PocketGamer.biz publishes Mobile Mavens Part 2 on AI

Susan Cummings opens with a developer-forward pitch: at 10six, AI enables player-specific content that wouldn’t have been practical before. She points to YOU vs Zombies, where the game can use as little or as much personal input as a player wants so that characters, story settings and representation match a player’s real life. Cummings contrasts that creative upside with a different cultural problem on PC: “For PC developers, the biggest problem is fear. Fear that admitting to any use of AI is like a Scarlet Letter on the game.” She says mobile and Roblox teams haven’t hit the same stigma, and adds a practical barrier: early adoption is harder when the tooling keeps changing. The net effect, by her account, is Western studios have been cautious rather than experimental when it comes to novel, AI-native gameplay.

Adam Smart splits the market in two and names the commercial pressure on mobile teams: studios “admit they’d be behind competitors if they hadn’t adopted AI.” He writes that mobile has moved to AI as a competitive necessity, especially for smaller teams doing more with less, while many Western PC and console studios remain reluctant because they fear player backlash. Smart contrasts that with APAC publishers, who he says are “openly using AI to build games faster and cheaper, not waiting for permission.” He also flags Epic’s AI MegaJam as a potential legitimiser for open AI use. Smart’s optimism is tempered by a heavy concern about discovery: if AI dramatically lowers the cost of making games, storefronts could become flooded and “organic discovery is hard enough now and could become nearly impossible.” He repeats a practical paradox later in the piece: AI may democratise development while making it harder than ever to actually succeed as a developer, because making more games does not automatically solve reaching the right audience.

Vadim Andreev brings a production-side account from 2026, saying AI accelerated adoption across workflows and enabled a “vibe coding” approach that lets developers ship quickly. He emphasises two concrete benefits: lowering production barriers and speeding development cycles, which in turn allow developers to release more frequently and open new channels of player monetisation. Andreev highlights a direct studio-level advantage for small teams: those “embedding AI across every phase of development are empowered to release highly polished, high-end titles.” He expects adoption to broaden next year and compares the likely jump in game production to how AI video moved from short clips to full-length content, arguing that studios integrating tools early will secure a competitive advantage over those that resist.

Elina Arponen keeps the tone practical: AI raises the floor on quality and serves as a “tireless sparring partner” for internal processes, but it doesn’t raise the ceiling for extraordinary creativity. She flags a specific risk many indie developers are already feeling: “One of the most unfortunate side effects is that games get copied more easily, and this is now being felt especially in the indie / Steam development scene.” To tackle that, Arponen and colleagues are proposing a concrete alternative to wide early builds: interactive trailers that convey a game’s idea without sharing game code or a full demo. She says a letter is underway to gather support before taking the proposal to Steam/Valve.

Peter Fodor offers a view from an agency that has pushed into AI tooling: AppAgent built AdAgent, an AI-assisted video ad production tool, and AppBrain, “a second brain” for company knowledge. Fodor reports an industry shift in client acceptance — two years ago most clients refused AI on their games; today most permit it within strict legal limits. He lays out three practical learnings from building tools: AI rarely invents without human refinement; AI can spot what wins but not why; and workflow speed-ups tend to yield marginal gains unless teams rethink how work is done. His prediction is operational: many studios will hit a wall in 6–12 months when higher creative volume doesn’t produce higher revenue, because the real ceiling is wrong audience, wrong message or wrong emotional driver. His concrete prescription: teams that use AI to buy time for thinking, not to stop thinking, will continue to have value.

Erik Dubbelboer and Philip Morris provide two complementary angles on quality, curation and sentiment. Dubbelboer says attitudes have become more measured, with the conversation shifting from raw excitement to practical uses that add value for players. He points to quality and novelty as the biggest remaining challenges — AI doesn’t yet understand what makes a game genuinely fun — and he argues that as creation becomes easier, human curation becomes more valuable. Morris gives a more cautionary data point on sentiment: he cites GDC’s State of the Game Industry survey showing 52% of respondents said generative AI is having a negative impact on the industry, up from 30% last year and 18% the year before. He also notes players appear most negative about AI in core creative areas like art and narrative, while being more open to AI for dynamic systems such as difficulty adjustment. Morris closes with a concrete user-generated content angle: watching his 10-year-old build in Fortnite illustrates where AI could tap into youthful imagination to unlock UGC without requiring coding skills.