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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.
Key Features:
- Plain-English test writing
- Self-healing scripts
- Automatic updates when code changes.
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.
Key Features:
- Low-maintenance scripts
- Integration with CI/CD
- Plain-English authoring.
Pricing: Free starter tier, with business and enterprise pricing on request.
Website: testrigor.com
Tool #3: Applitools
Applitools is best known for its Visual AI technology, which goes beyond functional checks to catch layout shifts, rendering issues, and accessibility problems.
Key Features:
- Visual validation
- Cross-browser testing
- Functional and API support
- Integration with popular CI/CD tools.
Pricing: Usage-based; free developer accounts are available.
Website: applitools.com
Tool #4: Tricentis Testim
Testim is an AI-powered platform built to speed up UI testing.
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 emphasizes agentic workflows, blending AI with automation to streamline testing across web and mobile.
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.
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, part of Perforce, delivers cloud-based test automation with AI features for faster execution and debugging.
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 one of the best-known cloud testing platforms, layering AI on top of its massive device/browser farm.
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.