The 10 Best AI-Powered Test Automation Tools in 2026

Liviu Lupei

Founder & Solutions Architect, Endtest · October 1, 2026

I know, I know, you probably rolled your eyes when you saw the title.

But hear me out, there are hundreds or thousands of "best test automation tools" articles that are low-effort AI-generated pieces for SEO purposes.

And it frustrates me that no one ACTUALLY tries to do a fair and in-depth comparison of those tools.

But that changes today. I'm writing a detailed and transparent article about this topic, based on the intensive research I did in the last few days.

I've been working in web development for almost 15 years, and my main focus was always on test automation.

I feel like most software tools nowadays are like cars: there is no "the best one", but there is "the best one for your team, budget, situation, etc."

Most of the "reviews" we see today are superficial, just listing some features and making some shallow comparisons and drawing some obvious conclusions. We don't see any actual proof that the author tried those tools. And we don't see any insights beyond what we can find out from the marketing pages of those tools.

But it's not as easy as you may think to try out a tool, because some tools don't give away free trials, because they want to be in control of the first impression.

They want to show you how their tool works in a predictable situation in a demo call, before anyone in your team gets a chance to try it out.

And yes, I don't like dealing with sales reps.

Believe me, I pulled a few strings to get access to some of these tools, mostly by asking friends to sign up with their company emails and book demos.

Other tools have an even sneakier approach, mimicking a "developer-friendly" attitude, making you think it's just some cool open-source tool, getting you to put it in your stack and then casually trying to upsell it to your management, without you even knowing about it.

Even if such things leave a bad taste, I'm going to ignore them for the purpose of this review, because we'll be focusing only on the technical capabilities.

What tools are we going to review?

There are TOO MANY test automation tools, so I picked out 10 by looking at G2 and Capterra reviews, Reddit mentions and appearances in job listings.

What scenarios are we testing?

We'll try the exact same functional scenarios across all 10 tools. These are some difficult scenarios where testing tools might hit a wall:

1. Sign up using email verification.
2. Interact with elements inside an iframe.
3. Interact with elements that have dynamic or unreliable attributes.
4. Complete a flow spanning multiple browser tabs.
5. Assert that a page is displayed in a specific language.
6. Reuse values and groups of steps.
7. Extract a verification code from a real SMS message.
8. Download a PDF and extract information from it.
9. Send an API request and use its response in a browser step.

Testing 9 different scenarios across all 10 tools seems like a healthy way to review them.

Beyond those 9 scenarios, I'm also evaluating the tools on these aspects:

1. Creating Tests with AI
2. Autonomous Test Generation
3. Creating Tests Without AI
4. Execution Performance
5. Test Transparency & Readability
6. Cross-Browser Testing
7. Maintenance & Debugging
8. Documentation & Customer Support
9. Enterprise Readiness
10. Portability & Vendor Lock-In
11. Pricing & Value
12. Overall Usability

Methodology

Since I wanted to make this comparison as consistent as possible, I followed the same process for each tool.

For the functional flows, I used the exact same websites and the exact same approaches.

For AI-generated tests, I tried to use the same instructions in the prompts (whenever possible).

No tool received more patience than the others.

When something was failing, I just checked the docs to see if there was some obvious setting or recommended approach that I missed.

I didn't label a scenario as successful just because the vendor's documentation said it's supported. I actually tried it myself.

And just to clarify:

✅ Passed means the tool handled the scenario without unusual intervention.

⚠️ Passed with workaround means the scenario worked, but required custom code, extra config, a third party service or some workaround.

❌ Failed means I couldn't get the scenario to work in a reasonable way.

I also don't consider using an external service equivalent to a built-in functionality.

For example, if a tool can get an SMS message only by integrating with another SMS provider, that's not really the same as the platform providing an actual real phone number and receiving the SMS itself.

The same logic applies to email verification, PDF files and other things.

For execution speed, I calculated the average number of executed steps per second for the same tests.

Execution speed also depends on the website, browser, network, etc.

