Navigating the Shift: How Mobile Games Industry Leaders View AI’s Evolution and Impact

Artificial intelligence remains one of the most polarizing and pervasive talking points in the global games industry. As generative tools, large language models, and machine learning systems become an increasingly common part of daily development pipelines, studios are continually finding novel ways to integrate the technology. From accelerating everyday administrative tasks and streamlining repetitive code refactoring to helping lean indie teams achieve more with fewer financial and human resources, AI has fundamentally altered the production landscape.

However, this rapid growth brings significant challenges. Persistent concerns surrounding the ethical use of AI, copyright disputes, intellectual property ownership, and the sheer ease with which software can be copied continue to raise vital questions about the technology’s long-term impact on the entertainment ecosystem. As these capabilities evolve at a breakneck pace, industry attitudes are shifting in complex ways. To understand how perspectives have transformed over the past year and how companies are actively utilizing these tools, we asked several prominent Mobile Mavens to share their insights.

The Operational Realities for Modern Studios

For Alisa Eren, Organic Growth Lead at Burny Games, the past year has fostered a pragmatic optimism regarding AI’s practical value, paired with a heightened awareness of how it is reshaping the competitive arena. Eren notes that the mobile games industry has evolved significantly, making the thoughtful, professional application of AI an essential requirement for maintaining a competitive edge. At Burny Games, Eren leverages AI daily to extend the team’s capabilities, continuously refining custom skills and workflows in Claude, automating task generation in Asana, and building automated user acquisition dashboards. By connecting these discrete tools into a unified workflow, the team reduces manual coordination and frees up valuable time to act on analytical insights.

Eren emphasizes that faster production ultimately raises the baseline for everyone in the market. After weeks spent optimizing internal processes, the Burny Games team can now handle at least double the workload per week without resorting to overtime. Yet, this efficiency creates a distinct managerial paradox. As more studios gain these capabilities, industry-wide competition intensifies. The primary opportunity lies in amplifying a team’s core expertise, while the central challenge is preserving creative quality and independent human judgment as operations scale. Eren believes that the strongest organizations will successfully combine a diverse range of human skills with systemic workflows that allow those skills to travel further.

This sentiment is echoed by Will Luton, Founder and Chief Product Officer at Village Studio Games. Luton observes that the broader games industry and the investment community appear to be traversing the classic Gartner hype cycle regarding large language models, currently sitting at various points between the peak of inflated expectations and the slope of enlightenment. Luton highlights that while AI can serve as a powerful accelerator for tedious, repetitive tasks when guided closely by human oversight, it quickly collapses when granted excessive autonomy or trust. The notion of prompting a fun, meaningful game into existence with a single command remains an unrealistic prospect, reinforcing the reality that skilled human programmers, writers, and designers are still indispensable.

To manage these dynamics, Village Studio enforces a strict internal policy: staff are free to utilize any AI tools they wish for supportive tasks, but all final art, sound, narrative design, and core game components must be 100% human-made. Luton relies on AI daily for coding assistance, primarily utilizing line completion and minor refactoring, noting that poorly generated AI code has previously cost the studio days and weeks of debugging. Furthermore, Luton points out broader risks associated with the technology, including cybersecurity vulnerabilities. Because malicious hacking often involves repetitive probing for weak spots—precisely the kind of repetitive labor AI handles efficiently—the short-term security landscape may face disruptions before defensive white-hat AI applications can properly balance the ecosystem.

Luton also sounds a cautionary note regarding the macroeconomic infrastructure supporting the current AI boom, warning of a potential dot-com-style financial bubble if circular investments in GPUs and data centers begin to collapse. This risk could be exacerbated by the rise of open-source models running locally on user hardware. If open models routinely cross the threshold of being "good enough," widespread reliance on centralized platforms could leave trillions of dollars in underlying infrastructure investments severely devalued.

Supply-Side Pressures and Changing Industry Demographics

Shifting focus to market dynamics, Colan Neese, Senior Vice President of Gaming at Screen Engine, observes that industry attitudes have fractured rather than swung uniformly. While coding assistants quietly permeated studio environments with minimal pushback, labor concerns and visible aesthetic choices—particularly art assets—remain flashpoints for controversy. The broader structural change, however, is the sheer volume of games entering the market. AI is pushing overall game production toward near-infinite output, even as the total amount of leisure time available to players remains fixed—a hyper-competitive dynamic mobile gaming has navigated for over a decade.

