Side, a long‑standing 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 commits the two organisations to collaborate on building 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 capital two years later. While Side brings decades of experience in delivering testing services to game developers, Modl.ai contributes a suite of AI tools designed to automate and augment the detection of bugs and other quality issues.
According to Martin McBride, Side’s chief commercial officer, the partnership "effectively combines the best of what Side has and the best of what Modl.ai has into a unique solution." He adds that creating a reliable AI‑driven QA system has long been described as a "holy grail" for the games sector, and that the duo believes they are close to achieving it. Earlier AI‑based QA approaches, including Modl.ai’s previous offerings, required developers to hand over entire game builds or even source code so that the testing platform could integrate via plugins and SDKs. This method proved cumbersome and introduced significant friction, as noted by Modl.ai founder Christoffer Holmgard.
The new solution eliminates the need for any internal access. Instead, developers provide the finished product exactly as they would to a human tester or eventual consumer. The AI then runs the game on a device that mirrors the target hardware, watches the on‑screen action, simulates user inputs, and records a comprehensive data set of every event that occurs. Once the raw data is captured, a second AI layer analyses it, flags potential defects, and escalates those findings to a human reviewer for validation.
Holmgard describes the initial phase as "building game knowledge": developers upload assets, design documents, screenshots, or even converse with the system in plain language to teach the AI about the game’s mechanics, narrative, and visual style. This conversational, natural‑language interface allows the AI to develop a contextual understanding that goes beyond simple code analysis.
After the knowledge base is established, developers specify the test scenarios they wish the AI to execute. These can range from traditional test cases—such as verifying menu navigation or collision detection—to novel, AI‑friendly challenges that exploit the system’s strengths. Holmgard emphasizes that human expertise remains essential at this stage to craft effective prompts and guide the AI toward the right behaviours.
When a test run (or "session") concludes, the platform produces a bug report that includes textual descriptions, short video clips serving as evidence, and detailed log files. These artefacts are handed to a senior QA specialist, who reviews the findings, decides on their relevance, and determines the appropriate remediation steps. One of the persistent challenges in automated testing is distinguishing genuine bugs from intentional features.
According to Holmgard, feedback loops from human testers help the AI learn these nuances over time. "Prompting, pre‑built game knowledge, and continuous human feedback all contribute to fine‑tuning the system’s judgement," he explains. Side envisions a future where QA professionals evolve into "AI engineers," leveraging the technology to shift their roles up the value chain.
McBride argues that this transition can revitalize job markets in regions where low‑cost testing has previously migrated away. By upskilling staff to manage and improve AI‑driven workflows, Side hopes to offer higher wages, new career pathways, and the possibility of bringing jobs back to countries that lost them due to price pressures.
The partnership also promises a more rewarding experience for testers. Repetitive, low‑level tasks—such as running smoke tests on every new build—can be automated, freeing humans to focus on strategic analysis, creative testing, and gameplay evaluation. "When the tool handles the boring, repetitive work, our people can think more strategically and grow their careers," McBride says.
Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment, noting that many current tests are tedious and could be better performed by a machine, allowing humans to concentrate on higher‑order assessments. Both companies stress that AI will not replace QA staff but will augment them.
McBride points out that testing costs remain low in certain regions, making a complete AI takeover impractical. Instead, providing sophisticated AI tools enables existing teams to extend their expertise, remain competitive, and enjoy longer, more fulfilling careers. Regarding the scope of games the solution can handle, Side’s chief operating officer Oliver Deslandes admits that the technology is presently best suited to simpler titles—puzzle games, card games, and other experiences with repeatable mechanics.
Fast‑paced, graphically intensive 3D open‑world or fighting games are still a few steps away. Deslandes stresses that early adopters should be developers willing to experiment and iterate alongside the AI, acknowledging that the system will evolve based on real‑world feedback. In summary, the Side‑Modl.ai collaboration aims to create a hybrid QA ecosystem where AI handles data‑intensive, repetitive testing while human specialists provide the critical judgement and creative insight that only experience can deliver. By positioning AI as a "sliding scale" with a permanent human in the loop, the partnership seeks to raise the overall quality of game releases, reduce errors, and open up new professional trajectories for QA talent worldwide.