Side, a long‑standing services provider formerly known as PTW, has entered into a six‑month memorandum of understanding with the Danish artificial‑intelligence specialist Modl.ai. The agreement sets the stage for a joint effort to build an AI‑driven quality‑assurance (QA) platform that blends Side’s deep testing expertise with Modl.ai’s cutting‑edge machine‑learning technology. Modl.ai, a relative newcomer to the gaming sector, was founded in 2018 and secured $1.7 million in seed capital two years later.
Its chief commercial officer, Martin McBride, frames the partnership as a marriage of the best assets each company brings to the table. “One of the holy‑grail experiences for the games industry today is leveraging AI to augment QA services,” he says.
“No one has nailed a robust solution yet – we think we’re about to change that.” Earlier AI‑based QA tools, including Modl.ai’s initial offering, required developers to ship entire builds—or even source code—to the testing firm. That approach relied on an integration‑heavy plugin and SDK, creating friction and, as founder Christoffer Holmgard notes, becoming “difficult over time.” The new system eliminates the need for any internal access. Instead, developers hand over the product exactly as they would to a human tester or eventual consumer, running it on a comparable device. The AI watches the screen, simulates key actions, logs every event, and then passes the compiled dataset to a second AI layer that flags potential bugs, escalates them to human reviewers, and asks whether corrective action is warranted.
The first phase, which Modl.ai calls building “game knowledge,” involves developers uploading assets and conversing with the AI in plain language. Holmgard explains that the interaction can include text, images, design documents, and other media, allowing the system to form a contextual understanding of the title. Once that foundation is set, developers specify the testing scope—ranging from classic test cases to novel scenarios tailored to the AI’s strengths. “Human expertise is still needed to craft the right prompts and guide the AI agent,” Holmgard adds, emphasizing the collaborative nature of the workflow.
When a test run—referred to as a “session” by Modl.ai—concludes, the platform generates a comprehensive bug report. The output includes textual descriptions, short video clips serving as evidence, and full log data. These artifacts are handed to a seasoned QA specialist who reviews them and decides the next steps for the production pipeline.
One persistent challenge for AI is distinguishing a genuine defect from an intentional feature. Holmgard says that continuous feedback from human testers helps the system learn these subtleties. Over time, the AI becomes attuned to the nuances of game design through a combination of prompting, pre‑built game knowledge, and iterative human input.
Side envisions a future where QA personnel evolve into AI engineers, reshaping the global distribution of testing jobs. McBride notes that this shift allows employees to move up the value chain, transitioning from routine testing roles to higher‑paid, more strategic positions. “When we elevate our people, we can bring jobs back to regions that lost them due to low‑cost labor pressures,” he explains.
The AI’s automation of repetitive tasks—such as smoke tests for each new build—frees testers to focus on strategic analysis, creative problem‑solving, and deeper gameplay evaluation. Benedikte Mikkelsen, Modl.ai’s chief product officer, echoes this sentiment: “Many current tests are monotonous and don’t require human judgment. By automating those flows, testers can concentrate on assessing gameplay and conducting more inventive testing, which is where real value lies.” Both executives 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 total AI takeover impractical.
Instead, the toolset empowers workers to extend their careers, acquire new skills, and remain valuable contributors for longer periods. He describes AI as a “sliding scale”—always accompanied by a human in the loop, which he calls the company’s core ethos.
When asked about the types of games the solution currently supports, Side’s chief operating officer Oliver Deslandes admits the technology is best suited for simpler titles—puzzle games, card games, and other experiences with repeatable mechanics. Fast‑paced, graphically intensive 3D open‑world or fighting games remain out of scope for now. Deslandes emphasizes that early adopters should be willing to embark on a pilot journey, acknowledging that results will vary based on project demands and budget constraints. In summary, the Side‑Modl.ai partnership aims to create a hybrid QA model where AI handles the heavy lifting of data collection and preliminary bug detection, while human experts provide the critical judgment and contextual insight that machines still lack.
By blending automation with human oversight, the collaboration seeks to raise the overall quality of game releases, enhance career pathways for QA professionals, and gradually expand the range of game genres that can benefit from AI‑enhanced testing. The six‑month MOU marks the first step in what both parties anticipate will be a longer‑term evolution of quality assurance in the gaming industry.