What is AI-driven game testing and why does it matter?
Leveraging AI across all areas of game development, including testing, is no longer just an innovation; it’s quickly becoming a necessity for teams looking to stay competitive. AI brings fresh perspectives to process automation and offers powerful ways to enhance the effectiveness of game testing.
AI-driven testing isn’t just about adding isolated AI features, such as image recognition for automated test verification, to existing test suites. While such capabilities can be extremely useful and significantly speed up daily test runs, true AI-driven testing involves reimagining the entire process. It means transforming testing workflows to fully harness AI’s advantages: increasing test coverage and repeatability while minimizing setup time. This approach is essential for complex and demanding applications like online games.
Why does this matter?
First, AI-based tools drastically reduce the time required for automating game tests. Traditional methods involved manually creating test scenarios for each game, an approach that could take hundreds of hours just to build a basic test suite for a single casino.
Second, AI expands test coverage to include visual elements rendered with technologies like Canvas or WebGL, without the need for painstaking and time-consuming content mapping using coordinates.
Together, these benefits can save substantial development time and bring a new level of reliability and efficiency to your games and casino platforms.
Best AI tools for game and software testing in iGaming
Appium and Selenium set the industry standard for test automation years ago, offering reliable and versatile frameworks for automating web and mobile applications. While they support a wide range of functionalities and multiple programming languages, their main limitation lies in their nature: they are code-based and can only process data that has been translated into known programming languages.
From a tester’s perspective, this means every aspect of the game testing process must be translated into test scripts. This is a time-consuming task, especially considering the large number of games in an online casino. Even when reusing existing scripts, testers must still manually update and verify each one individually.
Another challenge is test verification. Automated verification works well when test output can be easily extracted from the application’s HTML, but this is often not the case when testing key features of online games, where much of the content is rendered outside the HTML DOM.
This is where Percy becomes useful. Its screenshot comparison feature captures a screenshot at the end of a test case and compares it to a baseline image, the expected result.
While combining Appium, Selenium, and Percy can provide basic test coverage for most web and mobile applications, there is a significant shortcoming when it comes to game testing: these tools struggle with dynamic content such as animations and videos. Screenshots of such elements often appear blurry or unreadable, and it’s nearly impossible to fine-tune your test suite to consistently handle hundreds of different games.
Ultimately, the challenge lies in finding a tool or framework capable of processing and analyzing animated and video content and translating it into actionable test automation logic.
Currently, the only tool that meets these needs is PlayPatrol. This AI-powered solution is trained on hundreds of online casino games, with the sole purpose of understanding the sequence of actions and events that occur during gameplay. As a result, it can not only navigate casino platforms and games but also verify whether tests are executing correctly.
PlayPatrol operates using a single scenario to cover all games, significantly reducing the time required for onboarding new games. It automatically identifies whether tests pass or fail — delivering both efficiency and reliability in game testing at scale.
AI vs traditional QA – what’s the difference?
As mentioned in the previous chapter, traditional QA is a process in which a human tester acts as a proxy between the application and a testing tool or framework. The tester’s job is to understand how the application works, determine how it should be tested, and translate that knowledge into a code-based action plan that handles repetitive tasks.
With AI-driven QA, we incorporate an artificial tester, AI, which, of course, has some significant limitations compared to a human tester. For example, it requires a much larger amount of training data to produce reliable, repeatable, and accurate results. It also often needs additional data or human intervention to calibrate its learning process.
However, AI also brings several advantages: it processes data faster, never gets tired, and can operate at any time without complaints. Once it is trained to understand and handle specific tasks and processes, it can work more independently. Thanks to that once we taught our AI-tester how to test an online slot machine on certain amounts of online slot machines, calibrated the learning process and validated results, we can easily hire it to test any online slot machine without engaging actual human testers.
How AI supports compliance and faster time-to-market
There are, of course, many facets to game testing. One of the first things we traditionally think about is the technical side of the game: whether the reels are spinning correctly, bets can be placed, the wallet balance updates properly, and so on. Each of these functional aspects must be tested thousands of times before a game is released.
This isn’t just because we’re meticulous, it’s because we’re dealing with a random number generator, which makes it impossible to predict the exact outcome of each test scenario. Sometimes, to trigger a rare feature or bonus event, we literally need hundreds of spins. And we all agree that before releasing anything to the market, it needs to be tested more than once.
That’s where AI becomes particularly useful: repeating the same scenario thousands of times is exactly the kind of task it’s built for. Using AI in such cases can dramatically reduce the time required to thoroughly test a game before launch.
Another important aspect is meeting the technical requirements necessary for a game to be approved in certain markets. To comply with most licensing regulations, you must ensure that
the game adheres to specific rules. Verifying values such as RTP, minimum spin time, or maximum bet limits requires a reliable number of test runs. With the right tool, not only can you execute these tests quickly, but you can also record the entire testing process performed by the AI agent.
