Best AI Tools for QA Automation & Test Case Generation in 2025: A Complete Guide

AI in 2025: What QA Teams Need to Know

Modern software delivery infrastructure is increasingly reliant on AI-powered QA technologies. Whether your team relies primarily on manual testing, automation-dependent, or somewhere in between, these technologies can shorten release cycles, increase coverage, and speed up test creation by up to 70%.

In this article, we analyze manual-only and hybrid AI QA solutions to guide users in selecting the most appropriate AI tool based on their specific technical expertise, project requirements, and budget.

As part of our evaluation process, we tested these tools in real-world developer and QA workflows over several months. Our goal was to identify which tools delivered the fastest, most reliable results and offered the best alignment with project needs, based on the following criteria.

To provide a comprehensive analysis, we’ve carefully examined the most impactful AI tools designed for coding assistance, QA automation, and test case generation. The evaluated tools are divided into AI Manual Test Case Tools and Automation Tools.

JIRA Extension – AI Test Case Generator

By creating test cases straight from user stories in JIRA, this tool facilitates bulk generation and drastically cuts down on the amount of manual labor required to create test cases. It creates context-aware test cases, labels test types, and comprehends user stories using LLMs.However, the quality of test cases depends on the quality of JIRA user stories.

Testpad is a good choice for exploratory manual testers as it offers checklist/manual test creation with AI support. AI assists in planning and recommending manual test steps. Even so, this tool doesn’t integrate well with other development tools, making workflow coordination harder.

This tool provides manual test case management with AI suggestions, without script automation. AI suggests test cases based on project needs, aiding in the creation and management of manual tests. However, it only provides basic reporting and no deeper insights for teams.

Testmo focuses on manual test case authoring with AI-assisted hints and does not provide script automation. It’s best suited for manual QA and test managers, providing AI hints to improve test case writing and coverage.

TestingTools.ai helps create manual test cases from user stories or descriptions using GPT-powered natural language understanding. It’s recommended for quick, free manual test case generation.

With AI support, this tool creates manual test cases from requirements or URLs, but script automation is not used. It supports both web and mobile platforms and integrates with BrowserStack Test Management.

Pro Tip: For teams primarily focused on generating manual test cases quickly and efficiently, AI Test Case Generator and the JIRA Extension – AI Test Case Generator stand out as top recommendations. 

AI Automation Tools

These tools are ideal for QA teams that switch from manual to automation or hybrid teams seeking a balance between no-code accessibility and automation flexibility. These tools are good at both generating test cases and assisting with automation scripts.

GitHub Copilot

We were impressed by the responsiveness and dependability of GitHub Copilot, an AI-powered coding assistant, in producing usable code, including test scripts. It integrates directly into well-known IDEs such as Visual Studio, JetBrains, and VS Code and makes use of GPT-4.5 and complex context protocols. It is useful for rapid prototyping, UI development, and boilerplate creation. At the same time, it requires a consistent internet connection, may struggle with extensive codebases, and involves subscription costs with the need for manual validation.

ChatGPT

ChatGPT, notable for its large language model (LLM) capabilities, proved excellent for test case creation using custom prompts, supporting functional, boundary, exploratory, and regression test generation. It’s highly adaptable, capable of writing end-to-end test scripts for various frameworks like Cypress and Selenium, building initial test frameworks, and optimizing existing test code. On the other hand, the output quality depends on precise prompts, and it lacks integrated dashboards or CI/CD capabilities without additional setup.

Mabl

Mabl is a cloud-based, low-code test automation tool primarily for web applications, making it accessible to both technical and non-technical users through a visual recorder. Built on frameworks like Playwright, Appium, and Postman, Mabl significantly reduces the overhead of maintaining individual test automation frameworks. That said, it may not be appropriate for certain projects due to its higher cost, web-only focus, and difficulties with custom logic.

TestSigma

TestSigma stands out for its ability to create test cases using simple plain English or through recording, requiring no coding for most scenarios. It also supports custom Java functions for advanced use cases and data-driven testing. However, the steep learning curve, high cost, and edge case limitations are the main causes for concern.

TestRigor

TestRigor distinguishes itself by having AI automatically create test scripts. It offers three main generation methods: crawling a URL, recording user actions, or analyzing real user data. Importantly, TestRigor’s “scripts” are not traditional programming languages but sequences of commands written in plain, human-readable English. However, debugging complexities and vendor lock-in, particularly with edge cases, may require advanced features or enterprise support.

Testim (with Copilot)

With its automated UI test creation, Testim provides a hybrid approach that supports low-code JavaScript scripting as well as record-and-playback automation. It makes it very simple for testers without any coding experience by using modular test flows, reusable components, and JavaScript for custom logic. Its limited mobile and API support may limit wider use, and the costs are high for small teams.

Functionize

Functionize converts JIRA test steps into cloud-based execution, leveraging AI for adaptive learning and self-healing tests. It’s suitable for large enterprises with complex QA environments and scales AI-based automation.

ACCELQ

ACCELQ combines manual test design and automated execution in a visual, model-driven workflow, utilizing NLP input for codeless automation and self-healing features.

Rainforest QA

Rainforest QA provides no-code testing where English steps are converted into tests and can be run via cloud agents or the crowd. It’s simple and ideal for non-technical teams seeking fast functional feedback. But the pricing model may not suit all budgets.

Summary – AI Automation Tools

Pro Tip: If your team is hybrid, GitHub Copilot is a safe bet for automation inside IDEs, while ChatGPT can help with quick test case ideas. For non-technical users, Mabl provides low-code visual web automation with AI-driven maintenance. TestSigma uses plain English/recording for auto-generated, self-healing scripts for smooth automation transitions across platforms.

AI QA Tools: Manual vs Automation

This image represents the relationship between automation and advanced AI capabilities. The x-axis shows the automation level, ranging from manual (0.2) to fully automated (1.0), while the y-axis indicates AI depth, from low (0.2) to high (1.0). Tools like ChatGPT and GitHub Copilot score high in both automation and AI depth, while Testpad tends toward manual processes with less AI integration.

Which Is Best for You?

Choosing the right AI tool largely depends on your team’s specific needs, existing infrastructure, and technical expertise.

• If you are a code-first QA team or an SDET looking for the quickest, most dependable solution with enterprise-grade features and wide IDE support for rapid script generation, choose GitHub Copilot.
• Go with ChatGPT if you need flexible AI assistance for both manual and automated testing, possess strong prompt-engineering skills, and prefer a cost-effective, adaptable tool. 
• For generating manual test cases, select AI Test Case Generator (TestingTools.ai) to quickly generate manual test cases, and you can opt for JIRA Extension- AI Test Case Generator if you want to create test cases from JIRA user stories.

Concluding Remarks

The need for AI-driven coding and QA tools is rapidly evolving, making it an exciting time for software quality professionals. Right now, GitHub Copilot is still the most reliable coding assistant, but tools like TestSigma and Mabl are catching up fast, especially for teams that want low-code options. While a specialized tool like AI Test Case Generator is best suited for creating manual test cases, ChatGPT is highly flexible for both automated and manual testing.