The Best 10 AI Testing Tools in 2024

Updated August 2024

Introduction

AI has changed industries globally, including software testing. AI-powered tools are transforming how QA teams handle testing. This article explores how you can use AI testing tools to improve your testing strategies. We’ll also introduce the best AI testing tools that can take your testing efforts to the next level.

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Top 10 AI Testing Tools - List

Top 10 AI Testing Tools - Details

1. Functionize: Cross-platform UI and API AI Testing Tool

Type: AI/ML Test Automation Tool

Functionize is an AI testing tool that uses an innovative approach, incorporating artificial intelligence and machine learning, to transform the landscape of automated testing. This platform adapts to changes in your application, ensuring your tests remain reliable even as your software evolves.  It helps you release software faster and with greater confidence. 

By automating repetitive tasks, Functionize lets you focus on what matters most—delivering quality software quickly. Functionize goes beyond conventional test automation. With AI software testing and machine learning at its core, it offers intelligent and adaptable solutions. It's more than just a testing tool; it's a dynamic solution that perfectly meets modern software development's demands.

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Customer rating

G2 reviews:12; G2 rating: 4.7 out of 5 stars

Features Valued by Users

• Alerts/Notification Systems
• API Integration
• Data Visualization
• Parameterized Testing
• Real-Time Monitoring
• Requirements-Based Testing
• Test Management
• Parallel Execution Support

Advantages

• AI-Powered Testing: Functionize utilizes artificial intelligence and machine learning to enhance test automation. This enables it to adapt to changes in the application's UI and functionality, making tests more robust and reducing maintenance efforts.
• Self-Healing Tests: Functionize can automatically detect and repair broken test scripts when changes occur in the application, reducing the need for manual intervention and script updates.
• Parallel Testing: It supports parallel test execution, allowing for faster test runs and improved efficiency, especially in large-scale testing environments.
• Cross-Browser Testing: It supports testing across multiple browsers and devices, ensuring compatibility and a consistent user experience.
• Scalability: The tool is designed to scale with your testing needs, making it suitable for both small projects and large enterprise applications.

Disadvantages

• Limited Offline Testing: As a cloud-based tool, it may not be ideal for applications that require testing in completely isolated or offline environments.

Platform

• Web-based

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2. Sauce Labs

Type of the Testing Tool

Sauce Labs is a cloud-based testing platform designed for mobile and cross-browser testing. You can run tests on a scalable infrastructure with over 700 browsers, platforms, operating systems, and device combinations. The platform supports both automated and manual testing for desktop and mobile applications. You can use Selenium, Appium, and JavaScript unit testing frameworks. This AI software testing tool also offers machine learning-based analytics to provide insights for your test analysis.

Customer rating

G2 reviews: 142; G2 rating: 4.3 out of 5 stars 

Capterra reviews: 29; Capterra rating: 4.4 out of 5 stars

Features Valued by Users

• Parallel Execution Support
• Requirements-Based Testing

Advantages

• Wide Range of Browsers, Devices, and Operating Systems: Sauce Labs supports testing on over 700 different combinations.
• Live Testing: Provides real-time interaction with applications during testing.
• Responsive Testing: Ensures applications perform well on different screen sizes and resolutions.
• Integration with Popular Development Tools: Integrates with tools like Jenkins, GitHub, and Jira.

Disadvantages

• More expensive than some other options
• Confusing User Interface: Users may find the tool's interface confusing due to its setup complexity.
• Stability Concerns: May cause disruptions and delays in the testing process.
• Limited Reporting and Customization: lack of comprehensive reporting and customization options for dashboards

Platform

• Cloud-based

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3. Test Complete

Type of the Testing Tool

TestComplete is an AI tool for automation testing by SmartBear Software. You can use it to recognize objects and controls in your tested applications. It provides special commands to simulate user actions. You can also set specific checkpoints to easily verify the application's state during your test runs.

