Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Denmark‑based artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to develop an AI‑driven quality‑assurance (QA) platform that blends Side’s deep testing expertise with Modl.ai’s emerging AI capabilities. Modl.ai, a relatively new player in the gaming sector, was founded in 2018 and secured $1.7 million in seed funding two years later.
While the company has already experimented with AI‑enabled QA tools, earlier versions required developers to hand over entire game builds—or even source code—so the system could run its analyses. That “integration‑based” approach, which relied on plugins and SDKs, proved cumbersome and created friction for development teams, according to founder Christoffer Holmgard. The new solution, Holmgard explains, eliminates the need for any internal code access.
Instead, the game is delivered to the AI system exactly as a QA tester—or eventually a consumer—would receive it: installed on a comparable device, launched, and observed. The AI watches the screen, simulates player inputs, records every on‑screen event, and then hands the collected data to a second AI layer that flags potential bugs. Those flagged items are then presented to a human reviewer for final validation.
The process begins with what Modl.ai calls “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant materials, then converse with the AI in plain language. This dialogue helps the system form a contextual understanding of the game’s mechanics, narrative, and visual style. Holmgard notes that the interaction is entirely natural‑language‑based, allowing teams to simply “chat” with the AI while supplementing the conversation with images or documentation.
Once the AI has a solid grasp of the title, developers specify the testing objectives. These can range from traditional test cases—such as verifying menu navigation or level loading—to novel scenarios that are especially suited to AI‑driven exploration. Holmgard stresses that human expertise is still essential at this stage to craft effective prompts and guide the AI toward the right actions.
During a test run, the system generates comprehensive bug reports that include textual descriptions, short video clips (referred to as “evidence”), and detailed log files. These artifacts are then passed to a seasoned QA specialist, who reviews the findings and decides the appropriate course of action for the production pipeline.
One of the enduring challenges for AI in gaming QA is distinguishing genuine defects from intentional features. Holmgard says that feedback loops from human testers are crucial for teaching the AI these nuances. Over time, as testers label items as “bug,” “not a bug,” or “intended behavior,” the AI refines its judgment and becomes more attuned to the particular design philosophy of each project. Side envisions this collaboration reshaping the career trajectory of its QA staff.
Rather than remaining confined to repetitive test execution, employees can evolve into AI engineers who design prompts, interpret AI outputs, and fine‑tune the system. Chief Commercial Officer Martin McBride argues that this shift not only raises salaries and creates new career pathways, but also opens the possibility of bringing QA jobs back to regions where they have previously migrated due to cost pressures.
By moving workers up the value chain, Side hopes to retain talent longer and distribute opportunities more globally. McBride also highlights the qualitative benefits for testers themselves.
The AI handles routine smoke tests and other monotonous checks, freeing human QA professionals to focus on strategic analysis, gameplay evaluation, and creative testing. This, he believes, leads to more fulfilling work experiences and better professional development. Modl.ai’s Chief Product Officer Benedikte Mikkelsen echoes this sentiment, noting that many current test procedures are unnecessarily tedious. “You don’t need a person to repeat the same flow over and over,” she says.
“Instead, they can spend time assessing the game’s feel, exploring edge cases, or conducting more inventive forms of testing—exactly the value proposition AI brings.” Both leaders are careful to stress that AI will never replace QA humans entirely. The price point for manual testing remains low in certain markets, making a full automation takeover impractical.
Instead, AI serves as an augmentative tool that elevates human contributors, allowing them to apply higher‑order skills while the system manages the grunt work. McBride describes Side’s philosophy as a “sliding scale” for AI adoption: the technology can take on more responsibilities as confidence grows, but a human will always remain in the loop. “That’s our ethos,” he says. “The tool lets us leverage AI’s strengths—speed, consistency, error reduction—while preserving the critical judgment that only experienced testers can provide.” When asked about the types of games the platform currently supports, Chief Operating Officer Oliver Deslandes is candid.
The AI works best with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games. “We’re focusing on titles where the gameplay loop is predictable enough for the AI to model effectively,” he explains. “Clients who are willing to pilot this technology with us will help shape its evolution, and as we gather more data, we’ll expand into more complex genres.” In summary, the Side‑Modl.ai partnership aims to blend the reliability of seasoned QA practices with the efficiency of modern AI, all while keeping human insight at the core of the process.
The collaboration promises to reduce repetitive workload, create new technical roles, and potentially revitalize QA employment in regions that have seen job erosion, all without compromising the quality standards that gamers expect.