For subjective criteria such as usability, readability and maintenance, I used these ratings:

Excellent: Among the strongest tools tested in this area, with no major shortcomings.

Good: Strong overall, but with some noticeable limitations.

Average: Gets the job done, but has meaningful trade-offs.

Poor: Significant limitations or friction compared with the other tools.

If you're in a hurry, here's the summary of my findings:

Testing Capabilities

Ownership & Day-to-Day Use

Rating guide:

• Excellent: Among the strongest tools tested in this area, with no major shortcomings.
• Good: Strong overall, but with some noticeable limitations.
• Average: Gets the job done, but has meaningful trade-offs.
• Poor: Significant limitations or friction compared with the other tools.

Real-World Test Results

Legend:

• ✅ Passed: Completed successfully without unusual intervention.
• ⚠️ Passed with workaround: Completed, but required extra configuration, custom code, an external service, or another workaround.
• ❌ Failed: Could not successfully complete the scenario.

Great. Now that we got that out of the way, let me show you what those exact scenarios looked like.

1. Sign up using email verification.

I gave the instruction to create an account on some website and to verify the email.

While all the tools were able to enter the details and submit the form, very few were able to handle the entire scenario.

Endtest entered a random endtest-mail.io address, which it was able to access via the Endtest Mailbox.

The full signup flow with email validation in Endtest.

Validating the email using the Endtest Mailbox.

mabl and Testim also handled it well.

But the rest got stuck or gave a message that this isn't supported.

2. Interact with elements inside an iframe.

I tried it on this page: https://www.w3schools.com/tags/tryit.asp?filename=tryhtml_select

Just click on the Run button, then interact with the elements from the iframe on the right side. And then click on the Run button again. And ideally, you should see that the test switched to the iframe, and then switched out.

Endtest and mabl handled it perfectly, but the rest had some issues.

mabl correctly handling the iframe scenario.

Some didn't capture any events inside the iframe. And some captured the events, but registered them as being on the main DOM, instead of the iframe.

Testim didn't work for this scenario. I also tried using a Custom Step as a workaround, but that didn't work either.

The iframe scenario in Testim.

3. Interact with elements that have dynamic or unreliable attributes.

Recording steps is easy, but getting those steps to be reliable is not.

Bad locator: //*[@id="input-89437291"]

Better locator: //input[@name="email"]

Endtest, ACCELQ and Testim handled this beautifully.

An ACCELQ scenario from the locator and dynamic-element testing.

Those tools detected that certain attributes were dynamically generated, and didn't use them in the selectors generated for those steps.

As for the rest of the tools, they had no shame in using those obviously dynamic attribute values.

Hint: Dynamic attribute values usually have numbers or random characters; it's not that hard to detect them.

Worth mentioning here that mabl was able to pass this one after changing the settings to make it ignore those specific attributes.

4. Complete a flow spanning multiple browser tabs.

There are many situations where a test might need to switch across different tabs.

My typical approach involves:

• switch to a tab that was opened by clicking a button
• open a new empty tab and switch to it
• switch back and forth across multiple tabs (5-6)
• close the current tab

Most tools were able to handle this easily, since the browsers also make it easy.

Testim was an exception here. I couldn't get the multiple-tab flow to work, and I also tried using a Custom Step as a workaround, but that didn't work either.

The failed multiple-tab scenario in Testim.

5. Assert that a page is displayed in a specific language.

This is what I would call a "fuzzy" assertion, something that you wouldn't be able to verify so easily with tools from 5 years ago.

For example, let's say a website has a button to switch the language to French. We then want to go to a certain page and verify if the entire content is actually displayed in French.

This isn't something that can be handled by a classic "Element Contains Value" assertion.

And seeing "lang=fr" in the current URL doesn't actually prove that the content is displayed in French.

The only solution is for the tool to use an "AI Assertion" to verify the situation.

And since all the tools have AI Assertions, all of them did well.

Using an Endtest AI Assertion to check the language of the page.

An assertion in ACCELQ.

6. Reuse values and groups of steps.

I'd expect modern test automation tools to allow you to use the same best practices as scripting languages.

