Top 9 Tools for AI-Based Test Automation in 2023

The market of tools for AI-based test automation hits a global size of USD 20 Billion in 2022. While now, according to the latest updates from, the market for AI testing tools for automation is projected to achieve 15% CAGR projection by 2033. That’s a huge number, right? But why is there a need for AI-based test automation? Or more specifically why your product or software needs AI-powered test automation tools? We will dig right in here. So, join us till the end and find yourself.

Before AI-Based Test Automation, Product Testing Was All About High Costs, More Time, & Less Accuracy!

Quality control was longer to implement since it relied on a hybrid of manual and automated methods before AI was used for automated testing. To ensure reliability in the early days of software development, a team would repeatedly test the software, website, or any other program using a variety of manual methods. Time is money, and this took a long time. When combined with automation technology and open-source platforms, traditional quality assurance techniques were revolutionized by automation machines. The procedure was still imperfect because it was time-consuming and partly dependent on human intervention. Artificial intelligence (AI) arrived and revolutionized automatic testing. Now, thanks to advancements in both software and hardware, testing is entirely automated, eliminating the need for any human involvement whatsoever. Artificial intelligence (AI) can be used in testing to improve the user experience by delivering results more quickly and with fewer mistakes. Customers can have a better time using your product if you anticipate issues and address them before they actually have an impact.

Using Tools for AI-Based Test Automation Has the Following Advantages:

  1. Higher Accuracy
Quality assurance (QA) can be greatly streamlined with the use of AI-powered testing. Now that we don’t have to spend as much money on human testers, we can use that money toward more productive endeavors, like creating a blog about web development. In contrast to AI, manual testing might introduce inconsistencies and inaccuracies. Better defect identification and early issue detection are two benefits of AI-powered testing.
  1. Reduced Manual Effort
Artificial intelligence (AI)-based automated testing solutions reduce the need for human intervention by completing tests more quickly and precisely than humans could on their own. As a result, testers are freed up to focus on other crucial activities because these tools can run numerous tests without tiring.
  1. Increased Test Coverage
Complex software systems often consist of many interacting parts. Because of this, finding all potential test cases might be challenging for testers. In order to increase the scope of tests and refine the standard of the testing process, AI algorithms can find scenarios for testing that the human eye may have overlooked.
  1. Cost Savings
By automating software testing with AI, we can drastically cut down on testing expenses. Automated testing tools reduce the need for human labor, therefore saving money. Increased accuracy and shorter testing cycles reduce product problems and the costs associated with fixing them or issuing recalls.

Best 9 Tools for AI-Based Test Automation in 2023

Now that we are aware of the before and afters of AI-based test automation tools let’s look into the top tools you can use for your product/software. With the concept of A-based test automation rising, every new day comes with new AI testing tools. And it is becoming increasingly difficult to find what’s best for you. But don’t worry, we have your back. Here are the top 9 AI testing tools you can never go wrong with.

1. Selenium – Best for Multiple Automation Needs

When it comes to comprehensive test automation, Selenium is hard to beat as an automation framework. It’s compatible with a number of languages and offers a wide selection of automation-related tools and libraries.
  • With Selenium WebDriver, you can build powerful regression automation suites in your browser.
  • Excellent for Script Distribution and Scalability in a Wide Variety of Settings.
  • It helps with exploratory testing that is supported by automation and provides short scripts for reproducing bugs.

2. ACCELQ – Best AI-Based Test Automation Tool for Codeless Test Automation

Web UI, API, Mobile, and Desktop are all easily automated with ACCELQ , a cloud-based Codeless Test Automation platform powered by artificial intelligence. ACCELQ has helped multiple companies dramatically speed up their automation efforts. ACCELQ has been shown to enable synchronization with Continuous Delivery, accelerate automation programming by a factor of three, and reduce maintenance by a factor of seventy, saving businesses in excess of fifty percent in the process.
  • Develop automated tests quickly with little time spent on maintenance.
  • Automate testing in an integrated manner across different environments.
  • To further support DevOps and Agile practices, it is recommended to incorporate automation into sprints.
  • Automatic, self-repairing testing infrastructure that can quickly adjust to new versions of software.

3. Applitools – Best for UI Testing

Applitools works with continuous integration tools, notifies team members via instant messaging, and is compatible with all popular development frameworks. One of Applitools’ strongest points is the variety of visual testing alternatives it provides. It has a cellular grid to evaluate native mobile apps and a cross-platform (and cross-device) grid for testing web apps.
  • By comparing two screenshots of the same app, AI can detect suspicious changes in a short amount of time.
  • It’s also wonderful that all accessibility standards for the visually impaired are automatically met.
  • It also works with other bug-tracking software and even its rivals.

