By Jochen D.
Last reviewed: 31 August 2026.
This list is maintained by the TestingBot team. It is a survey of tools that describe themselves as AI-driven testing tools, with a short note on what each one automates. It is not a benchmark, and the entries are not ranked against each other. TestingBot appears in it because we build one of them, which is worth knowing when you read our description of it.
As AI-powered testing continues to evolve, more tools are emerging that enhance test automation efficiency for web and mobile applications. These tools leverage artificial intelligence to improve test creation, maintenance and execution, reducing flakiness and increasing test reliability.
Below is a curated list of the top AI-driven testing frameworks and tools for browser and mobile application testing.
1. TestingBot
TestingBot allows you to write tests in natural language and have AI run the test on remote browsers.
Simply describe the test scenario in plain English and our AI test agent will execute it on remote browsers.
No coding required, just provide instructions and the AI will perform the test as a human would.
Unlike traditional test scripts that break when an element changes, the AI adapts dynamically, ensuring seamless execution even when your UI evolves.
2. Browser-Use
Browser-Use is an AI-powered end-to-end testing framework that automates browser interactions.
You can use this tool in combination with AI providers such as OpenAI, Gemini and DeepSeek to automate tasks in a browser.
Simply provide one or more prompts and the AI agent will use a (remote) browser to perform the tasks you've instructed it to do.
Browser-Use is a great tool for automating repetitive tasks, such as filling in forms, clicking on buttons, navigating to specific URLs and more.
You can use the remote TestingBot browsers together with Browser Use, see the browser-use documentation for more information.
3. Skyvern
Skyvern automates browser-based tasks with AI. Replace manual tasks with an AI agent that performs the tasks in a (remote) browser.
You can use this tool in combination with AI providers such as OpenAI, Gemini and DeepSeek to automate tasks in a browser.
This tool can generate test cases automatically from prompts you've previously instructed.
It can automate outbound form submissions, fetch invoices from various vendors, automate job applications and more, all with AI.
4. testRigor
testRigor uses free-flowing plain English to build test automation.
This tool understands and executes high-level instructions like "purchase a Kindle."
It is capable of translating human-readable steps into precise automation commands.
Because there's no dependency on element locators, such as XPath, it is more resilient to changes in the UI.
5. Healenium
Healenium improves the stability of Selenium-based test cases by handling changes in element locators.
Its self-healing functionality will replace broken locators with another locator that does work.
It promises to improve overall stability of tests, making the tests less flakey.
6. appvance
Appvance is an AI-driven test automation platform designed for high-scale enterprise applications.
- Uses AI to generate test scripts based on user behavior analysis, improving test coverage.
- Supports functional, performance, and security testing within a unified platform.
- Automates UI, API, and database testing with self-healing capabilities.
- Integrates seamlessly with CI/CD pipelines for continuous testing.
- Leverages machine learning to predict and prevent potential software failures.
7. Applitools
Applitools is built around Visual AI. Rather than asserting on selectors, it compares how a page actually renders against an approved baseline and reports the differences a person would notice, which is what keeps it useful when the markup changes but the page still looks right.
Alongside the visual comparison it offers GenAI and no-code test authoring, and it runs against tests written in the usual frameworks rather than replacing them.
Applitools describes itself as "AI-Augmented Testing" and leads on Visual AI for application validation (checked 31 August 2026).
8. Aqua ALM
Aqua ALM (Application Lifecycle Management) is an AI-driven test management and automation tool designed for enterprises.
- Provides a centralized platform for managing test cases, test plans, and test executions.
- Uses AI to suggest test optimizations, predict failures, and enhance test coverage.
- Seamlessly integrates with CI/CD pipelines, enabling automated testing within DevOps workflows.
- Supports test automation across web, desktop, and mobile applications.
- Offers detailed reporting and analytics to track test progress and quality trends.
9. iHarmony
iHarmony is an AI-powered test automation platform designed for seamless integration into DevOps workflows.
- Uses AI-driven test generation and maintenance to reduce manual effort.
- Supports cross-browser and cross-platform testing with real-time reporting.
- Integrates with popular CI/CD tools, allowing automated test execution in pipelines.
- Leverages machine learning to predict test failures and optimize test coverage.
10. Fireflink
Fireflink is an AI-driven test automation platform that focuses on low-code/no-code test creation, making it accessible to both technical and non-technical users.
