Top 8 AI Test Automation Tools in 2024

Have you ever wondered how is AI transforming test automation? Over the past few years, test automation has progressed substantially, greatly reducing the errors that were caused by manual processes. In fact, according to Fortune Business Insights, the U.S. AI market, valued at USD 515.31 billion in 2023, is expected to surge to around USD 2740.46 billion by 2032. This clearly shows how AI has become a well-established technology across various industries, particularly in software development and testing.

With that said, there are numerous companies that have started adopting AI in test automation systems. This is where AI automation tools come into play. These tools are greatly helpful for QA professionals, developers, as well as startup owners that help them enhance their workflows significantly. 

While there are numerous AI test automation tools available in the market, choosing the right one is very important for successful outcomes. Thus, we have come up with a list of ‘top 8 AI test automation tools in 2024’, that will help you navigate the world of AI and automation testing and simplify the process of choosing the one that best suits your company’s needs. We will walk you through the benefits and features of each one of them. 

But before we dive in, let’s start with the basics of AI automation testing.

What Is AI Automation Testing and How Does It Transform Modern Test Automation?

AI automation testing refers to the integration of artificial intelligence and machine learning into existing software testing tools to enhance results and address common challenges found in traditional software testing. Research from Gartner emphasizes AI's increasing influence in IT and software testing. Although AI has speeded up how quickly products are developed, it is still evolving and needs more development to fully meet the needs of automated testing. To understand the impact of AI on automation testing, let's look at the key AI subsets that are driving the optimization of test automation processes.

The Role of AI in Automation Testing

While Artificial Intelligence (AI) may seem like a recent development, its history dates back over a century. In the early 1900s, inventor Leonardo Torres Quevedo created "El Ajedrecista," an early chess-playing automaton. Fast forward to today, AI has become a vital part of modern technology, revolutionizing industries like sales, email marketing, business operations, and conversational AI. AI’s impact, however, extends far beyond these applications. It has become a cornerstone of the software development process, especially in automation testing.

AI's Influence Across the Software Development Lifecycle

AI’s role begins early in the development process, aiding in planning and design by analyzing large datasets to discover trends, understand user behavior, and spot potential risks. When developers write code, AI assists with tasks like intelligent code suggestions, bug detection, and even automated code generation. However, one of the most profound impacts AI has had on the development process is in the realm of testing.

“In a 2023 Currents report, respondents from diverse industries, including fintech, blockchain, entertainment, and tech infrastructure, revealed that 47% utilize AI and machine learning (ML) in software coding. This underscores the widespread influence of AI on the software development lifecycle, from the planning stages to the final testing phase.”

AI in Automation Testing

Automation testing, an important part of software development, has been transformed by AI. AI-based testing tools improve quality assurance (QA) by automating repetitive tasks, running multiple tests at the same time, and analyzing results more effectively. These tools, using machine learning and generative AI, work to increase the accuracy, speed, and coverage of testing, greatly enhancing the process. Here are some key benefits of AI-powered testing tools:

Key Benefits of AI Testing Tools

1.   Increased Efficiency in Test Automation

AI testing tools can automatically generate test cases based on user interactions and behaviors. For example, in cloud-based CRM systems, AI analyzes user data to create comprehensive test scenarios, ensuring a higher level of test coverage with minimal manual intervention. This increases the efficiency of QA teams and accelerates the development timeline.

2.             Reduced Maintenance with Self-Healing Capabilities

One of the most significant advantages of AI-powered testing tools is their self-healing ability. As software applications evolve, particularly in environments like e-commerce platforms where updates are frequent, AI-driven tools can adapt to UI changes, updating test scripts automatically. This drastically reduces the manual effort required to maintain test scripts and ensures consistent functionality even as the application evolves.

3.             Proactive Issue Detection through Predictive Analysis

AI tools excel in predictive analysis, which enables proactive identification of potential issues before they affect users. In applications like cloud project management tools, AI can analyze historical data and current test results to forecast high-risk areas. By directing QA efforts to these vulnerable sections, AI enhances the stability and performance of the software, leading to more reliable products for end-users.

4.              Enhanced Visual Testing and Analytics

With the rise of multi-device usage, it's important to make sure the user interface (UI) works well on all of them. AI-based visual testing tools check how UI elements look and work on different screen sizes and devices, like desktops and mobile browsers. These tools provide clear information about any UI problems, helping to fix them quickly and ensure a smooth experience for users.

