15 Best AI Testing Tools that You Should Know

Over the years, software developers have heavily relied on manual testing processes, which continue to play a vital role in the testing phase. However, it’s important to acknowledge that there are scenarios where test automation becomes important too. That is where test automation tools come in handy. In recent years, automated testing has emerged as a valuable addition to the field of software testing. According to a report, a significant 97% of application testers have already implemented automated testing into their workflows. The market offers a wide range of AI testing tools, with hundreds of options available. To help you make an informed decision, here is a curated list of the top 15 AI testing tools to choose from.

What are AI Testing Tools?

Testing tools that make use of AI to offer the features that testers can use are called AI testing tools. But this is a very basic explanation.

In a broader sense, AI testing tools provide a playground for testers to create advanced, intelligent, and self-optimizing tests for any kind of testing. These tests are often self-healing and adaptive to any changes that happen in the code. Moreover, with AI driving the testing scenario, the use of Machine Learning (ML) makes test case creation, execution, and maintenance quite easy.

These tools assist humans in a myriad of testing activities and require minimal to no intervention for test case creation, test data generation, test execution, reporting and analytics, and integration capabilities.

Why We Need AI Testing Tools?

The testing landscape is fast-paced right now. With quick release cycles, increased dependencies on third-party software, and the use of CI/CD systems, testing has become not only an essential part of SDLC but also quite challenging or complex. More often than not, to stay on track with the deadlines, applications get released without proper and complete quality checks. Manual testing further exacerbates the situation.

However, as AI coding assistants and automation testing platforms surface, such problems take a backseat. These smart solutions bring down operational costs while ensuring the applications under test undergo sufficient testing. 

If you go by figures, businesses that use AI for testing, in any form, report almost a 30% reduction in testing costs and a 25% improvement in testing efficiency.

While possible cybersecurity and minor mishaps are expected to occur even when using AI-driven testing techniques, they can improve with time. Meanwhile, AI test automation tools are surely making test execution less cumbersome.

Benefits of AI Testing Tools

AI testing tools have transformed the way we test software applications, with their ability to automate the testing process and improve the accuracy of test results. They offer several benefits to automation engineers and developers, including cost savings, enhanced defect-tracing capabilities, self-healing capabilities, and more. Additionally, most of them are codeless testing tools, making it easy for anyone to script. In this post, we will explore some of the key benefits of AI testing tools and how they can help improve software testing processes.

Here are some of the main benefits of AI testing tools.

• Improved accuracy of test results
• Time and cost savings as they don’t require scripts
• Enhanced defect-tracing capabilities
• Self-healing capabilities after encountering errors
• Codeless testing, making it easy for anyone to script
• Continuous testing capabilities
• Nearly zero maintenance needs
• Improved API testing capabilities

15 Best AI-Powered Testing Tools List

Test automation tools are increasingly incorporating AI into their operations to enhance their capabilities. These AI-driven features include intelligent test case generation to predict and create test scenarios based on application usage patterns. Machine learning algorithms improve element identification, auto-healing, and reporting and analytics. 

Additionally, AI in test automation tools helps to automatically detect anomalies, prioritize test cases, and optimize test execution.

The 15 AI-Powered tools mentioned here are popular among testers, both beginners and experienced, as they combine legacy approaches (coding-based) with modern methods (Agile and codeless). Some of them are new entrants with a focus on propelling the testing forward by using AI and ML technology.

Let’s have a look!

Top AI Testing Tools – Comparison

Here is a comparison of the top 5 AI-powered testing tools in the market,

1. Testsigma

Testsigma is a robust, cloud-based, low-code GenAI-driven test automation platform that allows you to automate web, mobile, desktop, and API testing in one place. It makes your test automation 10x faster by simplifying the entire test creation, execution, reporting, and maintenance process.

It makes automated testing inclusive for both technical and non-technical members by supporting codeless and code-based testing in the same platform. It speeds up the overall testing process and improves the quality of testing.

