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 to co‑develop an AI‑enhanced quality‑assurance platform for video games. The agreement ties the two companies together for half a year, during which they will integrate Side’s extensive QA expertise with Modl.ai’s cutting‑edge machine‑learning technology to create a hybrid testing solution that keeps a human in the loop. Modl.ai, a relative newcomer to the gaming sector, was founded in 2018 and secured $1.7 million in seed financing two years later.
Its early attempts at AI‑powered QA required developers to ship full game builds or even share source code so that the system could run deep integrations via plugins and SDKs. As Modl.ai’s founder Christoffer Holmgard explains, that approach generated a lot of friction and eventually became unwieldy for both studios and testers. The new joint offering eliminates the need for any internal code access. Instead, the game is delivered to the AI system exactly as a QA tester—or ultimately the end‑player—would receive it: installed on a comparable device, launched, and observed from the outside.
The AI watches the screen, mimics user inputs, records every on‑screen event, and compiles a comprehensive data set. A second AI layer then analyses that data, flags potential defects, and escalates each finding to a human specialist 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 title. Holmgard notes that this interaction is entirely natural‑language based; users can chat, attach images, or feed in design PDFs, allowing the system to form a contextual model of the game world. Once the AI has a solid grasp of the project, developers specify the testing objectives. These can range from traditional test cases—such as verifying menu navigation or collision detection—to more exploratory scenarios that are deliberately crafted to leverage the AI’s pattern‑recognition strengths.
Holmgard emphasizes that human insight remains crucial at this stage to phrase prompts correctly and guide the AI toward the most relevant actions. During a test run, the system generates bug reports that include textual descriptions, short video clips serving as evidence, and full log files. These artifacts are handed over to a qualified QA analyst, who reviews the findings, decides which issues merit further action, and provides feedback to the AI. Over time, this loop of human‑in‑the‑middle correction helps the algorithm distinguish between genuine bugs and intentional game features, refining its accuracy.
Side’s chief commercial officer Martin McBride sees the partnership as a way to elevate its workforce. Rather than keeping testers confined to repetitive, low‑value tasks, the AI handles the monotonous smoke‑tests and regression checks, freeing human staff to focus on strategic analysis, creative test design, and higher‑order problem solving. McBride envisions a career trajectory where a tester can evolve into an AI engineer, gaining new technical skills and higher compensation. He believes this shift could even reverse off‑shoring trends, allowing higher‑paid roles to return to regions that previously lost QA jobs due to cost pressures.
The company’s chief product officer, Benedikte Mikkelsen of Modl.ai, adds that many current QA activities are unnecessarily tedious. Automating repetitive flows lets human testers devote their attention to assessing gameplay feel, balance, and emergent player behavior—tasks that truly benefit from a human perspective. Both leaders stress that AI will never replace QA professionals entirely.
The price of manual testing in low‑cost markets remains too low to eliminate human involvement wholesale, and the nuanced judgment required for many defect classifications still depends on experienced eyes. Instead, AI acts as a force multiplier, lifting the overall quality of the testing process while reducing human error.
Side’s chief operating officer Oliver Deslandes notes that the technology is presently best suited to simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world adventures or fighting games. He explains that the current models thrive on predictable input‑output patterns, and more complex, high‑speed environments will require further development. Nonetheless, Deslandes encourages early adopters to join pilot programs, as their feedback will shape the roadmap for expanding the system’s capabilities.
In summary, the Side‑Modl.ai collaboration aims to blend the best of human expertise with AI efficiency, creating a sliding‑scale approach where automation handles the grunt work and humans oversee the strategic and creative aspects. The partnership reflects an industry‑wide shift toward smarter, more adaptable QA processes that promise higher job satisfaction for testers, better defect detection for developers, and a more sustainable testing ecosystem overall.