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 testing expertise with Modl.ai’s cutting‑edge machine‑learning capabilities. Modl.ai, a relatively new player in the gaming industry, was founded in 2018 and secured $1.7 million in seed capital two years later.
Its founders have long sought a way to let AI truly augment QA rather than merely automate repetitive tasks. According to Martin McBride, Side’s chief commercial officer, the partnership “brings together the strongest assets of both companies into a unique solution that could become the industry’s holy grail for AI‑powered QA.” He believes the collaboration may finally deliver a practical, scalable answer to a problem that has long frustrated developers. Earlier AI‑based QA tools required developers to hand over entire game builds—or even source code—to a testing vendor.
Modl.ai’s previous offering relied on a plugin and software development kit (SDK) that integrated directly with the game’s internals, creating friction and, as co‑founder Christoffer Holmgard explains, “became difficult over time.” The new approach eliminates the need for any deep integration. Instead, the game is treated exactly as a QA tester or a consumer would receive it: installed on a comparable device, run, and observed from the outside. The system works by capturing the visual output of the game, simulating player inputs, and compiling a comprehensive data set of every on‑screen event. This raw information is then fed to a second AI layer that flags potential bugs, escalates them to a human reviewer, and asks whether corrective action is warranted.
Holmgard describes the first phase as building “game knowledge.” Developers upload assets, design documents, screenshots, or even short video clips, and converse with the AI in natural language to teach it the fundamentals of the title. Once the AI has a baseline understanding, developers specify the testing objectives. These can range from classic test cases—such as verifying menu navigation or collision detection—to more exploratory scenarios that are tailored to the AI’s strengths.
Holmgard stresses that human expertise is still essential at this stage: “You need to craft prompts and guide the AI so it performs the right actions.” During a testing run, the AI records logs, captures short video snippets as evidence, and generates textual bug reports. These artifacts are handed over to a seasoned QA specialist, who reviews the findings and decides the next steps for the production pipeline.
One of the persistent challenges in automated testing is distinguishing a genuine defect from an intended feature. Holmgard notes that continual feedback from human testers helps the AI refine its judgment. Over time, the system becomes attuned to the nuances of the particular game’s design language.
Side envisions this technology reshaping the career trajectory of its QA staff. Rather than remaining confined to repetitive test execution, employees can evolve into “AI engineers,” overseeing prompt engineering, data analysis, and system tuning. McBride explains that this shift moves workers up the value chain, offering higher salaries, new career pathways, and the possibility of repatriating jobs to regions where low‑cost testing has previously migrated. He adds that AI should relieve testers from monotonous duties, allowing them to focus on strategic analysis and creative problem‑solving.
Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “Tedious, repeatable tests don’t need a human to perform them over and over. By automating those flows, testers can devote their time to assessing gameplay, exploring edge cases, and delivering higher‑level insights.” Both leaders are careful to stress that AI will not replace QA professionals.
McBride points out that testing costs remain low in certain markets, making a full AI takeover impractical. Instead, the toolset augments human capability, extending careers and improving overall quality. He describes AI as a “sliding scale” where a human is always present in the loop—a principle that forms the core of Side’s ethos. Regarding applicability, Chief Operating Officer Oliver Deslandes notes that the current solution works best with simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced 3D open‑world or fighting games remain a longer‑term goal. He emphasizes that early adopters should be willing to pilot the technology and accept that the journey will involve iterative refinement.
In summary, the Side‑Modl.ai partnership aims to combine Side’s deep QA heritage with Modl.ai’s AI innovations to create a hybrid testing model. By feeding the AI with external game interactions, building contextual knowledge through natural‑language dialogue, and retaining human expertise for validation and decision‑making, the collaboration hopes to deliver faster, more accurate bug detection while elevating the role of QA professionals.
The initiative reflects a broader industry trend toward AI‑assisted workflows that enhance—not replace—human talent, promising a more strategic and rewarding future for those working in game quality assurance.