Neese points to proprietary attention-share data to illustrate this squeeze. The combined market share of the top ten tracked games plummeted from 36.5% to 27.8% between the launch week of Gears 5 in 2019 and the E-Day launch week. Despite these pressures, Neese remains an optimist, noting that the historic bottleneck of game development was never the conception of an idea, but the laborious execution of building it. AI now bridges that gap for anyone equipped with an idea and a free weekend. While hobbyist creations raise valid intellectual property questions, Neese draws a parallel to the early days of YouTube, which thrived on user-generated content and remix culture, suggesting that the next major wave of UGC will emerge from creators who previously lacked the technical means to build games.

At Almedia, Chief Operating Officer Jan Sommerfeld notes that AI has delivered substantial positive impacts across multiple business sectors over the past year. Almedia deploys AI across diverse departments, ranging from campaign performance analysis to bug report triage, and is currently developing internal data accessibility systems that allow staff to query company metrics securely using plain English. For Sommerfeld, the primary opportunity is liberating employees from repetitive administrative labor so they can focus on tasks requiring critical human judgment. Simultaneously, the chief operational concern is cost management; as companies scale their reliance on AI infrastructure, preventing expenditures from spiraling out of control remains a top priority.

Transforming Infrastructure and Managing Micro-Budgets

For Kimberley Shearer, Chief Marketing Officer at PingPlayers, AI’s most transformative impact on multiplayer gaming may lie in the technology running behind the scenes rather than the creative assets generated inside the virtual world. Shearer highlights AI-assisted infrastructure management as a major breakthrough, enabling developers to deploy servers, troubleshoot issues, manage configurations, and interact with infrastructure APIs using natural language commands. This capability significantly streamlines operations and empowers smaller teams to achieve more with fewer resources.

Paradoxically, however, the massive global expansion of AI data centres has disrupted traditional gaming economics, driving up RAM prices and straining hardware supply chains. The industry has reached an inflection point where AI simultaneously reduces software development costs while inflating the cost of the physical infrastructure required to host multiplayer experiences.

For small, mission-driven indie studios operating under strict financial constraints, these economic trade-offs are felt acutely. Pascal Clarysse, CEO of Big Karma and author of The Slingshot Formula, outlines how a lean indie team successfully integrates a disciplined suite of AI tools into daily operations. Big Karma relies primarily on three platforms: Gemini, integrated into Google Workspace for low-complexity tasks to preserve valuable Claude credits; Claude Code, operated locally by the lead developer on a high-performance machine for advanced coding and bug tracking; and Tripo, utilized by animators to generate initial 3D renders from hand-drawn character concepts created by veteran artist Miguel Francisco.

Despite keeping total AI expenditures well under 1% of the studio’s monthly burn rate, Clarysse estimates the efficiency gains equal two to three additional man-months of part-time freelance labor. Yet, as an economist and marketing expert, Clarysse voices deep concern over the macroeconomic implications of a supply-side explosion. If accessible production tools enable faster development across the board, individual demand for each title risks shrinking, compounding existing challenges in organic discovery and high user acquisition costs.

Moving Toward AI-First Ecosystems

Wenfeng Yang, Founder of the Big Bang Accelerator, observes that nearly every game team he engages with has incorporated AI into some facet of development or publishing. In development, tools like Tripo facilitate rapid prototyping and low-poly asset creation, bridging communication gaps between designers, artists, and programmers, while specialist human expertise remains essential for high-end polish. In publishing, teams routinely utilize AI to produce advertising creatives, execute automated A/B tests, and analyze market intelligence by combining platform analytics with advanced language models.

Furthermore, Yang points to the burgeoning commercial potential of AI-native products, signaling consumer appetite for interactive, AI-driven companionship and dynamic storytelling. On the investment front, game companies are increasingly acting as limited partners in funds backing AI startups, seeking active participation in shaping the underlying technologies. Looking further ahead, Yang anticipates the eventual emergence of AI-first companies where intelligent systems handle routine information sharing, task tracking, and coordination, freeing human talent to focus entirely on creative direction and strategic judgment. Having witnessed teams successfully deploy these systems to achieve tangible results, Yang views artificial intelligence as a permanent, structural transformation in how games are conceived, produced, and experienced.