Customer rating

G2 reviews: 97; G2 rating: 4.2 out of 5 stars

Capterra reviews: 6; Capterra rating: 4.0 out of 5 stars

Features Valued by Users

• Hierarchical View
• Reporting & Statistics
• Parallel Execution Supports 

Advantages

• Support for Different Types of Applications: Test Complete supports desktop, web, and mobile applications.
• Multi-Language Support: TestComplete allows writing tests in various languages like VBScript, JavaScript, and C# Script.
• AI-Driven Object Recognition Engine: The AI-powered visual object recognition technology improves accuracy and efficiency in identifying and interacting with application elements.
• CI/CD Integration: TestComplete can easily integrate with CI/CD tools like Jenkins and Azure DevOps, streamlining your development and testing workflows.
• Parallel Testing: Run multiple tests simultaneously to speed up the testing process and increase productivity.

Disadvantages

• Costly: TestComplete is not a free tool, and its licensing costs can be significant for smaller teams or projects.
• Supports Only Windows Platform: It is primarily designed for Windows environments, limiting its use to teams working on macOS or Linux.
• High Learning Curve: Requires substantial learning to master both the tool's functionality and the underlying testing methodologies.
• Limitation with Cloud-Based Testing: TestComplete's capabilities in cloud-based testing are somewhat limited.

Platform

• Windows

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4. Tricentis Tosca

Type of the Testing Tool

Tricentis Tosca offers advanced test automation with AI-powered, codeless, end-to-end capabilities. You can test across more than 160 technologies seamlessly. It combines UI, API, and data testing into one test case. With its Vision AI feature, you can enhance UI testing through self-healing and recognize UI objects across different control types. This extends automation to various use cases, including remote desktop apps and legacy systems.

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Customer ratings: 

G2 reviews: 71;  G2 rating: 4.2 out of 5 

Capterra reviews: 17; Capterra rating: 4.3 out of 5 

Features Valued by Users

• API Integration 
• Data Visualization 
• Hierarchical View Option 
• Parameterized Testing 
• Requirements-Based Testing 
• Parallel Execution Support

Advantages

• Ease of Learning and Implementation: Tricentis Tosca is highly regarded for its user-friendly interface and ease of learning. 
• Efficiency in Automation: The software enables efficient script automation, helping teams meet project deadlines effectively.
• Sophistication and Thoughtful Design: Tricentis Tosca is praised for its sophisticated design and thoughtful automation suite. 
• Helpful Add-Ins: The availability of helpful Add-Ins enhances the user experience and makes decision-making around adopting Tricentis Tosca straightforward. 

Disadvantages

• High Cost and Certification Fees - the tool's steep price and certification costs might be prohibitive for smaller organizations with limited budgets.
• Challenging Learning Curve - may require substantial time and effort for configuration and comprehension.
• Limited Integrations - while it supports integrations with other tools, some restrictions can impact its overall functionality, limiting seamless collaboration with diverse toolsets.
• Dependency on Technical Expertise - achieving optimal results requires deep technical knowledge of software automation, posing a challenge for users without extensive technical expertise.

Platform

• Can be used on a variety of platform

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5. Katalon Platform

Type of the Testing Tool

Katalon is an AI-based testing tool for quality management. You can use it for testing web, mobile, API, and desktop applications. It is designed for ease of use, even if you have little to no coding experience. Katalon helps you automate your testing processes with features like record and playback, test case management, and integration with popular frameworks like JUnit, TestNG, and Cucumber. Its user-friendly interface allows you to create and execute tests quickly. 

Customer ratings: 

G2 reviews: 108, G2 rating: 4.5 out of 5

Capterra reviews: 707, Capterra rating: 4.4 out of 5

Features Valued by Users

• Alerts/Notification Systems
• API Integration
• Data Visualization
• Hierarchical View Option
• Parameterized Testing
• Requirements-Based Testing
• Test Management
• Parallel Execution Support

Advantages

• Versatility: Katalon Studio offers comprehensive testing capabilities for web, mobile, API, and desktop applications.
• Scalability: It provides flexible automation support suitable for projects and teams of any size.
• Seamless Integration: Katalon easily integrates with CI/CD ecosystems, streamlining development and testing workflows for enhanced efficiency.
• Cross-Browser Compatibility: The tool supports cross-browser testing across macOS, Windows, Linux, iOS, and Android, ensuring broad compatibility.
• User-Friendly Interface: Its intuitive interface simplifies codeless test automation management.

Disadvantages

• Learning Curve: While user-friendly, there can still be a learning curve for mastering all features.
• Resource-Intensive: Running tests on a large scale can be resource-intensive.
• Cost: The cost associated with Katalon, especially for large-scale usage, can be a consideration for some organizations.

