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 build an AI‑enhanced quality‑assurance (QA) platform that blends Side’s deep testing pedigree with Modl.ai’s cutting‑edge machine‑learning capabilities.
Modl.ai, a relatively new player in the gaming ecosystem, was founded in 2018 and secured $1.7 million in seed financing two years later. While the firm has already experimented with AI‑driven QA tools, earlier versions required developers to hand over full game builds or even source code, creating friction and limiting scalability. According to Modl.ai founder Christoffer Holmgard, those integration‑heavy approaches proved cumbersome and eventually “became difficult over time.” The new solution, however, eliminates the need for any internal access to a game’s codebase.
Holmgard explains that the process mirrors how a human tester would receive a finished product: the game is installed on a device that closely resembles—or is identical to—the consumer hardware. The AI then runs the title, watches the screen, simulates player inputs, and records a comprehensive data set of every on‑screen event. A second AI layer analyses this feed, flags potential defects, and escalates the findings to a human reviewer for final validation.
The first phase of the workflow is 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 to teach it the fundamentals of the game world. Holmgard notes that this interaction is entirely natural‑language‑based, allowing teams to supplement textual descriptions with images or other media. Once the AI has a solid contextual foundation, the development team defines the testing scope—ranging from conventional test cases to novel scenarios that play to the strengths of the AI engine. Human expertise remains essential at this juncture.
“You need some human insight to shape the prompts and guide the AI agent toward the right actions,” Holmgard says. After the AI executes the defined sessions—referred to as “runs”—it produces bug reports that include textual descriptions, short video clips as evidence, and detailed log data. These artifacts are handed to a seasoned QA specialist, who reviews them, decides on their relevance, and determines the next steps in the production pipeline. One of the perennial challenges in game QA is distinguishing a genuine bug from an intentional feature.
Holmgard points out that feedback loops from human testers help the AI refine its judgment over time. “Prompting, pre‑built game knowledge, and ongoing tester feedback all teach the system to recognize what is a defect versus what is a design choice,” he explains.
As the AI receives more annotations—such as “this is a bug because…,” or “this is expected behavior”—its predictive accuracy improves, making future testing cycles more efficient. Side sees this collaboration as a catalyst for redefining QA careers.
Chief Commercial Officer Martin McBride envisions QA staff evolving into AI engineers, moving up the value chain and gaining higher‑paying, more strategic roles. “Instead of a linear path from junior tester to senior tester, our people can transition into AI‑focused positions, which not only boosts compensation but also opens new career trajectories,” he says. This shift could also reverse the offshoring trend that has seen QA jobs migrate to low‑cost regions; by upskilling workers, Side hopes to repatriate talent to markets where such roles have dwindled. McBride adds that AI will relieve testers of repetitive, low‑skill chores, allowing them to concentrate on higher‑order analysis and creative problem‑solving.
“Every new build requires smoke tests and countless verifications that bog down a tester’s workflow. Automating those routine checks lets our team think strategically and grow professionally,” he notes. Similarly, Modl.ai’s Chief Product Officer Benedikte Mikkelsen observes that many current tests are monotonous and could be handled by a machine, freeing humans to evaluate gameplay feel and conduct exploratory testing. Both executives stress that AI is not a replacement for human QA but a complementary tool that elevates the profession.
McBride describes AI as a “sliding scale” where the human‑in‑the‑loop principle is non‑negotiable. “Our ethos is that there will always be a person overseeing the process. The AI reduces error and workload, but the final judgment still rests with experienced testers,” he asserts.
When asked about the types of games the system can currently handle, 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 mechanics. Fast‑paced, graphically intensive 3D open‑world or fighting games remain a future goal. Deslandes emphasizes that early adopters should be willing to pilot the solution and collaborate on its evolution, acknowledging that the journey will involve iterative refinements based on real‑world feedback.
In summary, the Side‑Modl.ai partnership aims to fuse robust human QA expertise with AI‑driven automation, creating a hybrid workflow that promises faster bug detection, reduced manual effort, and new professional pathways for testers. By starting with modest game genres and gradually expanding scope, the collaboration hopes to demonstrate tangible value, attract pilot customers, and ultimately reshape how quality assurance is performed across the gaming industry.