Side, a seasoned services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Danish 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 capabilities.
Modl.ai, a relatively new entrant to the gaming industry, was founded in 2018 and secured $1.7 million in seed financing two years later. While the startup has already experimented with AI‑based QA tools, earlier versions required developers to hand over complete builds or even source code, creating friction and limiting scalability. According to Modl.ai founder Christoffer Holmgard, those integration‑heavy approaches proved cumbersome and ultimately stalled adoption.
The new solution, Holmgard explains, eliminates the need for any internal access to a game’s code. "We treat the product exactly as you would hand it to a human tester or eventually to the consumer," he says. "The game runs on a device that mirrors the target platform, our system watches the screen, simulates key inputs, records every visual and data point, and then passes that stream to a second AI layer that flags potential bugs. That layer escalates findings 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 even converse with the AI using natural‑language prompts.
This conversational interface helps the system construct a contextual model of the game’s mechanics, narrative, and visual style. "All of this happens in plain language," Holmgard notes.
"We can chat about the game, attach images, feed in design docs, and the AI learns from that multimodal input." Once the AI has a baseline understanding, developers specify the testing scope. They may select traditional test cases—such as regression checks or performance benchmarks—or craft novel scenarios that play to the strengths of the AI, like exploring emergent gameplay loops. Holmgard stresses that human expertise is still required at this stage to phrase prompts effectively and guide the AI toward meaningful exploration.
During a test run, the system generates comprehensive bug reports that include textual descriptions, short video clips as evidence, and full log files. These artifacts are handed off to a seasoned QA specialist, who reviews the findings, decides on severity, and determines the appropriate remediation path.
"The human reviewer adds the final layer of judgment," Holmgard says. "They confirm whether an anomaly is a genuine defect, an intended feature, or a design nuance that the AI might misinterpret. Over time, this feedback loop fine‑tunes the AI’s perception of what constitutes a bug in that particular game." One of the recurring challenges in automated testing is distinguishing between a flaw and a deliberate design choice. Holmgard points out that the AI improves its accuracy by learning from repeated human feedback, gradually aligning its internal model with the developers’ intent.
Side sees this partnership as a catalyst for upskilling its workforce. Chief Commercial Officer Martin McBride envisions QA staff evolving into "AI engineers" who design prompts, interpret AI outputs, and refine the testing pipeline. This shift, he argues, moves employees up the value chain, offering higher‑pay roles and new career trajectories. "Instead of a linear ladder from junior tester to senior tester, we can now offer a path toward AI‑focused engineering," McBride explains.
"That not only raises salaries but also opens the possibility of bringing jobs back to regions where low‑cost testing was previously outsourced." McBride also highlights the human‑centred benefits of automation. Repetitive smoke tests and routine verifications consume a large portion of a tester’s day, limiting strategic thinking. By offloading these monotonous tasks to AI, testers can focus on higher‑order analysis, creative exploration, and gameplay evaluation.
"The tool reduces the burden of repetitive work, freeing our people to think strategically and grow professionally," he says. Modl.ai’s Chief Product Officer Benedikte Mikkelsen echoes this sentiment, noting that many current QA activities involve tedious, repeatable flows that a machine can execute far more efficiently.
"When a tester no longer has to run the same sequence a dozen times, they can invest that time in assessing game feel, balance, or innovative testing approaches," Mikkelsen adds, framing AI as a value‑adding augmentation rather than a replacement. Both leaders stress that AI will never fully replace human QA talent. The price point for manual testing in certain low‑cost regions remains so low that a complete automation takeover is economically impractical. Instead, the goal is to equip people with smarter tools, extending their careers and enhancing job satisfaction.
"There will always be a human in the loop—that’s our ethos," McBride affirms, describing AI as a "sliding scale" where human oversight remains essential. Regarding the types of games the solution currently supports, Side’s Chief Operating Officer Oliver Deslandes admits the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable, slower mechanics. High‑intensity, fast‑paced genres such as fighting games or expansive 3D open worlds present additional challenges that the team plans to tackle in later phases. "We’re targeting clients willing to pilot this journey with us," Deslandes says.
"The early adopters will help us refine the system, and as the technology matures, we’ll expand to more demanding titles." In summary, the Side‑Modl.ai collaboration aims to create a hybrid QA ecosystem where AI handles the grunt work of data collection and initial bug detection, while seasoned human testers provide the nuanced judgment only a person can supply. By merging Side’s operational experience with Modl.ai’s AI research, the partnership aspires to raise the overall quality of game releases, improve tester career prospects, and gradually broaden the scope of AI‑driven testing across the gaming industry.