Features

Zero setup time: You don’t have to spend time setting up any testing infrastructure. Create a free trial account and that’s all you need to access the testing platform on the cloud.

Low learning curve: Start creating automated tests in plain English using NLP-based testing or Recorder.

Data-driven testing: Data-driven capabilities for real-life test cases, allowing you to automate your tests and get reliable results

Integration support: Provides seamless integrations with 30+ top CI/CD tools, project management, collaboration, and bug-tracking tools.

CI/CD Integration: Integrating your automated tests into existing CI/CD and DevOps pipelines allows you to continuously test, accelerate feedback loops, and ship code faster. 

Test Reporting: Get detailed and actionable test insights for every test run. Allows developers and testers to collaborate and speed up the feedback and bug fixing.

Testsigma Copilot: Your GenAI assistant for high-quality testing

Testsigma Copilot is a GenAI assistant for QA teams that help improve testing quality and productivity. Apart from the AI-driven test automation capabilities supported by Testsigma, Copilot is specifically designed for QA teams to assist them with the entire software testing process by providing smart test suggestions. How QAs can benefit from Testsigma Copilot:

• Generate test cases automatically from multiple inputs: user stories, prompts, or Figma designs.
• Suggests additional user scenarios to cover for testing
• Get 70% automation coverage by covering even edge case scenarios.
• Automated API test case generation

2. TestCraft

TestCraft acquired by Perfecto, is currently named Perfecto Scriptless supports web and mobile testing. Moreover, it is developed to allow both manual and automated testing. The tool is best for delivering tests for web-based software at super speed. Besides, it can be scaled to offer the highest quality industry-based standards. Furthermore, it has the best features for running repetitive tests.

Features

• Multi-language support. Developers can create scripts in multiple languages and run them on the tool.
• Has a copy-to-clipboard feature where users can copy tests and paste them into the clipboard
• Test idea generation tool which uses advanced GPT technology to test websites
• Integration feature for integrating with other tools

3. Appvance

Appvance is a software testing tool that uses generative AI to accomplish testing tasks using artificial intelligence. The goal behind using Appvance for every tester should be to cover as much area as possible under AI. Claiming to increase the coverage up to 100% with AI, Appvance doesn’t demand any maintenance work from the testers which is always a major concern for testers.

Features

• Appvance can analyze the test runs, keeping the application’s exploration in mind. This allows the tool to provide new test cases for the missing areas and conduct exploratory testing in the process.

• Enhancing the application visibility by 10x, Appvance’s artificial intelligence can explore all the paths from every point to create newer test cases and expose hidden points for testing.

• Since Appvance explores various deep points in the application, it can define a complete health chart which is essential in understanding any future flaws very early in the system.

• Appvance supports test creation in low-code format or just operates the application like manual testing and converts actions into test cases easily.

• The tool is capable of performing different testing on different domains such as web, and mobile, and services such as APIs.

4. Worksoft Certify

A powerful test automation tool for enterprise-level testing is Worksoft Certify. It is specially tailored for complex enterprise applications and specializes in automating business process validation with a focus on ensuring that critical business workflows function correctly across diverse systems such as SAP, Oracle, and Salesforce. It involves intelligent automation features powered by AI, that includes self-healing scripts and test optimization.

Although the testing environment is scriptless, it still comes with a fair share of learning curve. Yet it is easier to use for non-technical users compared to the code-based tools. 

5. OpenText UFT One

OpenText UFT One is a functional testing software equipped for both front-end and back-end functional testing. It helps accelerate testing and provides AI-based technology to understand application elements and learn the intricacies along the way.

Features

• UFT One comes with a wide variety of testing domain support including API testing, end-to-end testing, SAP testing, web testing, and more.

• The tool comes with object recognition and identification of visual patterns that help identify elements based on patterns rather than locators.

• OpenText UFT One provides functional labs for testing mobile applications using cloud infrastructure. 

• The platform supports parallel test execution which helps cut down time and shorten the feedback loop for release.

