Side, a seasoned services provider, 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. The partnership blends Side’s deep experience in the services sector with Modl.ai’s cutting‑edge AI capabilities, aiming to create a solution that augments traditional QA processes without eliminating the human element.
Side, previously known as PTW, has been a fixture in the outsourcing and testing arena for years. Modl.ai, by contrast, is a newer player that broke into the gaming market in 2018 and secured $1.7 million in seed funding two years later. Martin McBride, Side’s chief commercial officer, describes the MOU as “the convergence of the best that Side offers and the best that Modl.ai brings, resulting in a unique offering.” He adds that the gaming industry has long chased a “holy‑grail” – an AI‑powered QA system that genuinely enhances testing efficiency. According to McBride, many attempts have fallen short, but the duo believes they have finally found a workable approach.
Earlier AI‑enabled QA tools, including earlier versions from Modl.ai, required developers to ship full builds or even source code to the testing vendor. Those solutions relied on integration plugins and SDKs, creating friction and scalability problems, as noted by Modl.ai founder Christoffer Holmgard.
The new system eliminates the need for internal access. Holmgard explains that the product is treated exactly as a QA tester would receive it – a compiled build placed on a device similar to the consumer’s hardware.
The AI then runs the game, observes the screen, simulates key inputs, records every interaction, and passes the resulting data to a second AI layer that flags potential bugs. Human reviewers then decide whether each flagged issue warrants action.
The first phase of the 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 in plain language. Holmgard says the interaction is entirely natural‑language‑based: “We just chat with the system about our game, adding images or design docs as needed.” This conversational model allows the AI to develop a contextual understanding of the title before testing begins.
Next, developers specify the testing objectives. These can range from traditional test cases to novel scenarios that exploit the AI’s strengths. Holmgard stresses that human expertise is still crucial at this stage to craft effective prompts and guide the AI toward the right actions. Once the parameters are set, the system executes a “run” – Modl.ai’s term for a testing session – and automatically generates bug reports.
Each report includes textual descriptions, short video clips that serve as evidence, and comprehensive log data. These artifacts are handed to a human QA specialist, who reviews them and determines the appropriate next steps for the production pipeline.
Holmgard points out that distinguishing a genuine bug from an intended feature can be challenging for AI alone. Ongoing feedback from human testers helps the system learn these nuances. Over time, the AI becomes attuned to the specific design language of the game, improving its precision. Side envisions a future where QA professionals evolve into AI engineers, shifting the skill set required for quality assurance.
McBride explains that this transition moves staff up the value chain, offering higher salaries, new career trajectories, and the possibility of bringing jobs back to regions where they have previously disappeared due to cost pressures. By automating repetitive, low‑value tasks, the AI frees testers to focus on strategic analysis, creative testing, and deeper gameplay evaluation.
“Repeated smoke tests and routine verifications can bog down a tester’s workflow,” McBride notes. “When the AI handles those, our people can think more strategically and grow their careers.” Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment, arguing that eliminating tedious, repetitive flows lets humans concentrate on higher‑order tasks such as assessing gameplay feel and conducting inventive test scenarios. Both executives stress that AI is not a replacement for human QA workers but a tool that elevates their role. McBride says the current price point for manual testing in certain low‑cost regions makes a full AI takeover impractical.
Instead, providing AI‑assisted toolsets extends career longevity and retains talent by moving them into more valuable positions. Side’s philosophy frames AI as a “sliding scale” – a spectrum where human involvement never disappears. “There will always be a human in the loop; that’s our ethos,” McBride asserts. The AI reduces human error and monotony, raising overall quality while preserving the critical judgment that only experienced testers can provide.
When asked about the types of games the solution currently supports, COO Oliver Deslandes admits the technology is best suited for simpler titles – puzzles, card games, and other experiences with repeatable mechanics. Fast‑paced 3D open‑world or fighting games remain a longer‑term goal. Deslandes emphasizes that early adopters should be clients willing to experiment and iterate, acknowledging that the journey will involve pilots, refinements, and gradual expansion into more complex genres. In summary, the Side‑Modl.ai partnership aims to blend AI efficiency with human expertise, creating a QA ecosystem where repetitive testing is automated, bug detection is accelerated, and QA professionals can ascend to more strategic, higher‑value roles.
The six‑month MOU serves as a proving ground for this vision, with the ultimate aim of reshaping how quality assurance is performed across the gaming industry.