Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to build an AI‑enhanced quality‑assurance (QA) platform that blends Side’s deep testing expertise with Modl.ai’s cutting‑edge machine‑learning technology.
Modl.ai, a relative newcomer to the gaming sector, was founded in 2018 and secured $1.7 million in seed capital two years later. Its founder, Christoffer Holmgard, explains that earlier attempts at AI‑powered QA required developers to hand over full builds, source code, or integrate proprietary SDKs. Those methods created significant friction, slowed pipelines, and ultimately proved unwieldy for large‑scale production environments. The new solution eliminates the need for any internal code access.
"We treat the product exactly as you would hand it to a QA tester or eventually ship to a consumer," Holmgard says. The game is installed on a device that mirrors the target platform, and the AI watches the screen, emulates user inputs, and records every on‑screen event. This raw data is then fed to a second AI layer that flags anomalies, generates bug reports, and escalates items that require human judgment.
The workflow begins with what Modl.ai calls "building game knowledge." Developers upload assets—textures, models, design documents, even screenshots—and converse with the AI in plain language. The system ingests these inputs, forming a semantic model of the game’s mechanics, narrative flow, and visual style.
Holmgard emphasizes that the interaction remains natural‑language‑based: "We just chat with the system about our game, adding images or design docs as needed." Once the AI has a foundational understanding, developers specify the testing objectives. These can range from traditional test cases (e.g., verifying that a menu opens correctly) to novel scenarios crafted to exploit the AI’s pattern‑recognition strengths. Here, human expertise is still vital.
"You need to shape the prompts and guide the AI so it performs the right actions," Holmgard notes, underscoring the collaborative nature of the process. During a test run, the AI captures textual logs, video snippets (referred to as "evidence"), and comprehensive telemetry.
This package is handed to a seasoned QA specialist, who reviews the findings, validates whether each flagged item is truly a defect or an intended feature, and decides on subsequent actions. Over time, feedback from these human reviewers refines the AI’s decision‑making, allowing it to distinguish subtle design nuances and reduce false positives. Side sees this partnership as a pathway to elevate its workforce.
Chief Commercial Officer Martin McBride explains that QA personnel can transition from repetitive manual testing to roles as "AI engineers," overseeing prompt design, data interpretation, and system tuning. This shift not only raises salaries but also creates new career ladders, potentially repatriating jobs to regions where low‑cost testing has previously migrated away. McBride adds that automating monotonous tests frees testers to focus on strategic analysis and creative exploration. "Smoke tests, regression checks, and other routine verifications consume a lot of time," he says.
"By offloading those to AI, our people can concentrate on higher‑order tasks like gameplay balance, user experience assessment, and innovative test design." Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, echoes the sentiment: "There are many tedious flows that a human can repeat endlessly without added value. Let the AI handle those, and let the tester evaluate the fun factor, discover emergent behaviors, and conduct more insightful testing." Both executives stress that AI will never fully replace human QA staff. The price differential for low‑cost testing in certain countries remains a barrier to complete automation, and human insight is essential for interpreting ambiguous results.
Instead, AI acts as a lever to "move people up the value chain," extending careers and enhancing job satisfaction. Side characterizes its AI philosophy as a "sliding scale"—a spectrum where human involvement gradually recedes but never disappears.
"There will always be a human in the loop; that's our ethos," McBride affirms. By reducing manual error and fatigue, the technology lifts overall quality while preserving the critical human judgment that defines great games. Regarding applicability, Chief Operating Officer Oliver Deslandes notes that the current iteration excels with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced 3D open‑world or fighting games present greater challenges and will be addressed in later phases. Deslandes encourages early adopters to join pilot programs, emphasizing that the journey is iterative: "If you partner with us now, you’ll see how the tech evolves and where it can take your QA processes." In summary, the Side‑Modl.ai collaboration aims to blend robust human expertise with sophisticated AI analysis to create a more efficient, insightful, and rewarding QA ecosystem for the gaming industry. The MOU marks the first step toward a future where testers become AI‑savvy engineers, repetitive drudgery is minimized, and game quality reaches new heights through a balanced partnership between man and machine.