And that includes the ability to reuse values (variables) and groups of steps (components, test cases, etc.).

For example, if you have a login flow, you'd want to define the username and password and the steps in only one place, and then be able to reuse that login across other tests.

The obvious advantage is that if something changes in your login flow, you would only need to update it in one place.

From what I tested, all the tools seem to have this functionality, in one way or another.

Using variables in mabl.

Using Shared Steps in Testim.

7. Extract a verification code from a real SMS message.

The best example here is a login flow with 2FA enabled, where you get an SMS with the authentication code.

Ideally, this should be achieved natively in the tool, without using third-party integrations and complicated workarounds.

That means the tool would need to assign a real phone number to your team, because we want to see if the SMS was actually delivered, and not just extract the authentication code from a database or an endpoint.

Surprisingly, only Endtest and Functionize support this SMS flow.

SMS verification in Functionize.

All the other tools required you to call some external provider to achieve that.

8. Download a PDF and extract information from it.

This is trickier than it sounds, because any tool can open a PDF and take a screenshot.

But extracting actual information from the PDF isn't so easy, since most of these tools use WebDriver or Playwright under the hood, and those do not have the functionality to extract information from a PDF file.

And again, a user would expect to be able to do that directly, without involving other third party tools.

And ideally, we'd expect more than a visual validation for the contents.

This functionality should work for PDFs opened in a new tab or downloaded (even downloaded via API steps).

Autify doesn't support PDF testing at all. It only allows you to see the URL of the PDF, but you can't inspect, extract or validate the contents of the PDF itself.

9. Send an API request and use its response in a browser step.

In advanced E2E flows, you often have situations where you need to send an API request and then reuse the returned value in a UI step, or vice versa.

That's why it's important for UI steps and API steps to be in the same interface.

Most tools handled this well, since they have a "Send API request" type of action.

An API request in Katalon.

As for these evaluation criteria:

1. Creating Tests with AI

This refers to providing granular or high-level instructions to create a test.

That means the tool has to understand each instruction, inspect the elements, find the best locator, verify that the step works and save the step.

It doesn't mean just blindly converting user instructions into a test.

Both speed and reliability matter here, but reliability is more important. Because I'm OK with the test creation process taking a bit longer, as long as I can actually rely on that test later.

2. Autonomous Test Generation

This involves giving a URL and some directions to the tool and expecting the tool to explore the web application and come up with scenarios and completed tests.

We don't want the tool to just look at the website and print some scenarios. We expect it to actually navigate all the flows and generate executable tests.

Ideally, this shouldn't be divided into separate features. I don't want a feature that "comes up with test cases" by looking at specs, and then another feature that attempts to automate those test cases.

And I don't want something that comes up with questions for me related to each scenario.

I want something like an autonomous QA colleague, where I provide some direction and then they go and do their work and keep me updated.

The Endtest Bot is the best example here, because it's like hiring a test automation expert that works independently.

3. Creating Tests Without AI

Some users don't want AI in their workflows. This should not shock you.

They have their reasons, either because they're working in sensitive domains (healthcare, defense, etc) or because they want to be in full control of the process.

A modern test automation tool should not force a user on the AI path.

Endtest allows users to create tests in 3 different ways without using AI:

• Endtest Web Recorder
• Manual test creation
• Import tests from files

4. Execution Performance

We're talking about the actual test execution speed here. And we want to have realistic expectations, because that speed also depends on the web application and it also depends on the browser.

For this comparison, I'm referring to cloud executions, not tests executed locally on your own machine.

Making calls to some AI endpoint during the test execution for each step is not a good approach, because that adds a delay.

So, you shouldn't have steps stored as "Click on Login button", because that means it will call the AI each time it executes that step, in order to figure out which one is the Login button.

The only time when it's acceptable for the tool to call an AI endpoint during the test execution is for situations that can't be resolved without AI, such as AI Assertions or self-healing.

For my benchmark, I think it's fine if a test automation tool has a speed of around 1 step/second. If the speed is slower than that, it's possible that the tool is doing things it doesn't need to.

