual reporting make it easy to scale testing, improve quality, and accelerate release cycles.
Key Features:
- Auto-healing UI tests
- Integrated reporting
- Visual testing
- Regression detection
Pricing: Free trial; pricing by request.
Website: mabl.com
Tool #6: Tricentis Tosca
Tosca is an enterprise-grade test automation suite that incorporates AI to accelerate risk-based testing. Tricentis Tosca supports web, desktop, mobile and APIs. It integrates into CI/CD pipelines. This type of platform works well with large or enterprise-level organizations but won’t necessarily work as well for smaller teams or startups with small budgets.
Key Features:
- Model-based test automation
- AI-powered test case design
- Broad application coverage
Pricing: Enterprise licenses; quotes on request.
Website: tricentis.com/tosca
Tool #7: Perfecto
Perfecto is a cloud-based testing platform designed for automated and manual testing of web and mobile applications. It enables teams to execute tests across a wide range of real devices and browsers, ensuring consistent performance and user experience. With integrations into CI/CD pipelines, Perfecto supports continuous testing, helping organizations accelerate release cycles and improve software quality. Its advanced analytics and AI-driven reporting features make it easier to identify root causes of failures and optimize test coverage.
Key Features:
- AI-assisted root cause analysis
- Test analytics
- Web and mobile coverage.
Pricing: Flexible pricing based on concurrency and usage.
Website: perfecto.io
Tool #8: Sauce Labs
Sauce Labs is a leading cloud-based testing platform that allows developers and QA teams to run automated and manual tests across thousands of browser, device, and OS combinations. It provides seamless integration with popular testing frameworks and CI/CD tools, making it easy to include cross-browser and mobile testing in continuous delivery pipelines. Sauce Labs is praised for its scalability, reliability, and detailed test analytics that help quickly identify and fix issues. The platform also offers real-device testing and visual testing capabilities, ensuring accurate real-world results. While its pricing may be higher than some competitors, Sauce Labs delivers strong enterprise-grade performance and comprehensive test coverage that justify the investment.
Key Features:
- AI-driven failure analysis
- Visual regression detection
- Real device testing at scale.
Pricing: Subscription tiers for individuals, teams, and enterprises.
Website: saucelabs.com
Which AI Testing Platform Should You Use?
Choosing the right AI platform depends on context.
Budget and team size: Tools like testRigor work well for smaller teams with limited resources. Enterprises often choose platforms such as Tosca or Perfecto, which require more investment but deliver more extensive coverage.
Use cases: Applitools excels when visual accuracy is the priority. Jetify and testRigor focus on natural-language scripting, making it easier for non-technical contributors to participate in testing.
Integration: Integration matters. Mabl and Sauce Labs fit smoothly into standard DevOps pipelines, reducing setup time and allowing teams to run tests where they already work.
AI testing platforms can speed up workflows and expand coverage, yet they aren't designed to replace every aspect of QA. Human testers are crucial for exploratory testing. They provide usability insights and catch nuanced bugs that automation can't predict. For a deeper dive, see PLUS QA's blog post on why manual testing remains essential alongside AI tools.
By combining QA automation tools with skilled manual testing, you get the best of both worlds. If you're exploring AI testing tools and seeking a partner to fill the gaps with expert manual QA, please get in touch with us. We'd be happy to talk through how our testers can help strengthen your next release.