6. Telerik Test Studio

Working according to the modern test cycle, Telerik Test Studio provides a platform for developers, testers, and managers to easily manage test automation. The Test Studio incorporates patented algorithms that help stabilize tests and increase test coverage across the suites without any additional work.

Features

• Telerik Test Studio provides a record-and-playback facility to record the automated test and run it on multiple sessions later.

• The platform provides an intensive monitoring feature to easily observe all the anomalies at the micro level.

• Telerik Test Studio provides multiple features to minimize the tester’s maintenance work. This includes unique element detection (patented), a centralized object repository, and intelligent suggestions.

• The platform covers multiple test domains such as web test automation, desktop automation, API automation, and responsive testing.

7. Sauce Labs

Features

• An error reporting tool that monitors and generates reports for errors
• Cross-browser tool for combined testing of browsers and OS
• Visual tool for conducting automated visual and UI tests
• Mobile tool for testing real and remote mobile devices
• API tool for testing and monitoring APIs

8. TestComplete

TestComplete is an intuitive tool with dynamic UI testing elements. Additionally, it contains a feature known as checkpoints which test images, tables, and app properties. It is a scriptless tool that allows users to trigger tests using keywords or the record-and-play feature. Furthermore, the tool features data-driven testing for web, PC, and mobile UI tests. Above that, it performs test report analysis and generates a report.

Features

• Non-stop testing for DevOps
• Parallel testing features for mobile, PC, and web-based app tests
• BitBar feature for scaling mobile and web tests
• Ability to reuse automated UI tests for a wide range of projects
• Data-based and automated reporting and analysis tools

Check here – TestComplete vs Selenium

9. Katalon Studio

A popular tool in the test automation space is Katalon. It comes with an ability to provide an all-in-one solution with an intuitive interface, which allows users to create, execute, and manage automated tests efficiently. Not to mention that it is built on top of open-source automation frameworks, such as Selenium and Appium with a specialized IDE interface for web, API, mobile, and desktop application testing. Its AI capabilities include self-healing, automated test generation, AI-Powered analytics, and NLP-based test scripting.

Another aspect that makes Katalon quite popular is the ease of use that even non-technical individuals or beginner testers can employ for building and running tests. It allows scriptless test creation and advanced scripting option for complex testing process.

Features

• Its AI-driven Smart Wait feature improves test stability by dynamically adjusting wait times for web elements.
• Integrates seamlessly with CI/CD pipelines for robust reporting and analytics.
• Employs machine learning algorithms to recommend test objects and automatically heal broken test scripts.
• Heavily popular for developing and executing complex API tests, including SOAP, REST, and GraphSQL.
• Has a bit of learning curve, but smoother than script-based automation tools.

10. Tricentis TOSCA

Another famous tool in our list is Tricentis TOSCA. It offers a comprehensive, end-to-end testing through automation through model-based approach. TOSCA allows users to create reusable test assets with minimal scripting. Its use of AI includes advanced test case design, self-healing automation scripts, and intelligent test data generation.

Its key features include risk-based test optimization and a powerful test data management. TOSCA avails AI to analyze historical data and predict which areas of the application are most likely to fail and to help prioritize test cases based on potential business impact for risk-based testing. For efficient test data management, AI algorithms assist in generating and managing test data that are realistic and near to real life scenario.

Features

• Supports a wide range of technologies, including web, mobile, API, and desktop applications.
• Integrates seamlessly with CI/CD tools, facilitating continuous testing and DevOps practices.
• Comes with extensive support for SAP and other enterprise applications.
• Has strong reporting capabilities for comprehensive test management and analytics.
• Model-based automation provides reusable test assets with minimal scripting.
• Allows testing of applications in isolation by simulating the behavior of dependent systems.

11. Keysight Eggplant Test

Referred to as an advanced, AI-driven test automation tool, Eggplant is built by Keysight for comprehensive and efficient software testing. It focuses on user-centric testing by simulating real user interactions and provides end-to-end testing capabilities across various platforms, including web, mobile, and desktop applications.

