Side, a veteran services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with Danish artificial‑intelligence specialist Modl.ai to co‑develop an AI‑driven quality‑assurance platform for the gaming industry. The agreement binds the two firms to collaborate on a system that blends Side’s extensive QA expertise with Modl.ai’s cutting‑edge AI capabilities, aiming to create a more efficient, scalable, and insightful testing process. Modl.ai, founded in 2018, raised $1.7 million in seed capital two years later and has since been positioning itself as a forward‑thinking player in the games market. While earlier AI‑enabled QA tools required developers to hand over full builds or even source code—often via plugins, SDKs, or deep integration—this approach generated considerable friction and limited adoption.
According to Modl.ai founder Christoffer Holmgard, the new solution eliminates the need for any internal access. "We take the product exactly as you would hand it to a QA tester or ultimately to the consumer," he explains. "The game runs on a comparable device, our system watches the screen, simulates key actions, records a comprehensive data set, and then a second AI layer reviews that data to flag potential bugs.
Those findings are then presented to a human reviewer for final validation." The workflow begins with what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, and even converse with the AI in natural language to teach it the fundamentals of the title. "All of this happens through simple chat interactions," Holmgard notes, "but we also ingest visual material and other documentation to create a rich, multimodal understanding of the game." Once the AI has a baseline comprehension, developers define test objectives. These can range from conventional test cases—such as verifying UI elements or checking level loading—to more exploratory scenarios that are specifically tailored for AI execution. Holmgard stresses that human expertise remains critical at this stage: "Crafting effective prompts and guiding the AI’s language model requires seasoned QA insight so the system behaves as intended." During a test run, the AI records textual logs, video snippets (referred to as "evidence"), and other telemetry.
This information is compiled into a bug report that is handed off to a human QA specialist for review. The specialist decides whether the issue is a genuine defect, a design choice, or a false positive, and provides feedback that the system uses to refine its future predictions.
"Over time the AI becomes attuned to the nuances of game design through this continuous loop of human feedback," Holmgard says. Side sees this collaborative model as a pathway to elevate its workforce.
Chief Commercial Officer Martin McBride envisions QA staff transitioning into AI‑engineer roles, thereby moving up the value chain. "Instead of a career that ends at senior tester, our people can become AI engineers, earn higher salaries, and open new career trajectories," he states.
This shift could also help repatriate jobs that have migrated to lower‑cost regions, as higher‑skill positions become more geographically flexible. McBride adds that AI will make QA work more fulfilling by automating repetitive, low‑value tasks such as smoke tests and routine verifications.
"When the AI handles the drudgery, our testers can focus on strategic analysis, gameplay assessment, and creative testing approaches," he explains. This sentiment is echoed by Modl.ai’s Chief Product Officer Benedikte Mikkelsen, who points out that many current tests are monotonous and could be better performed by humans if the AI took over the repetitive flows. Both companies stress that AI is not a replacement for human testers but a force multiplier.
McBride notes that price pressures in certain countries make it difficult to eliminate human QA entirely, yet providing advanced tools enables staff to extend their careers and deliver higher‑value contributions. He describes AI as a "sliding scale" where the proportion of automation can be adjusted, but a human will always remain in the loop—an ethos that underpins Side’s approach. Regarding the types of games the solution currently supports, Side’s Chief Operating Officer Oliver Deslandes admits that the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games. "We are focusing on projects where the AI can demonstrate immediate value while we continue to expand its capabilities," he says.
Deslandes emphasizes that early adopters will likely be partners willing to pilot the system and help shape its evolution. In summary, the Side‑Modl.ai partnership aims to create a hybrid QA ecosystem where AI handles data‑intensive, repetitive testing while human experts provide strategic direction, nuanced judgment, and continuous feedback. By doing so, they hope to reduce errors, accelerate release cycles, and ultimately empower QA professionals to evolve into higher‑skill roles, fostering a more sustainable and rewarding career path within the gaming industry.