From what I could figure out, some tools have lower speeds either because their cloud infrastructure is more complicated than it needs to be or because they're collecting too many artifacts.

Ideally, you should allow the user to configure what artifacts need to be collected. And the tool should fetch the DOM only when there is a failure, and not for every step.

5. Test Transparency & Readability

The last thing we want is a black box.

We don't want a test that shows us high-level instructions like "Perform the login" or even granular instructions like "Click on the Login button".

Storing tests as instructions for an AI invites ambiguity. You're not sure what that test will do, and you're not sure if it's the right thing.

The steps should be stored as human-readable instructions, but with clear selectors and parameters. So a test executed 1000 times will run the exact same instructions each time.

The other thing we don't want is for the output to be code. Using no-code tools to generate code tends to turn into a messy process.

6. Cross-Browser Testing

Whatever you might hear on LinkedIn or X, cross-browser testing is still important in most large organizations.

A large online retailer that spends tons of resources to optimize every detail doesn't want to miss out on purchases because the checkout flow is broken in Firefox or Safari.

And no, not everyone is using Chrome.

For those who are old enough to remember the Selenium days, you had to put in some effort to make the same test work on all major browsers, because options and capabilities had to be configured differently for each one. And even some things like tab switching or JS execution worked differently across different browsers.

The less obvious aspect is that Chrome on Windows is different from Chrome on Mac or Chrome on Linux, even if they look and work in the same way.

I've seen plenty of situations where a bug was present on Chrome on Windows, but not on Chrome on Linux.

It's somehow similar to games; a game might have a bug on PlayStation 5, but it might not have that bug on the PC version.

And don't even get me started on Headless Chrome.

Ideally, you want the option to run a test on browsers on Windows and macOS machines.

If a tool doesn't mention the operating system, there is a possibility that they're using headless browsers on Linux containers, which is cheaper for them, but not ideal for the user.

If someone says "A customer said they can't finish the purchase flow, they're on Safari on macOS", you don't want your answer to be "I don't know, our tests are running on headless Chrome on Linux. Tell them to try on Chrome."

7. Maintenance & Debugging

In test automation, most of the time and resources are consumed with maintaining and debugging tests, not with creating tests.

So, if someone brags that they just created 500 tests in 5 minutes, you can assume they don't have much experience in test automation.

The challenge is that having more and more tests means we have a lot more logs and errors to understand.

And this is a fantastic use case for AI.

Self-healing has been around since 2017, way before the GenAI boom. Back then, it was done by storing backup selectors during successful test executions and relying on those backup selectors when something went wrong (if the ID changed, maybe the other attributes stayed the same).

But now self-healing is powered by AI, which can analyze the step, the screenshot and the DOM and fix the test for you.

And most tools have some sort of "Analyze Failure with AI" functionality, to help you understand why an error happened.

And some even have "AI Summary" buttons for the logs, so you get an "executive summary" without having to read the entire logs.

8. Documentation & Customer Support

You'd expect everyone to have detailed, up-to-date docs nowadays, but it's not always the case.

I did find plenty of inconsistencies and outdated information.

Given the high price of most of these tools, I expected outstanding 24/7 technical customer support, but that's far from the truth.

I'd expect businesses to understand that not having real human technical support saves some money, but it also adds friction to the success journey of a user.

9. Enterprise Readiness

In general, these tools are more popular in the enterprise space than in the SMB space.

And thus, I'd expect enterprise features such as integrations, SSO, role-based access, API access, and security certifications (such as ISO 27001).

Most of the tools did really well here, with the exception of Katalon. I think the reason for that is that Katalon was initially a desktop app and they're still trying to navigate through the transition to being a cloud platform.

10. Portability & Vendor Lock-In

It's common sense to expect a modern platform to offer the option to take your data wherever you want.

That doesn't mean they should build a "Migrate to Competitor" feature, but it simply means offering the option of exporting your data in a useful format.

Some vendors used to provide an export output that was almost "intentionally" obfuscated and difficult to understand. But now AI makes it easy to insert exported data from one tool into another tool.