Platform

• Cloud-based

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6. ACCELQ 

Type of the Testing Tool

ACCELQ is a cloud-based, codeless test automation tool that uses AI.  This platform simplifies testing for web UI, API, mobile, and desktop applications. You can easily integrate it with existing tools like Jira, TFS, Jenkins, and Bamboo. ACCELQ focuses on quality lifecycle management, covering everything from test design to change management in a cohesive strategy.

Customer ratings: 

G2 reviews: 51; G2 rating: 4.8 out of 5

Capterra reviews: 42; Capterra rating: 4.8 out of 5

Features Valued by Users

• API Integration
• Hierarchical View Option
• Parameterized Testing
• Requirements-Based Testing
• Test Management
• Parallel Execution Support

Advantages

• Codeless Automation: ACCELQ offers a codeless approach to test automation.
• Versatility: The platform supports automation across various testing domains, including Web UI, API, Mobile, and Desktop.
• AI-Powered Automation: ACCELQ leverages AI capabilities. The Intelligent Element Explorer, coupled with natural language programming, contributes to faster and smarter automation.
• Integration Ease: ACCELQ seamlessly integrates into existing tool ecosystems such as Jira, TFS, Jenkins, and Bamboo.
• Quality Lifecycle Management: The platform emphasizes Quality Lifecycle Management, offering an integrated strategy from Test Design through Change Management to enhance overall testing quality.

Disadvantages

• Learning Curve: Users may face a learning curve, especially if they are new to the platform.
• Cost: The cost of using ACCELQ could be a consideration for some organizations, especially smaller ones.

Platform

• Can be used on a variety of platform

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7. Applitools

Type of the Testing Tool

Applitools is a testing automation platform known for its advanced AI-aided visual testing. You can use it for functional testing and visual regression testing with its unique Visual AI technology. It offers Smart Assist to provide suggestions and improve your tests. Applitools integrates with many important frameworks, making it versatile and easy to use in your existing setup.

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Customer ratings: 

G2 reviews: 59; G2 rating: 4.4 out of 5 

Capterra reviews: 30; Capterra rating: 4.6 out of 5

Features Valued by Users

• Hierarchical View Option
• Parameterized Testing
• Requirements-Based Testing
• Test Management
• Parallel Execution Support

Advantages

• Self-Healing Tests: Applitools' Visual AI technology enables tests that can self-heal and self-maintain.
• Lightning-Fast Test Creation: The platform simplifies the creation of a comprehensive suite of tests in a matter of minutes.
• Excellent Integrations: Applitools offers a suite of integrations, making it compatible with various testing frameworks and technologies.

Disadvantages

• Complex Dashboard: Some users find the platform's dashboard to be clunky and complex.
• Incomplete JavaScript Documentation: The JavaScript documentation provided by Applitools has been noted as incomplete, which can pose challenges for users seeking comprehensive guidance.
• Slow Execution: In some cases, test execution speed may not meet the expectations of users.

Platform

• Cloud-based

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8. Testsigma

Type of the Testing Tool

Testsigma is an AI automation testing tool aimed at accelerating your testing cycles. It provides a wide variety of test automation features, including automated test case execution, test case management, and reporting.

Customer ratings: 

G2 reviews: 28;  G2 rating: 4.5 out of 5

Capterra reviews: 17; Capterra rating: 4.2 out of 5

Features Valued by Users

• Alerts/Notification Systems
• API Integration, Hierarchical View Option
• Parameterized Testing
• Requirements-Based Testing
• Test Management
• Parallel Execution Support
• Regression Testing
• Codeless Scripting
• Multi-Platform Testing

Advantages

• Scriptless Testing in Plain English: Enables easy test creation using plain English, reducing complexity and fostering collaboration.
• Automated Periodic Executions: Schedule tests to run automatically at set intervals, ensuring continuous testing without manual oversight.
• Detailed Regression Test Reports: Generates detailed reports for regression tests across multiple device configurations.
• Customizable Test Prioritization: Prioritize and filter tests to create lean and optimized regression test suites.
• Seamless CI/CD Integrations: Integrates smoothly with popular CI/CD tools like Jenkins, JIRA, Slack, and more.