4. Testim – Best Tool for AI-Based Test Automation for Custom & Web Apps

Testim claim to provide self-repair checks, clear visibility for speedy troubleshooting, and room to develop further. However, Testim’s focus is not on generating automated tests from scratch, but rather on assisting experienced engineers in writing them. Functional, API, and UI testing are the main focuses.
  • Rapid, low-code creation with unparalleled adaptability via user-defined code.
  • Management of both physical devices and mobile apps is streamlined.
  • Compatible with all of your preferred Continuous Integration technologies, issue trackers, test management platforms, and more.

5. Testigma – Best Cloud-Based AI Automation Testing Tool

When it comes to testing AI, Testsigmaranks highly. Automation engineers and QA analysts can use it to build automated tests for APIs, mobile apps, and desktop software. Additionally, it features robust self-healing capabilities that fix problems on its own.
  • Natural language processing enables code-free test development, making test design as straightforward as writing simple English statements.
  • Being web-based, it eliminates the requirement for local setup.
  • Allows for the automation of web, mobile, desktop, and API tests.

6. Katalon – Best AI-Based Automation Testing Tool for Technical & Non-Technical Users

Katalon is an automated testing platform that provides a full suite of features for checking the functionality of online, mobile, and API software. Katalon’s user interface for test automation is both straightforward and easy to pick up, making it accessible to a wide range of users.
  • Strong Object Repository: Develop Reusable Components for Better Test Upkeep.
  • Katalon’s support for integration with other common CI/CD technologies means that you can easily add automated testing to your existing development process.
  • Built-in analytics and reporting features allow you to generate comprehensive test reports and monitor the outcomes of your test executions.

7. IBM Rational Functional Tester – Best in Supporting Multiple Languages

IBM’s commercial automation testing solution is called Rational Functional Tester. It’s compatible with several different programming languages and frameworks, including Siebel, Net, SAP, Java, PowerBuilder, Flex, and Dojo.
  • It can be programmed in both Java and Visual Basic. There is a strong connection between IBM Rational Quality Manager and Net Rational Functional Tester (RFT).
  • All three types of testing—functional, regression, and data-driven—are supported by the instrument.
  • In RFT’s innovative Storyboard Testing, the test script is captured as a series of screenshots illustrating the actions taken on the AUT.

8. Aqua ALM – Best AI-Based Test Automation Tool for Large Companies

For testing purposes, Aqua ALM makes use of its NLP capabilities. This web-based platform also provides a great deal of leeway, complete transparency, and an intuitive interface. Developers’ testing cycles will shorten, and they’ll be able to run more tests on this platform. In addition, it serves as a test management solution for enterprises with heavy workloads.
  • It paves the way for a unified system of test administration across many divisions.
  • Includes a function for locating and fixing errors.
  • Includes resources for planning and budgeting, as well as exams generated automatically.

9. Mabl – Best GUI Based AI Testing Tool for Test Automation

Mabl’s GUI is both robust and intuitive, making it a pleasure to use. An artificial intelligence testing tool, that eliminates the necessity for scripting when conducting tests. This solution is great for teams that are constantly on the go because it facilitates rapid testing at every stage of the program’s creation. Mabl also encourages constant two-way communication between clients and supervisors.
  • Low capacity to prioritize quality through testing of code.
  • Artificial intelligence and self-healing technology.
  • Capabilities based on actual data for testing purposes.
  • Integral API-based end-to-end testing.
  • Provides developers with actionable data insights


An automotive factory, for example, may use IA to speed up production or reduce the chance of human mistakes, whereas a pharmaceutical or life sciences company may employ intelligent automation to reduce costs and obtain resource efficiencies where repetitive procedures exist. 

AI can help testers uncover common code faults that can impede a software system’s smooth operation. Understanding what the client wants allows them to design test cases to ensure that the product does not break while attaining those objectives. 

A greater focus on AI-based automation testing: The usage of AI in testing has progressively increased in recent years, and this trend is expected to continue in 2023. Tools for AI-based test automation can help enhance testing process accuracy and efficiency, decreasing the time and effort necessary for manual testing. 

One significant way AI-assisted software testing has altered the quality assurance process is by accelerating the whole procedure. There is no need to perform computations yourself or undergo the process of manually evaluating the software multiple times with AI.

Automated software testing can assist enhance software quality by increasing the depth and scope of tests. Longer tests, which are frequently avoided during manual testing, can be done unattended. They can even run on numerous PCs with varying configurations. 

AI can supplement continuous testing by assisting in the automation of more procedures in the interaction between new features, development, and testing. According to Honda, AI may generate a range of artifacts for testing activities, including test scripts, test data identification, and test suite identification for execution. 

Our Ultimate Take Away… 

No doubt the demand for AI-based test automation is increasing day by day. But so do the tools for AI-based test automation which make it difficult to choose the right one for your software/product.  

We hope our discussion here on the top 9 tools for AI-based test automation has clarified things for you a little bit. All tools mentioned above are top-quality and expert in their own way. Panacealogics is the best overall AI solution-providing platform while ACCELQ is the best in codeless AI automation testing. Each tool has its own unique feature.  

Now it depends on you to choose whether you want a one-time solution or one which can handle all your AI automation needs! 



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