5.             Seamless Integration in CI/CD Pipelines

AI-powered testing solutions integrate smoothly into Continuous Integration and Continuous Deployment (CI/CD) pipelines, enabling continuous testing. In large systems like enterprise resource planning (ERP) software, automated tests can be triggered with every code change, offering immediate feedback on the results. This ensures that issues are caught early in the development process, leading to faster release cycles and more robust software.

Now that we have got a basic understanding of AI in automation testing and its benefits, let’s move on to the list of top 8 AI automation testing tools in 2024.

Top 8 AI Automation Tools in 2024

AI-driven testing tools are designed to enhance automation and boost efficiency across a wide range of testing scenarios. These tools excel in various areas of software testing, such as functional, regression, performance, and usability testing, making them suitable for agile development teams and large enterprise environments alike. 

Let’s take a closer look at each of the 8 AI tools:

1.   ACCELQ

ACCELQ is a cloud-based continuous testing platform that simplifies API and web automation without requiring any code. It accelerates the testing process by automating key lifecycle elements such as test design, planning, generation, and execution.

Key features of ACCELQ include:

• ACCELQ is a cloud-based codeless AI automation for Web UI, API, Desktop, and Mobile,
• Natural language programming, intelligent element exploration, and self-healing capabilities,
• Smooth integration with popular DevOps tools to provide a unified QA lifecycle view, and
• Offers predictive and path analysis for effective test scenario development.

ACCELQ, powered by AI, stands out as the only cloud platform delivering codeless automation for a wide range of enterprise applications, including Web, Mobile, API, and Desktop. By utilizing AI, ACCELQ builds sustainable automation for reliable test execution.

Additional Features:

• ACCELQ’s analytic engine enhances test stability by adapting to unforeseen application changes, with a design-first approach ensuring robust element identification via AI,
• Its AI-driven Mobile Object handling reduces test flakiness,
• Automated and AI-based reconciliation adapts testing to changes in the application’s UI,
• Smart View Analyzer efficiently manages test assets across various application versions,
• Auto-generated test cases ensure comprehensive test coverage,
• Q-Runner executes tests swiftly and efficiently,
• Integrated test management merges different testing types and connects with Jira and Jenkins for continuous delivery, 
• Actionable reports provide a 360-degree functional perspective,
• The natural language editor allows test automation in plain English, making it easy for manual testers to scale with minimal effort.
• ACCELQ is both scalable and secure, meeting enterprise-level requirements.

2.             Applitools

Applitools is a leading tool in visual AI testing, designed to validate user interfaces with precision. It is especially useful for applications that demand consistent UI across different devices, such as e-commerce and financial platforms. Applitools improves the user experience by making sure that visual elements are accurate and uniform.

Key features of Applitools include:

• Applitools is powered by enterprise-grade AI, with proprietary algorithms refined over a decade of experience, used by rapidly growing companies,
• It enables the creation of tests through codeless tools, preferred frameworks, or AI-generated tests,
• Validates any interface, including apps, components, and PDFs, whether on screen or device, and
• Offers UI component testing to detect regressions and changes in Storybook components through automated visual and functional testing.

Applitools is an AI-driven platform for visual testing and monitoring, easily integrated with modern test frameworks.

Additional Features:

• Allows teams to create automated tests without coding, accommodating all skill levels,
• Supports efficient execution of tests to validate both functionality and performance,
• Simplifies test maintenance to keep tests relevant as applications evolve,
• Provides detailed reports to track application health, identify issues, and gain insights,
• Ensures consistent visual quality by validating elements like text, images, layouts, and videos, 
• Enables cross-browser and cross-device testing for both functionality and visual consistency, and
• Detects and addresses visual regressions during development or updates.

3.             Mabl

Mabl is an AI-driven test automation platform that is designed to make automated testing accessible to all members of a development team. It is particularly well-suited for agile teams working on web applications. Using machine learning, Mabl adapts to changes in applications, ensuring comprehensive test coverage.

Key features of Mabl include:

• It enables browser UI tests for user journeys, including SVGs, 2FA, email, and PDFs, using low-code and JavaScript,
• Supports mobile UI testing for hybrid and native frameworks with low-code and Appium scripts, 
• Integrates API tests into web and mobile workflows through Mabl’s code editor or Postman collection imports,
• Simplifies web accessibility testing by reusing existing browser UI tests to identify and fix issues, and
• Enhances load testing for both browser and API by reusing tests with Service Level Agreements (SLAs) for web vitals and user flow performance.