Disadvantages

• Initial Setup: Setting up test automation frameworks, including TestSigma, can be time-consuming and require expertise.
• Cost: Licensing and maintenance costs associated with test automation tools can be substantial.
• Not Suitable for All Tests: Some types of testing, such as exploratory testing or usability testing, may still require manual intervention.
• Limited UI Changes: Frequent changes to the user interface can lead to test script failures and necessitate updates.

Platform

• Cloud-based

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9. Mabl

Type of the Testing Tool

Mabl stands out as an AI testing tool designed for test automation, offering low-code testing capabilities without scripting requirements. Covering web, mobile, API, accessibility, and performance testing comprehensively, Mabl provides a robust framework for modern software development. Its intuitive graphical user interface (GUI) makes testing powerful yet accessible.

Customer ratings

G2 reviews: 35; G2 rating: 4.5 out of 5

Capterra reviews: 66, Capterra rating: 4.0 out of 5

Features Valued by Users

• API
• Collaboration Tools
• Hierarchical View
• Reporting & Statistics
• Software Testing Management
• Supports Parallel Execution

Advantages

• Time-saving Automation: TestRigor immediately starts running tests when a new application is added, saving valuable time for the QA team.
• Excellent Customer Service: Customers appreciate the professional, friendly, and helpful support provided by TestRigor's customer service team.
• Ease of Use: TestRigor simplifies testing processes, making it easier for customers to manage and execute tests efficiently.
• Modern Interface: The modern look and feel of TestRigor, along with its strong support features, enhance user experience and confidence in the product.

Disadvantages

• Issues with Test Execution: TestRigor sometimes fails to locate selected fields, buttons, or page elements during test creation, causing tests to abruptly stop without clear error messages.
• Logging Out During Tests: The tool occasionally logs itself out during testing, which can disrupt the test process and affect test results.
• Difficulty with Test Replay: TestRigor struggles with replaying tests successfully on the first try, posing challenges for test maintenance.

Platform

• Cloud-based

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10. TestRigor

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Type of the Testing Tool

TestRigor is an AI-based testing tool that simplifies software QA testing by allowing testers to create codeless end-to-end functional tests for web, mobile (native and hybrid), desktop, and API applications. It includes built-in features for email, visual, and audio testing and automates tests faster than traditional tools. TestRigor supports parallel test execution, integrates easily with issue management and CI/CD tools, and scales effortlessly for software testing needs.

Customer ratings

G2 rating: 4.6 out of 5 (16 reviews)

Capterra rating: 4.6 out of 5 ( 5 reviews)

Features Valued by Users

• API Integration 
• Collaboration Tools
• Hierarchical View
• Monitoring
• Reporting & Statistics
• Requirements Management
• Software Testing Management
• Supports Parallel Execution
• Test Script Reviews

Advantages

• Ease of Use: TestRigor allows writing and generating scripts using simple English statements.
• Time-Saving: Enables quickly and efficiently writing end-to-end UI tests without needing to use any programming language.
• Dedicated Customer Support: TestRigor provides a responsive Customer Support Team that is readily available to assist with any issues or questions you may have.

Disadvantages

• Limited Customization: This may lack the level of customization and flexibility available with traditional coding-based testing frameworks.
• Learning Curve: If the users are unfamiliar with its interface, may still encounter a learning curve when initially using testRigor.
• Dependency on Platform Updates: Changes to the platforms it supports may impact testRigor's effectiveness.

Platform

• Web-based

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Selection Criteria and Methodology of the Best AI Testing Tools

For selecting the best AI testing tools we did a comprehensive evaluation based on several crucial criteria. Our goal was to ensure that we present a range of tools that effectively meet different testing needs. Here’s how we made our selection:

