Side, a long‑standing services provider formerly known as PTW, has entered into a six‑month memorandum of understanding (MOU) with Danish artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to create an AI‑driven quality‑assurance (QA) platform that blends the strengths of each partner.
While Modl.ai brings cutting‑edge machine‑learning expertise to the table, Side contributes deep industry knowledge and a global network of QA professionals. Together they aim to deliver a solution that can augment, rather than replace, human testers.
Modl.ai, founded in 2018, raised $1.7 million in seed capital two years later and has since been experimenting with AI‑enabled testing tools. Early versions of the technology required developers to hand over entire game builds or even source code, which meant integrating a plugin or SDK into the development pipeline. That approach proved cumbersome and, as Modl.ai’s founder Christoffer Holmgard admits, “became difficult over time.” The new system eliminates the need for any internal code access.
Instead, the game is treated exactly as a QA tester or eventual consumer would receive it: it is installed on a comparable device, the AI runs the title, watches the screen, simulates key inputs, and records every observable event. The recorded data is then passed to a second AI layer that scans for anomalies, flags potential bugs, and escalates findings to a human reviewer.
Holmgard describes the first phase of the workflow as “building game knowledge.” Developers upload assets, design documents, screenshots, and other relevant materials, then converse with the AI in natural language to teach it the specifics of their title. This conversational interface allows the system to absorb visual and textual cues, creating a nuanced model of the game’s mechanics and intended behavior.
Once the AI has a baseline understanding, developers specify the testing objectives. These can range from classic regression test cases to novel scenarios that are better suited to AI‑driven exploration. Holmgard notes that human expertise is still essential at this stage to craft effective prompts and guide the AI toward the right actions.
The AI then executes the defined sessions—what Modl.ai calls “runs”—and produces comprehensive bug reports. Each report includes textual descriptions, short video clips that serve as evidence, and full log data. These artifacts are handed over to a seasoned QA specialist, who reviews the findings and decides the appropriate next steps for the development pipeline.
A persistent challenge in automated testing is distinguishing a genuine defect from an intended feature. The system relies on continuous feedback from human testers to fine‑tune its judgment. As Holmgard explains, testers annotate bug reports with confirmations such as “this is a bug,” “this is not a bug,” or “this is an intended feature, because….” Over time, this iterative feedback loop trains the AI to better recognize the subtle design decisions that differentiate errors from gameplay choices. Side envisions a broader transformation of the QA workforce.
Chief Commercial Officer Martin McBride sees the AI tool as a pathway for testers to evolve into AI engineers, thereby moving up the value chain. “Instead of a career that stops at senior tester, our people can become AI engineers, earn higher salaries, and open new career trajectories,” he says. This shift could also reverse the off‑shoring trend that has seen QA jobs migrate to lower‑cost regions.
By equipping staff with higher‑skill responsibilities, Side hopes to bring talent back to markets where such roles have previously disappeared. McBride emphasizes that the AI is not meant to replace humans but to relieve them of repetitive, low‑value tasks. Smoke tests, regression checks, and other routine verifications often consume a large portion of a tester’s day, limiting their ability to think strategically.
Automating these chores frees QA professionals to focus on deeper analysis, creative testing, and gameplay assessment—activities that are more intellectually rewarding and career‑enhancing. Benedikte Mikkelsen, Modl.ai’s Chief Product Officer, echoes this sentiment: “There are very tedious tests that testers are performing right now.
You don’t need a human to repeat the same flow over and over. That person could be doing something more valuable, like evaluating the gameplay itself or conducting exploratory testing.” The value proposition, therefore, lies in reallocating human talent to tasks that require imagination and critical thinking, while the AI handles the grind.
Both companies acknowledge that AI will not instantly solve every testing scenario. McBride describes AI adoption as a “sliding scale” where a human remains in the loop at all times—a core part of Side’s ethos. He points out that the current price pressure on testing services in certain countries makes a complete AI takeover impractical.
Instead, the goal is to provide tools that augment human capability, extend career longevity, and improve overall quality. Regarding the types of games the solution can currently support, Chief Operating Officer Oliver Deslandes notes that the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. Fast‑paced, graphically intensive 3D open‑world or fighting games remain a longer‑term objective.
Deslandes stresses that early adopters should be willing to experiment and accept that the system will evolve alongside their feedback. In summary, the Side‑Modl.ai partnership aims to create a hybrid QA model where AI performs high‑volume, repetitive testing and humans provide the strategic oversight and nuanced judgment that machines lack. By combining natural‑language interaction, visual data capture, and continuous human feedback, the platform aspires to reduce errors, accelerate testing cycles, and ultimately deliver higher‑quality games to market. The six‑month MOU will serve as a proving ground for this approach, with pilots expected to reveal both the strengths and the remaining challenges of AI‑enhanced quality assurance in the gaming industry.