Having a simple option to export a JSON or a CSV is more than enough.

11. Pricing & Value

This one is a big differentiator.

The price tag can really change someone's impression of a tool. And I'm going to go on a rant here.

No one likes companies that hide their prices. Do they imagine that their pricing would scare potential users from trying their product?

In an ideal situation for such vendors, they'd expect a user to sign up for a free trial and then recommend the tool to their company and that user would never even find out what their company actually ended up paying for that tool.

Users know what cloud infrastructure and tokens typically cost; you can't overcharge them without causing resentment.

Having a very limited free plan or a very limited cheap starter plan as a "hook" is also a strategy that leaves a bad impression.

My view has always been that we should set prices based on "costs + margins" instead of "how much would they be willing to pay?"

For example, mabl and Functionize are good tools, but their prices are significantly higher than similar competitors, and it's difficult to justify such high prices.

12. Overall Usability

All the tools have decent usability. These are tools that have been on the market for a number of years, so they've had plenty of time to refine their UX.

That means the small things can really make a difference. And that's where you can almost tell when a company is actually using their own tool.

I honestly think Endtest really has the most intuitive UI. And there's so much attention put into all the details.

For example, in the Endtest Web Recorder, there's a toggle to start with a clean session.

When viewing the steps of a test case, you can also view them as a flowchart or as an AI summary.

On the opposite end, I found TestMu's UI to be a bit confusing and couldn't understand what was happening at some moments.

mabl has also improved its usability. A few years ago, it used unconventional names for certain items ("journeys" instead of "test cases"). I'm glad they gave up on that and started using the industry-standard terms.

Individual Tool Summaries

Endtest

What I liked

• Very intuitive UI
• Transparent pricing, with unlimited AI
• Really comprehensive E2E testing features

What I didn't like

• Not enough videos in the docs
• The Endtest MCP doesn't allow me to create tests with my own AI models

Biggest surprise

• The number of integrations. There are a lot more than I expected.

Real-world scenarios: 9/9
Execution speed: 1.21 steps/sec

Best suited for: Enterprises and SMBs. And any team that needs a reliable AI-powered test automation tool that is also affordable.

mabl

What I liked

• Pretty UI
• Great toolkit for E2E testing flows
• The API testing functionality is better than I expected

What I didn't like

• Lack of transparent pricing
• Execution speed was quite low compared with most of the other tools
• Some of the more advanced scenarios needed workarounds

Biggest surprise

• The API testing features. I wasn't expecting them to be this good.

Real-world scenarios: 6/9 + 3 workarounds
Execution speed: 0.38 steps/sec

Best suited for: Enterprises

Functionize

What I liked

• Very strong AI test creation
• Good enterprise functionality
• Native SMS testing, which almost nobody else has

What I didn't like

• The pricing is really hard to justify compared with some of the alternatives
• Some browser scenarios that I expected to be easy didn't work that well
• The tests don't feel as transparent and readable as I'd like

Biggest surprise

• The native SMS testing. They actually give you a phone number and let you test the real SMS flow, which is surprisingly rare.

Real-world scenarios: 6/9 + 2 workarounds
Execution speed: 0.61 steps/sec

Best suited for: Enterprises

Katalon

What I liked

• Lots of ways to create tests without AI
• Good documentation
• Very mature traditional test automation features
• TrueTest is an interesting approach for generating tests automatically

What I didn't like

• Some advanced scenarios need plugins, external services or workarounds
• It didn't do that well with some dynamic element scenarios
• Some parts still feel like they come from a desktop product that is now trying to become a cloud platform

Biggest surprise

• The execution speed. It was actually one of the faster tools.

Real-world scenarios: 4/9 + 3 workarounds
Execution speed: 1.07 steps/sec

Best suited for: Technical QA teams that want both low-code and scripted automation

BrowserStack Low Code Automation

What I liked

• Great cross-browser capabilities
• Very good debugging and maintenance functionality
• Excellent documentation
• You also get easy access to the rest of the BrowserStack ecosystem

What I didn't like

• The tests aren't always as transparent as I'd like
• Some advanced E2E scenarios still need workarounds
• Portability isn't as good as with tools that let you work directly with standard code formats

Biggest surprise

• How much BrowserStack has expanded beyond just browsers and devices. This is basically a full testing platform now.

