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 paves the way for a joint venture that blends Side’s deep‑rooted QA capabilities with Modl.ai’s cutting‑edge AI technology to create an AI‑enhanced quality‑assurance platform for the gaming industry.
Modl.ai, a relatively new player in the games sector, was founded in 2018 and secured $1.7 million in seed capital two years later. Its early attempts at AI‑driven testing required developers to hand over complete builds or even source code, using a plug‑in and SDK that tightly integrated with the development pipeline.
According to co‑founder Christoffer Holmgard, that approach generated excessive friction and eventually proved unsustainable. The new solution, however, eliminates the need for any internal access to the game’s codebase. "We treat the product exactly as you would hand it to a QA tester or eventually to a consumer," Holmgard explains. "The game runs on a device that mirrors the end‑user hardware, our AI watches the screen, simulates key actions, records every event, and then hands the resulting data set to a second AI layer that flags anomalies, escalates them to human reviewers, and asks whether they merit further action." The process begins with 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.
This dialogue helps the system construct a semantic model of the game’s mechanics, art style, and narrative flow. Holmgard notes that the interaction is entirely natural‑language‑based, allowing teams to simply "chat" with the AI while feeding it visual and textual references. Once the AI has a foundational understanding, the development team defines the testing scope. Test cases can range from traditional, scripted scenarios to novel, AI‑friendly challenges that exploit the system’s strengths.
Here, human expertise is still essential: engineers must craft prompts and instructions that guide the AI toward the desired behavior. "You need a skilled tester to shape the language and the prompts so the AI does the right thing," Holmgard says.
During a test run—referred to by Modl.ai as a "session"—the AI records video snippets, log files, and textual summaries that constitute the evidence of any detected issues. These artifacts are then passed to a human QA specialist, who reviews the findings, validates whether each item is truly a bug or an intended feature, and decides the next steps for the development pipeline.
Holmgard emphasizes that distinguishing bugs from features remains a nuanced judgment that benefits from human feedback, which in turn fine‑tunes the AI’s future performance. Side envisions a future where QA professionals evolve into AI engineers, shifting the value chain upward. Chief Commercial Officer Martin McBride explains that this transition can revitalize careers, increase compensation, and even bring jobs back to regions where low‑cost testing labor has previously driven work offshore.
"Instead of a linear path from tester to senior tester, our people can become AI engineers, opening new career ladders and allowing us to retain talent longer," he says. The AI tool also promises to make QA roles more rewarding by automating repetitive, low‑skill tasks such as smoke testing and routine verification. By offloading these chores to the machine, human testers can focus on strategic analysis, creative exploration, and higher‑order problem solving. "When the boring, repetitive work is removed, our staff can think more strategically and grow professionally," McBride adds.
Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: many current tests are monotonous and can be performed more efficiently by an algorithm. This frees human testers to concentrate on gameplay assessment, artistic evaluation, and inventive testing methodologies—areas where human intuition still outperforms machines. Both companies stress that AI will never replace QA workers entirely.
The price point for manual testing in certain low‑cost regions remains so low that a complete AI takeover is economically unrealistic. Instead, the technology acts as a force multiplier, enhancing human capabilities while preserving jobs.
"There will always be a human in the loop—that’s our ethos," McBride affirms, describing AI as a "sliding scale" that adjusts its involvement based on context. Regarding the types of games the platform currently supports, Chief Operating Officer Oliver Deslandes notes that the system is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics—rather than fast‑paced 3D open‑world or fighting games. "We’re focusing on titles where the gameplay loop is predictable and not overly rapid," he says.
"Clients willing to pilot the technology with us can help shape its evolution toward more complex genres." In summary, the Side‑Modl.ai partnership aims to blend human expertise with AI efficiency to create a more agile, cost‑effective, and fulfilling QA process. By keeping humans at the center of decision‑making while leveraging AI to handle the grunt work, the collaboration hopes to set a new standard for quality assurance in the gaming industry, one that can adapt over time as the technology matures and expands into broader game categories.