Side, a long‑standing services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Danish artificial‑intelligence specialist Modl.ai. The agreement binds the two companies to collaborate on an AI‑driven quality‑assurance (QA) platform that aims to reshape how video‑game testing is performed.
Modl.ai, a newer player in the gaming sector, was founded in 2018 and secured $1.7 million in seed capital two years later. Side brings decades of experience in outsourced services, while Modl.ai contributes cutting‑edge machine‑learning expertise. "The MOU effectively brings the best of what Side has and the best of what Modl.ai has together in a unique solution," explains Martin McBride, Side’s chief commercial officer.
"One of the crown‑jewel, holy‑grail experiences for the games industry right now has been using AI technology to better augment QA services. No one's really found a great solution for that. We think we have." Earlier AI‑enabled QA tools, including Modl.ai’s first generation, required developers to ship entire builds or even share source code so that the testing system could instrument the game.
That approach proved cumbersome, creating friction that slowed adoption. "It became difficult over time," admits Modl.ai founder Christoffer Holmgard. The new solution eliminates the need for internal access. Instead, the game is delivered to the AI exactly as a QA tester—or eventually a consumer—would receive it: installed on a comparable device, run, and observed.
The system operates in two stages. First, it builds what Modl.ai calls "game knowledge." Developers upload assets, design documents, screenshots, and other relevant files, then converse with the AI in natural language to teach it the game's mechanics, narrative, and visual style.
"All of this is in natural language," Holmgard notes. "We just chat with the system about our game, but we're also adding in images, or we might upload our game design documents and so on." Once the AI has a contextual model, developers specify the testing objectives. These can range from classic test cases—such as verifying that a menu opens correctly—to novel scenarios designed to exploit the AI’s pattern‑recognition strengths. Holmgard stresses that human expertise is still essential at this juncture: "You need some human expertise here to adapt the prompting and the language to the AI agent to make it do the right things." During a "run" (Modl.ai’s term for a testing session), the AI plays the game, monitors the screen, simulates key inputs, and records a comprehensive data set of every event.
A second AI layer analyses this data, flags anomalies, and generates bug reports. The output includes textual descriptions, short video clips as evidence, and full log files.
These reports are then handed to a human QA specialist for review. "We get all the texts, and we get some video snippets that we call evidence along with all the log data and everything," Holmgard explains.
"A human expert reviews it and decides what happens with it for the rest of our production." One of the most nuanced challenges is distinguishing a genuine bug from an intentional feature. The system learns from the feedback loop provided by human testers: they label each report as "bug," "not a bug," or "feature," and explain why.
Over time, this iterative feedback refines the AI’s judgment, making it increasingly attuned to the subtleties of game design. Side envisions a broader impact on the labour market. By equipping QA staff with AI tools, they can transition from repetitive test execution to higher‑value roles such as AI‑engineer or data‑analyst.
"One of the cool parts about programs like this is that we get to move our people up the value chain," says McBride. Instead of a linear career path from junior tester to senior tester, employees can evolve into AI‑focused positions, commanding higher salaries and opening new career trajectories. This shift could also repatriate jobs to regions where low‑cost testing has previously migrated, because the higher‑skill roles are less sensitive to price differentials. McBride adds that AI will make QA careers more fulfilling by automating the monotonous, repetitive tasks that currently dominate testers' daily routines.
"For every new build you have to do smoke tests and many verifications that bog down workflow," he says. "By knocking these out and automating them, testers can think more strategically, focus on analysis, and grow their expertise." Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: "There are some very tedious tests that testers are performing right now.
You don't really need a human doing the same flow over and over again. That person could be doing something much more valuable, like assessing the gameplay itself or doing more creative kinds of testing. That, I think, is a value proposition of using AI." Both leaders stress that AI is not a replacement for human QA workers but a catalyst for upskilling. The price point for manual testing in certain low‑cost regions remains so low that a complete AI takeover is unrealistic.
However, providing testers with AI‑enhanced toolsets extends their careers, improves accuracy, and reduces human error. "There's always going to be an opportunity for people to do a lot of the testing work here because the price point of testing right now is so low in certain countries that it's very hard to augment it completely away," McBride observes. "But by giving our people tool sets like this, I'm allowing them to further their career." Side’s philosophy is that AI operates on a "sliding scale" with a perpetual human in the loop—its core ethos.
"That's sort of our ethos," McBride affirms. "This tool really does allow our people to take the best of what AI can offer and reduce the burden and also reduce mistakes. A lot of this work is tedious and prone to human error. You take that out of the equation, and everything ratchets up a notch and it becomes better." When asked about the types of games the system can handle, COO Oliver Deslandes admits the current focus is on simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—not fast‑paced 3D open‑world adventures or fighting games.
"We have to focus on titles that are more appropriate. What we're aiming for at this stage is really clients that are willing to come on the journey with us because it could very much depend on what they want to do with this," Deslandes says.
He acknowledges that the technology is still evolving: "The reality is that it's a journey, but if you are at the table now with us and maybe doing some pilots, then you will see where this tech goes." In summary, the Side‑Modl.ai partnership seeks to blend human expertise with AI efficiency, creating a hybrid QA model that reduces repetitive workload, improves bug detection, and opens new career pathways for testers worldwide. The six‑month MOU marks the first step toward a future where AI augments—but never fully replaces—the nuanced judgment of seasoned QA professionals.