Real-world scenarios: 5/9 + 2 workarounds
Execution speed: 0.83 steps/sec

Best suited for: Enterprises, especially teams that already use BrowserStack

Autify Nexus

What I liked

• Very intuitive UI
• I like the Playwright-based approach
• You can still work with actual Playwright code
• The AI test creation experience is pretty good

What I didn't like

• Quite a few of the more advanced scenarios needed workarounds
• Some E2E features aren't as complete as they are in the more mature platforms
• PDF testing isn't supported at all. You can only see the URL of the PDF, but not inspect or validate its contents

Biggest surprise

• The Playwright import/export functionality. This is probably one of the better approaches if you care about avoiding vendor lock-in.

Real-world scenarios: 3/9 + 4 workarounds
Execution speed: 1.02 steps/sec

Best suited for: SMBs and development teams that like Playwright but want something more visual and AI-assisted

TestMu AI KaneAI

What I liked

• Very good AI test creation
• Great browser and device coverage
• Good portability and code export options
• Pricing is pretty competitive

What I didn't like

• I found the UI confusing in some places
• The autonomous test generation wasn't as autonomous as I expected
• Several complex E2E scenarios either needed workarounds or didn't work

Biggest surprise

• The code export options. I expected it to be more locked into the platform than it actually is.

Real-world scenarios: 3/9 + 4 workarounds
Execution speed: 0.96 steps/sec

Best suited for: Teams that want AI-powered test creation and access to a large browser/device cloud

ACCELQ

What I liked

• It handled dynamic elements very well
• Strong enterprise features
• Good codeless test creation experience
• Reusable values and reusable groups of steps work well

What I didn't like

• Several advanced E2E scenarios aren't really supported natively
• Portability isn't as good as with tools that focus more on code export
• Pricing isn't very transparent

Biggest surprise

• How well it handled dynamically generated attributes. It was one of the few tools that didn't blindly use bad dynamic values in selectors.

Real-world scenarios: 5/9 + 1 workaround
Execution speed: 0.71 steps/sec

Best suited for: Enterprises that want a codeless automation platform with strong governance features

Tricentis Testim

What I liked

• Very good traditional test creation experience
• Excellent maintenance and debugging features
• Great documentation
• Custom JavaScript is available for some situations

What I didn't like

• A few years ago, I considered Testim one of the top tools in this space, but I feel like it has fallen behind since being acquired by Tricentis in 2022
• The AI test creation isn't as advanced as some of the newer AI-first tools
• Autonomous test generation is still pretty limited
• I couldn't get iframe or multiple-tab scenarios to work, even with a Custom Step workaround
• SMS and PDF scenarios needed workarounds
• Portability could be better

Biggest surprise

• The execution speed. It's one of the older and more mature tools, but it was still one of the fastest in the test.

Real-world scenarios: 5/9 + 2 workarounds
Execution speed: 1.03 steps/sec

Best suited for: Teams that have flows that do not involve multiple tabs or iframes. And teams that need to automate testing for Salesforce flows.

UiPath Test Cloud

What I liked

• Very strong enterprise functionality
• Good maintenance and debugging features
• Supports both low-code and coded automation
• Integrates really well with the rest of the UiPath ecosystem

What I didn't like

• Some browser-specific scenarios needed workarounds
• The whole platform can feel more complicated than a dedicated web testing tool
• Pricing and packaging aren't very simple
• Some things feel designed more around the wider UiPath automation ecosystem than web testing specifically

Biggest surprise

• Autonomous Exploration. UiPath has gone much further into autonomous testing than I expected.

Real-world scenarios: 5/9 + 3 workarounds
Execution speed: 0.62 steps/sec

Best suited for: Large enterprises, especially companies that already use UiPath