Selection Criteria

1. Popularity and Community Supportsome text
   • We focused on tools with substantial user bases and robust community engagement.
   • Each tool was required to have garnered feedback from at least 15 users across major review platforms such as G2.com and Capterra.
   • Tools needed to achieve a minimum rating of 4.2 out of 5 on either Capterra or G2.
   • We avoided tools with any entirely negative reviews to ensure a positive user experience.
2. Features and Functionalitysome text
   • We assessed each tool’s range of features specifically for AI testing. Priority was given to tools that offer comprehensive functionalities to handle different areas of AI testing.
   • Key functionalities included support for different AI models, automated testing capabilities, and integration with machine learning pipelines.
3. User Experience and Interfacesome text
   • User feedback was analyzed to determine how intuitive and user-friendly each tool is. Tools that offer an easy-to-navigate interface and streamlined user experience were preferred.
4. Scalabilitysome text
   • The tools were evaluated for their ability to accommodate both small-scale and large, complex AI projects. We examined user feedback and “Company Size” information available on G2 to ensure the tools could scale effectively.
5. Integration Capabilitiessome text
   • Tools that seamlessly integrate with popular development environments, AI frameworks, and continuous integration systems were given preference. This includes compatibility with tools for data management, version control, and deployment.
6. Innovation and Updatessome text
   • We prioritized tools that demonstrate active development, frequent updates, and a commitment to evolving with the latest AI trends and technologies.

Methodology

To ensure the accuracy and relevance of our selections, we employed the following methodology:

1. Data Collectionsome text
   • We collected data from major review sites including G2.com and Capterra, focusing on user reviews, ratings, and feedback for each tool.
2. Feature Analysissome text
   • We performed a detailed analysis of the features and capabilities of each tool, paying particular attention to their AI-specific testing functionalities.
3. User Experience Reviewsome text
   • User feedback was reviewed to gauge the ease of use and overall user satisfaction with each tool.
4. Scalability Assessmentsome text
   • We evaluated each tool’s scalability based on user feedback and information regarding their suitability for different project sizes.
5. Integration and Innovation Checksome text
   • We assessed how well each tool integrates with other essential systems and examined their track record for innovation and updates.
6. Selection and Validationsome text
   • The tools were selected based on the criteria mentioned, and their relevance and effectiveness were validated through user reviews and expert opinions.

This methodology ensured a thorough and unbiased selection of the best AI testing tools, providing valuable insights for our readers. No sponsorships were involved in the evaluation process; all selections were made based on independent analysis and genuine user feedback.

How to Choose The Right AI Testing Tools for Your Team

Choosing the right AI testing tool for your team involves several key considerations:

1. Project Requirements: Understand your project's specific testing needs to save time and money.
2. Team Skills: Evaluate your team's ability to handle coding or prefer codeless tools.
3. Budget: Set a realistic budget that fits your project's financial limits.
4. Ease of Use: Choose a tool with user-friendly interfaces or low-code options for easier test case creation and maintenance.
5. Integration: Make sure the tool fits well with your current systems to streamline testing processes.

By considering these factors, you can choose an AI testing tool that enhances productivity, matches your team's skills, and achieves your project objectives efficiently.

How to Use AI Automation Testing Tools

AI automation testing tools transform software testing by handling tasks like generating test cases, predicting bugs, and analyzing results. They significantly boost testing efficiency, effectiveness, and reliability. These tools automate mundane tasks, freeing you to tackle more complex testing scenarios. They also excel at predicting and pinpointing defects early in the testing phase, ensuring thorough software evaluation.

Integrating AI into software testing is vital for accelerating release cycles and enhancing software quality. By automating repetitive tasks, you can expedite software deployment. AI tools also proactively identify and resolve potential defects before they impact users, ensuring smoother operations.

Automate AI Testing: How and Why to Do It 

There are numerous advantages of using AI software testing tools. They include faster testing, improved efficiency, and better accuracy. Here are some effective ways you can integrate AI into your testing workflow:

• Automated Test Data Generation: Creating test data automatically using artificial intelligence saves time and effort. It also ensures comprehensive test coverage.
• Low/No-Code Testing: The utilization of low/no-code testing tools simplifies the creation and maintenance of test cases.
• Self-Healing Tests: Self-healing automation powered by artificial intelligence prevents test failures by updating tests automatically after code changes.
• Accelerated Testing: Testing driven by AI automates repetitive and long-lasting test scripts thereby speeding up your testing process.

Conclusion

• AI testing tools are advanced software solutions that use artificial intelligence to enhance and automate the testing process. 
• AI tools for automation testing can generate test cases, predict bugs, and analyze results to improve the efficiency and accuracy of software testing.
• When choosing AI testing tools, focus on those that align with your project's specific needs to save time and money.
• By automating tasks and predicting defects, the best AI automation testing tools simplify test case creation and maintenance. 
• AI tools for software testing save time, prevent test failures with self-healing features and accelerate your testing process with generative AI testing tools.