Side, a veteran 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 a next‑generation, AI‑enhanced quality‑assurance (QA) platform tailored for the gaming industry.
Modl.ai, although a relative newcomer, has been active in the games sector since its 2018 launch and secured $1.7 million in seed capital two years later. According to Martin McBride, Side’s chief commercial officer, the partnership combines the deep operational expertise of Side with Modl.ai’s cutting‑edge AI technology to create a solution that could become a "holy grail" for game developers seeking smarter QA processes. Historically, AI‑powered QA tools required developers to hand over full game builds, source code, or integrate SDKs and plugins into their pipelines.
This "integration‑based" model created friction, as it forced studios to expose internal assets and often resulted in cumbersome workflows. Modl.ai’s founder, Christoffer Holmgard, explains that the new approach eliminates the need for any internal access. Instead, the system treats the game exactly as a human tester or end‑user would: the product is loaded onto a device—sometimes the same hardware a consumer would use—and the AI observes the screen, simulates inputs, records every interaction, and then hands the collected data to a second AI layer that flags potential bugs.
Human reviewers then decide whether each issue warrants action. The first phase of this workflow is what Modl.ai calls "building game knowledge." Developers upload assets, design documents, screenshots, or any other relevant material and converse with the AI using natural‑language prompts. This dialogue helps the system construct a contextual model of the game’s mechanics, narrative, and visual style. Once that foundation is in place, the development team defines the testing scope—ranging from conventional test cases to novel scenarios that are particularly well‑suited to AI‑driven exploration.
Holmgard stresses that crafting effective prompts still demands human expertise. "You need to translate your testing goals into language the AI understands," he notes, highlighting the collaborative nature of the process.
After the AI runs a "session" (Modl.ai’s term for a test run), it produces a comprehensive bug report that includes textual descriptions, short video clips as evidence, and full log data. These artifacts are forwarded to a seasoned QA specialist who reviews them, determines the severity of each finding, and decides the next steps in the production pipeline.
One of the persistent challenges in automated testing is distinguishing genuine bugs from intentional game features. The system improves its judgment over time by incorporating feedback from human testers. When a QA analyst labels a finding as a bug, a non‑bug, or a design choice, that information is fed back into the AI, gradually refining its ability to interpret nuanced design decisions.
Side envisions this technology reshaping the career trajectory of its QA staff. Rather than remaining in repetitive testing roles, employees can evolve into "AI engineers," overseeing prompt engineering, data curation, and model tuning. McBride explains that this shift not only raises salaries and creates new career pathways but also offers the potential to repatriate jobs to regions where low‑cost testing has previously migrated.
By moving staff up the value chain, Side hopes to retain talent longer and provide more fulfilling work that emphasizes strategic analysis over monotonous test execution. Both McBride and Modl.ai’s chief product officer Benedikte Mikkelsen agree that AI should handle the drudgery of repetitive checks—such as smoke tests for each new build—freeing human testers to focus on higher‑order tasks like gameplay assessment and creative testing. "You don’t need a person to repeat the same flow over and over," Mikkelsen says.
"Instead, they can evaluate the experience, explore edge cases, and contribute ideas that only a human can generate." Despite the optimism, the partners acknowledge that AI will not replace QA professionals. The price point for manual testing in certain low‑cost markets remains too low to eliminate human involvement entirely.
Instead, AI acts as an augmentation tool that reduces error rates and speeds up routine verification, allowing humans to concentrate on tasks that require judgment, intuition, and domain expertise. Side’s chief operating officer Oliver Deslandes adds that the current iteration of the AI solution is best suited for simpler titles—puzzle games, card games, or other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games. He emphasizes that early adopters should be willing to experiment and pilot the technology, as the system will evolve based on real‑world feedback and the specific demands of each client.
In summary, the Side‑Modl.ai collaboration aims to blend human insight with machine efficiency, creating a QA ecosystem where AI handles the bulk of repetitive validation while seasoned testers provide the critical thinking and nuance that only people can supply. This "sliding scale" philosophy—where a human is always in the loop—forms the core of Side’s ethos and reflects a broader industry trend toward smarter, more collaborative quality‑assurance workflows.