Mabl is an intuitive test automation tool that offers low-code capabilities, eliminating the need for extensive scripting and enabling high-velocity testing for fast-paced teams.

Additional Features:

• Its low-code approach allows developers to focus more on quality.
• It uses intelligent automation with self-healing capabilities,
• Offers data-driven testing for real-world scenarios,
• Provides comprehensive end-to-end testing through API integrations,
• Empowers developers with insights through its data analytics, and 
• Features a user-friendly dashboard for easy navigation.

4.             Functionize

Functionize is an AI-driven testing platform that streamlines the entire QA process, from test creation to execution and maintenance, using generative AI. It is well-suited for web-based applications and integrates smoothly with continuous testing workflows. It uses machine learning to adapt to application changes, minimizing the need for manual updates.

Key features of Functionize include:

• Architect: A Chrome extension that utilizes machine learning to create and maintain tests by recording user interactions, automatically adjusting to site changes, reducing maintenance efforts.
• TestAGENTS: AI-powered tools that generate tests based on real user behavior, automatically debug issues with root-cause analysis, and develop test plans for case management systems.
• Functionize uses AI and computer vision for visual verification to ensure pixel-perfect user interfaces in automated tests,
• Handles minor browser differences by providing detailed visual comparisons and accessibility to all team members, and
• Utilizes natural language processing to enable test creation without complex coding.

Functionize is a versatile AI-based automation tool, perfect for testing complex applications in organizations of any size. It eliminates the need for repetitive test scripts and creates an intelligent platform that combines machine learning with human insights, encouraging collaboration across teams.

Additional Features:

• Self-healing capabilities.
• Tools for test planning and editing.
• Supports cross-browser testing.
• Automates end-to-end testing for web and mobile applications.
• Integrates with popular DevOps tools.
• Features an intuitive dashboard with robust reporting options.

5.             TestCraft

TestCraft is an AI-powered test automation tool designed to offer a low-code solution for creating and maintaining automated tests, especially for teams with limited coding expertise. It’s particularly useful for testing web applications, with AI capabilities that automatically update test scripts, minimizing the need for manual intervention.

Key features of TestCraft include:

• TestCraft automatically generates tests across major automation frameworks and programming languages, enhancing efficiency and test coverage,
• It uses AI to create thorough and diverse test scenarios, ensuring critical areas are not missed,
• Identifies accessibility issues and provides actionable recommendations for improving usability and compliance, 
• Converts AI-generated test ideas into automated tests, streamlining workflows and boosting productivity.

TestCraft, a browser extension powered by GPT-4, transforms software testing by simplifying test generation, automating test creation for tools like Cypress and Playwright, and addressing accessibility concerns.

Additional Features:

• It uses GPT-4 AI to generate comprehensive test ideas from webpage elements, ensuring optimal coverage,
• Quickly generates test scripts in JavaScript and TypeScript for Cypress and Playwright, saving time and effort,
• Identifies accessibility issues in web apps and offers actionable insights to improve inclusivity,
• Seamlessly converts AI-generated test ideas into automated test scripts, and
• Allows easy copying of generated tests and code snippets for direct integration into your development environment.

6.             Keysight Eggplant Test

Keysight Eggplant Test is an AI-powered automation tool that is designed for comprehensive functional, performance, and usability testing. It excels in handling complex applications that require end-to-end testing across multiple platforms and devices. Eggplant’s AI capabilities allow tests to adapt to evolving application features and changes.

Key features of Keysight Eggplant Test include:

• Seamless integration with popular CI/CD tools like Jenkins, Azure DevOps, and GitHub Actions, streamlining automated testing workflows from code changes to deployment.
• It supports testing across a wide range of environments, including different browsers, operating systems, and devices, ensuring consistent performance and user experience across platforms,
• Simplifies the setup of automated testing deployment tools, reducing the need for custom coding and complex configurations, which speeds up test preparation and deployment,
• Automates regression testing, improving efficiency and allowing teams to focus on more strategic testing tasks, and
• Uses AI algorithms to enhance testing accuracy and scalability, making it ideal for responsive user experiences and complex technical ecosystems.

