Beyond the Hype: How Global Game Developers Are Actually Implementing Artificial Intelligence

As the global games industry prepares for the upcoming Pocket Gamer Connects Nordics event on October 20th and 21st, conversations surrounding artificial intelligence have moved far beyond speculative futurism. While massive tech conglomerates launch new tools, secure billions in funding, and draft aggressive IPO plans amid dramatic claims about the existential trajectories of large language models, day-to-day developers are finding pragmatic ways to integrate the technology. At PGC Nordics, the dedicated AI Gamechangers Summit will tackle these realities head-on, opening with a keynote by former Take-Two Interactive head of AI and LuDic AI founder Dr. Luke Dicken. Entitled "Surviving The AI Hype Cycle – A Pragmatist’s View," the session sets the tone for an industry-wide reassessment of how artificial intelligence functions inside active production pipelines.

Throughout the two-day summit, industry leaders such as Wooga’s Holger Wurst, Game Makers of Finland’s Wilma Ramona Ikäheimonen, and Gamepack Studio’s Ruslan Zelenskyi are set to explore the multifaceted impacts of the technology. Discussions will range from the everyday disruption experienced by visual artists to the viability of AI-assisted development and the growing role of autonomous agents in game creation. To understand where the technology truly delivers value away from the marketing noise, industry stakeholders have opened up about how they harness machine learning and generative tools right now.

"More Shots at Goal" in Modern Game Production

For executive leadership overseeing massive portfolios of developers, AI offers a structural shift in how projects are conceptualized and scaled. Maria Redin, president and CEO of MTG—a group managing studios including Plarium, Snowprint Studios, and InnoGames—explains that building new games today looks fundamentally different than it did even a year ago. According to Redin, studios can restructure their teams and leverage modern tooling to completely alter the development lifecycle of fresh IP.

Where a single development team might have previously spent an entire year delivering one major title, optimized workflows now allow organizations to tackle three projects concurrently by scaling teams differently and utilizing automated assistance. Redin notes that this operational shift provides studios with "more shots at goal," allowing teams to test a wider array of creative concepts, quickly terminate unviable prototypes, and, ideally, reach the market at an accelerated pace.

In contrast to the blank-slate approach of greenfield titles, implementing artificial intelligence in established pipelines requires a different strategy. When addressing how the technology enters production workflows for existing games versus brand-new projects, Redin points out that studios cannot simply discard well-functioning legacy systems. Instead, developers adapt and tweak every single process within the existing production chain, embracing available tools to ensure they can operate faster, generate higher volumes of content, and execute rigorous testing cycles.

Diverse Approaches Across Global Studios

The integration of artificial intelligence varies wildly depending on a studio’s history, geographical location, and technical maturity. South Korean publisher NC, which has steadily expanded its mobile casual division, approaches the technology from a foundation of deep, long-term research. Veroplay CEO Anel Ceman notes that NC has been actively developing its own proprietary large language models for 15 years, positioning AI at the very core of the enterprise rather than treating it as a superficial add-on. On the user acquisition front, Ceman highlights that internal models allow the publisher to produce promotional creatives at roughly 70% to 80% of traditional costs, delivering assets that are cheaper, faster, and often superior in quality.

Curiously, the rush to adopt generative tools is not universal even among developers operating in regions heavily associated with technological experimentation. Ryan, co-founder of Chinese studio Hypergryph—currently developing the highly anticipated Arknights: Endfield—reveals that the title uses almost no artificial intelligence. However, that specific project began production before the current industry-wide wave of generative AI hype took hold, underscoring how project timelines dictate technical adoption.

Meanwhile, studios across the Nordic region are finding practical, unglamorous niches for the technology. Daniel Rantala, chief growth officer at Fingersoft, explains that the studio primarily deploys AI across core programming, data analysis, visualization, error-proofing, and other repetitive or time-consuming tasks. Rantala notes that the company continuously evaluates where machine learning fits into its daily operations, backing those verified use cases with dedicated tooling and secure access to advanced AI systems.

Mikael Gummerus, chairman and co-founder of Drive Ahead developer Dodreams, echoes the sentiment that the most transformative impact for his studio lies in data analysis and transforming raw metrics into actionable insights. Gummerus reports that AI has significantly reduced manual workloads and decreased the number of fragmented systems the team must juggle. The resulting process is not only less expensive and higher in analytical quality, but it also surfaces perspectives and suggestions that the studio simply lacked the manpower to uncover previously.

At the same time, Gummerus points out that the same revolutionary leap has yet to materialize in Unity development or traditional artwork creation, where advancements remain incremental rather than transformational. Hind Toufga, founder of Julicia Studio, shares a similar cross-studio perspective, noting that developers are increasingly turning to AI for coding support, automated testing, quality assurance, localization, concept development, and repetitive production chores. For Toufga, the most compelling aspect of the technology is not the replacement of creative talent, but its capacity to help smaller teams work efficiently while freeing human developers to focus on tasks that genuinely demand human judgment and creativity.

Practical Use-Cases and Monetisation

The practical application of machine learning was also a central theme at ChinaJoy and the concurrent PGC Summit Shanghai, where panel discussions focused on concrete operational use-cases rather than speculative futures. Speakers demonstrated how developers are utilizing AI to drive down production costs across prototyping, localization, and art design, proudly sharing short cinematics, interface elements, and conceptual artwork generated through machine learning pipelines.

For Mattel163, COO Devin Nambiar emphasizes that artificial intelligence has already moved the needle significantly across multiple operational pillars. On the monetisation and user acquisition side, predictive modeling and return on ad spend (ROAS) forecasting allow the publisher to dynamically calibrate user acquisition campaigns across diverse channels, a capability he describes as paramount in a highly competitive market environment. On the content side, Nambiar notes that AI assists live content pipelines by working alongside designers to generate engaging mini-games, streamline seasonal updates, and accelerate localization efforts for limited-time events.

As the industry looks past the noise generated by hyperscalers and PR-driven panic, artificial intelligence is steadily cementing its place as a practical toolkit for modern game development. These themes, practical methodologies, and real-world case studies will take center stage when industry leaders gather at Pocket Gamer Connects Nordics.