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Redefining QA roles, enhancing development cycles, and balancing automation with human intuition
As the gaming industry continues its rapid evolution, the role of QA is transforming, driven by advancements in AI. To explore this shift, we spoke with Dajana Dimovska, CEO of Indium Play and co-CEO of NapNok Games. With over a decade of experience at the helm of innovative game development companies, Dajana offers a unique perspective on the intersection of technology and creativity in QA.
Having navigated multimillion-dollar PlayStation projects and leading a team of over 50 specialized testers at Indium Play, Dajana Dimovska brings deep expertise to the evolving world of game QA. Her forward-thinking approach, which blends AI-driven automation with manual testing, positions her as a key voice on how technology and creativity can work together to shape the future of QA.
Key Takeaways
- Combine AI with manual QA: Use AI to handle repetitive testing tasks, freeing QA professionals to focus on exploratory and creative work, enhancing efficiency and job satisfaction.
- Elevate the role of QA professionals: Shift QA from entry-level, repetitive tasks to a skilled discipline requiring critical thinking, creativity, and data analysis, leading to better career opportunities and compensation.
- Incorporate QA early in development: Introduce AI-driven QA at the start of the development cycle to identify and resolve issues efficiently, ensuring higher-quality outcomes.
- Balance AI speed with human intuition: Leverage AI for speed and coverage while relying on human testers for creative thinking and identifying unique edge cases.
- Simplify AI integration: Develop more plug-and-play AI tools to reduce complexity and ensure seamless adoption into QA workflows.
Combine AI with manual QA
AI is increasingly finding its place in games QA, but its real strength lies in working alongside human testers rather than replacing them. By automating repetitive and routine testing tasks, AI enables QA professionals to focus their efforts on areas that require critical thinking, creativity, and problem-solving. This integration boosts efficiency and enhances the overall experience of QA work, making it more engaging and fulfilling for testers.
“We definitely see the future as a combination of automation and manual testing. There are a lot of repetitive processes that can easily be figured out quite early in a project and prepped for AI execution. This saves time and resources while allowing testers to concentrate on explorative or functionality testing.”
Dajana highlights that AI’s ability to handle predictable tasks — such as running smoke tests or performing pattern recognition — frees testers from monotonous work. This shift accelerates workflows and positions QA as a more attractive and intellectually rewarding career path. As AI takes on routine testing, human testers can delve deeper into understanding player behaviors, breaking systems, and providing nuanced feedback that only a creative mind can offer. The collaboration between AI and manual testing creates a symbiotic relationship that enhances productivity and job satisfaction.
Tools like modl:test, powered by modl.ai’s behavioral AI engine, exemplify this balance by automating routine QA tasks while empowering teams to focus on creative problem-solving.
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Elevate the role of QA professionals
The role of QA professionals is poised for significant evolution. Historically, QA has often been viewed as an entry-level position, characterized by repetitive tasks and limited creative demands. However, the integration of AI is elevating QA into a specialized discipline, requiring critical thinking, creativity, and data analysis skills. This shift enhances the impact of QA professionals and opens doors for better compensation and more fulfilling career growth.
“I see it as saving time and also making the QA job more interesting as a career choice. Right now, the entry point for QA is quite low, but with AI tools, we can train testers to analyze data, think critically, and provide in-depth reports that help developers understand issues more deeply. It’s a step toward redefining QA as a respected and specialized discipline.”
With AI taking on repetitive testing, QA professionals are now free to tackle more complex tasks, such as identifying underlying patterns in bug reports or devising creative ways to break the game. This shift transforms QA into a career path that values expertise and ingenuity. Dajana emphasizes that this evolution will not only enhance the quality of games but also help QA gain the respect and recognition it deserves as a vital part of the development process.
Incorporate QA early in development
Incorporating QA from the earliest stages of development is a practice that can make or break a studio’s success. With the introduction of AI-driven QA tools, this approach becomes even more powerful. By identifying and addressing issues early in the development cycle, teams can save time, reduce costs, and maintain the high-quality standards players demand. Early integration of QA streamlines workflows and creates a stronger foundation for the game’s development journey.
“Having QA from early production until the end can be very helpful in reaching deadlines and the quality you expected. By integrating AI-driven QA tools early, you’re catching problems when the game is smaller and systems are less complex, making it faster and easier to fix issues before they escalate.”
Dajana highlights that early QA integration, especially with AI, allows teams to focus on building solid gameplay systems without being overwhelmed by late-stage fixes. The ability to run automated tests early and iteratively ensures that developers receive constant feedback, fostering a proactive rather than reactive approach to quality assurance. This early start lays the groundwork for a smoother development process and a better final product.
Balance AI speed with human intuition
AI has revolutionized QA by offering unmatched speed and coverage, but its capabilities are not without limitations. When it comes to understanding unpredictable player behavior or discovering edge cases that could disrupt gameplay, human intuition and creativity remain essential. A balanced approach — leveraging AI for efficiency and humans for ingenuity — ensures a comprehensive QA process that delivers quality and depth.
“I don’t think we’ll ever replace human behavior… that kind of intuitiveness and creativity. AI bots can explore within learned behaviors, but players act unpredictably. It’s the human testers who can think outside the box, break the system in ways no AI could, and offer insights into how the game truly feels.”
By allowing AI to handle repetitive and systematic tasks, QA professionals can dedicate their time to more nuanced challenges, such as analyzing player experiences or preemptively identifying potential exploits. This synergy between human testers and AI accelerates the QA process and ensures a higher standard of gameplay quality that resonates with players.
Simplify AI integration
Despite the promise AI brings to QA, its adoption comes with challenges. While 87% of game developers feel their studios are ready to implement AI in QA processes, many current AI tools require extensive setup, customization, and collaboration between teams, slowing down the potential for widespread integration. To truly unlock AI’s transformative potential, the industry needs tools that are seamless, intuitive, and ready to use out of the box.
“We are still waiting on a lot of solutions or improvements… that’s the biggest hurdle. When AI tools become easier to integrate — when they’re more plug-and-play — we’ll see faster adoption and a greater impact on QA workflows.”
Dajana underscores the need for AI solutions that can quickly adapt to different genres and projects without requiring exhaustive adjustments. Streamlined tools would allow teams to focus on QA itself rather than troubleshooting the technology. Addressing these integration challenges is a critical step toward making AI an indispensable part of game development that is capable of delivering efficiency and innovation.
Shaping the future of QA with AI-driven innovation
Integrating AI into QA processes is becoming less of a luxury and more of a necessity. Insights from leaders like Dajana emphasize that while AI offers tremendous advantages — speed, efficiency, and scalability — it thrives best as a complement to human creativity and intuition. By redefining the role of QA professionals, embedding testing earlier in the development cycle, and addressing challenges in AI adoption, studios can build stronger, more player-focused games.
“Human intuition will always play a vital role, but AI can elevate what we achieve together. The future of QA is a partnership between human testers and AI tools, working together to deliver better games.”
For studios ready to embrace this vision, AI-driven solutions like modl:test provide a powerful starting point. Modl.ai’s behavioral AI engine for games offers seamless automation of repetitive QA tasks, freeing testers to focus on the creative, critical work that makes games truly exceptional. By adopting tools like modl:test, studios can build resilient QA pipelines that not only meet but exceed the expectations of today’s players.