Eggplant Test uses a model-based, AI-driven digital twin testing approach. It is trusted by global enterprises to improve coverage, user experience, and release speed, ensuring high-quality testing at scale. The platform simulates real user interactions within applications without requiring access to source code, which makes it suitable for secure development environments.

Additional Features:

• AI-driven test modeling ensures compatibility across all browsers, operating systems, and devices.
• Model-based testing improves app performance and reliability by predicting behavior under various conditions.
• Integration with CI/CD tools like Jenkins, Bamboo, and GitHub enhances test coverage and optimizes development pipelines.
• Provides real-time analytics for data-driven decision-making during the testing process.

7.             Tricentis Testim

Testim is a type of AI-driven test automation tool that is built to speed up the creation and maintenance of automated tests. By adopting the power of generative AI and machine learning, it efficiently generates, executes, and manages test cases, making it an excellent choice for web-based and mobile applications. Testim is especially beneficial in agile development settings where rapid test creation and updates are very important.

Key features of Testim include:

• Testim offers flexible testing environments, adapting to various needs by providing versatile setups for running tests,
• Conducts cross-browser web tests, ensuring compatibility and performance across different browsers using Selenium,
• Supports testing on both physical and virtual mobile devices to ensure mobile app quality,
• Seamlessly integrates with CI/CD pipelines, enabling automated testing on code check-ins,
• Provides code-free, end-to-end testing for businesses using Salesforce, and
• Supports both desktop and mobile browsers for comprehensive coverage.

In simple words, Tricentis Testim is an AI-powered tool designed for web and mobile app testing. It simplifies test writing, reduces maintenance, and accelerates product delivery. With its AI-based smart locators, Testim helps create robust, well-designed tests that require minimal upkeep, tackling even the most challenging testing scenarios efficiently.

Additional Features:

• The Monaco editor allows sharing code across multiple tests, improving efficiency.
• Testim’s AI uses smart locators to identify and update web elements automatically to prevent failures due to layout changes.
• Diagnoses failed tests with highlighted screenshots and network logs for easier debugging.
• TestOps manages test changes, organizes teams, and optimizes testing activities.

8.             Katalon Studio

Katalon Studio is a comprehensive quality management platform designed to streamline the work of QA, DevOps, and software teams of all sizes. It simplifies the entire development process by enabling efficient end-to-end test automation, helping teams build exceptional customer experiences faster and more effectively. The platform supports the creation, execution, and management of tests across web, API, mobile, and desktop applications, all without requiring any coding. Its flexible integration with team workflows enhances productivity and ensures seamless maintenance of test scripts.

Key features of Katalon Studio include:

• Katalon Studio supports test creation, execution, and reporting on a unified platform,
• Automatically generates test cases by capturing user interactions and modeling behaviors,
• Seamlessly integrates with JIRA for comprehensive manual test case management, and
• Uses AI for intelligent test execution, screenshot analysis, and categorizing test failures.

Katalon is a modern testing platform that helps teams deliver high-quality digital experiences. Its AI-powered tool, TrueTest, eliminates the need for test maintenance by performing instant regression tests, ensuring full coverage without gaps. TrueTest integrates effortlessly with the rest of the Katalon platform to provide efficient and accurate testing.

Additional Features:

• Provides a clear view of user actions with TrueTest.
• Executes instant regression tests for various flows and edge cases.
• Automatically updates and maintains tests as applications evolve.
• Ensures complete test coverage, reflecting real user interactions.

The Takeaway?

These AI test automation tools offer great benefits for software testing today. They use machine learning to handle changes in applications, cut down on manual work, and make testing easier. Each tool has its own features to suit different team sizes and testing needs, making it easier to release products faster with more accuracy and better test coverage.

However, when choosing an AI test automation tool, it's essential to consider several key factors. These include the specific testing needs, the skill level of your team, the complexity and scale of your application, and your available budget. 

Wrapping Up

We have just explored how AI has become an essential part of software development, especially in automation testing. Far from being just a buzzword, AI is now an integral part of streamlining the entire development process. It speeds up test generation, minimizes manual updates, and uses predictive analytics to enhance testing efficiency. As highlighted by the top 8 AI automation testing tools, integrating these solutions is essential for development teams in order to stay competitive and deliver reliable, high-quality software.

So, are you ready to upscale your testing strategy? Dive into the world of AI-powered testing tools and see how they can transform your development process. Explore your options today and take the next step toward optimizing your software quality!