- Uses natural language processing (NLP) to convert plain English test cases into executable automation scripts.
- Supports web, mobile and API testing with built-in integrations for CI/CD pipelines.
- Provides AI-powered self-healing to reduce test maintenance and improve test resilience.
- Includes analytics and real-time reporting to identify bottlenecks and optimize testing workflows.
11. Momentic
Momentic is an AI-driven test automation tool designed for modern web and mobile applications.
- Uses AI-powered self-healing technology to minimize test maintenance and reduce flaky tests.
- Automatically generates test cases based on application usage patterns.
- Provides real-time insights and predictive analytics to detect potential failures before deployment.
- Seamlessly integrates with CI/CD pipelines for continuous testing.
- Supports cross-browser and cross-platform testing to ensure application compatibility.
12. Copado
Copado is a cloud-based AI-driven DevOps and test automation platform designed specifically for Salesforce and enterprise applications.
- Provides low-code and no-code test automation for Salesforce, allowing testers to create robust test cases without extensive programming knowledge.
- Leverages AI-powered test generation and self-healing capabilities to adapt to Salesforce UI and backend changes dynamically.
- Integrates seamlessly with CI/CD pipelines to enable continuous testing and deployment.
- Includes powerful test analytics and reporting tools to help teams monitor test coverage and identify areas for improvement.
- Supports end-to-end testing across multiple platforms, including Salesforce, SAP and Workday.
13. Squish
Squish is a powerful cross-platform GUI test automation tool developed by froglogic. It is designed for automating applications based on various UI technologies, including desktop, web, mobile and embedded systems.
- Supports automated testing for Qt, Java Swing, Web, Android, iOS and more.
- Uses an object-based approach to identify and interact with UI elements, making tests more stable and maintainable.
- Provides scriptless test creation with a record-and-playback feature, as well as scripting support in Python, JavaScript, Perl and Ruby.
- Integrates seamlessly with CI/CD pipelines, allowing for automated regression testing.
- Includes built-in support for behavior-driven development (BDD) with Gherkin syntax.
- Ensures reliable testing with optical character recognition (OCR) and image-based validation.
14. Telerik Test Studio
Telerik Test Studio is a comprehensive test automation solution designed for web, desktop and responsive web applications.
- Provides AI-powered test automation for functional, load and performance testing.
- Supports scriptless test creation with a user-friendly record and playback feature.
- Offers cross-browser and cross-device testing to ensure compatibility.
- Uses self-healing technology to adapt to UI changes and reduce test maintenance efforts.
- Seamlessly integrates with CI/CD pipelines and popular DevOps tools.
- Includes advanced debugging and reporting features to optimize test execution.
15. OpenText UFT One
OpenText UFT One (formerly Micro Focus UFT) is a robust AI-driven functional testing tool designed for automating web, mobile, API and desktop applications.
- Leverages AI-based object recognition to improve test creation and maintenance.
- Supports cross-platform testing for desktop, web and mobile applications.
- Integrates with CI/CD pipelines and DevOps workflows for continuous testing.
- Provides built-in support for scriptless test automation with natural language processing.
- Uses self-healing capabilities to adapt to UI changes and reduce test flakiness.
Frequently asked questions
What are AI testing tools?
AI testing tools use machine learning or large language models to take on work that used to be hand-written: generating test cases, locating elements when the markup changes, spotting visual differences, or driving a browser from an instruction written in plain English. Most are not whole frameworks. They sit on top of, or alongside, something like Selenium, Playwright or Appium.
Do AI testing tools replace Selenium or Playwright?
Generally no. The established frameworks still do the driving; the AI layer decides what to click, repairs a selector that moved, or writes the first draft of a test. Tools that replace the framework entirely exist, but adopting one means giving up the ecosystem around it, so most teams add AI to a suite they already have rather than starting again.
Are AI testing tools reliable enough to run in CI?
It depends on which part you let the AI own. Self-healing locators and visual comparison are widely used in pipelines because a wrong answer is visible and cheap to correct. Letting a model decide pass or fail on its own is a bigger step: the same input can produce a different result on a later run, so teams that do it usually pin the model version and keep a deterministic check alongside it.
What should you look for when choosing one?
Whether it runs where your tests already run, what happens when the AI is wrong, and how much it costs when the suite grows. Ask whether failures are explainable, whether you can pin behaviour across runs, and whether the tool locks your tests into a format only it can read.