By using image recognition and machine learning, this tool can execute tests based on visual elements. Further, it approaches functional, performance, and usability testing from the user’s perspective, which makes the complete quality process highly reliable and closer to real-world scenarios.

Features

• Utilizes AI-driven capabilities and machine learning to mimic user interactions when executing test cases.
• Employs image recognition technology to interact with the application’s user interface.
• Supports cross-browser testing on a combination of OS and devices.
• Offers a scriptless test creation environment, making it an ideal choice for non-technical and time-bound projects.
• Seamlessly integrates with CI/CD pipelines.

Apart from the AI-powered testing tools, there are a few other AI-based test management tools or software quality tools that help streamline the QA process, which we will discuss here,

12. Digital.ai

Features

• Digital.ai brings artificial intelligence into analytics and reporting, giving meaningful insights to testers and business owners helping them make better business decisions.

• The tool provides assessments of agile solutions to bring transparency into the infrastructure from one end to another.

• Digital.ai provides easy deployment services with templates that testers can use and automate the deployment process easily.

• Digital.ai brings DevSecOps into the picture where security is at the core of the process. Through this, the testers can monitor their application’s security without worrying about issues such as reverse engineering and responding to threats.

While most of the tools have been focusing on developing test scripts and bringing the codeless environment into the picture, Digital.ai targets processes that start after the execution is completed. This makes Digital.ai a unique tool to possess and increase our AI coverage for cutting down even more time and costs.

13. Aqua ALM

Aqua ALM leverages its natural language processing capabilities to perform tests. It is one of the AI driven test automation tools with multi-lingual testing capabilities. Additionally, this web-based platform offers high flexibility, full visibility, and easy-to-use tools. With this platform, developers can speed up their test time and do more tests. Furthermore, it is designed as a test management system for busy companies. Specifically, the tool is a perfect choice for large technology companies.

Features

• It allows centralized test management by multiple departments
• Generates reports for test execution
• Has a feature for detecting and correcting defects
• Automatically generates tests
• Contains budgeting and forecasting tools
• Feature for permissions and access controls

14. Symflower

Gaining control over large language models directly instead of providing cooked generic software brings Symflower as a unique tool into the market. The LLMs are trained using high-quality data and can be tuned according to the requirements of the business. The tool developers claim a test execution time reduction of 29% with the adoption of Symflower.

Features

• Symflower provides a complete setup for writing and maintaining test cases written in Java, Sprint, or Sprint Boot. This includes providing a template and complete test suite generation.

• Once integrated into the IDE, Symflower can diagnose the test cases and detect potentially unwanted pieces of code (or missing exceptions) to prevent test failures in the future.

• Symflower comes as a plugin for popular IDEs such as IntelliJ and VSCode.

• Symflower comes with a code repair and linting facility through which the code can be checked and fixed on the go during the run.

15. Sealights

Sealights is an AI-driven quality management tool that leverages ML and advanced analytics to optimize software testing. It monitors the changes in the code and test execution process to provide end-to-end visibility of Quality Risks across the delivery pipeline. That means, testers can easily manage and supervise the tests while the tool supports continuous testing through its AI capabilities.

Overall, Sealights boasts of providing the visibility, traceability, and metrics that is needed to deliver a quality software at the speed of DevOps.

Features

• Automatically identifies the tests that need to be executed based on recent code changes.
• Prioritizes testing efforts on high-risk areas of the code to ensure critical functionalities undergo thorough testing.
• Provides detailed insights and metrics on test coverage, quality trends, and potential risks.
• Supports integration with CI/CD pipelines.
• Utilizes ML to predict potential defects and vulnerabilities in the code.

AI Testing Tools – Conclusion

Automated software testing allows the testing of software without human intervention. Automation helps minimize errors, improve accuracy, and save time. The tools should be chosen based on project demands, budgets, and features.