AI is becoming part of everyday production across game development, animation, digital content, and adjacent creative industries. It can already accelerate texture generation, concept art iteration, voice localization, quality assurance, and other execution-heavy tasks. The larger question for studios, schools, and young creatives is what happens when technical production becomes faster and cheaper, while originality, authorship, and creative judgment become harder to replace.

For game developers, this shift is changing both the production pipeline and the talent pipeline. Employers are starting to value people who can brief AI tools, evaluate outputs, understand workflows, and direct work toward a coherent creative vision. Technical skill remains important, but it is increasingly only one part of the equation. The ability to make creative and commercial judgments, especially in markets where original IP is still developing, is becoming a more important differentiator.

This is also a regional opportunity. Southeast Asia has deep reserves of mythology, history, language, and cultural identity that remain underexplored in global games and digital entertainment. If AI lowers the cost of production, smaller studios and training institutions may have more room to invest in original IP, rather than only executing work for external franchises or larger global studios.

In this TNGlobal Q&A, Kaveh Wong, Co-Founder of Xsolla Curine Academy and Founder of Curine Ventures, discusses how AI is reshaping creative workflows, hiring expectations, and talent development in game production. Wong, a Malaysian entrepreneur and venture builder whose work spans energy, technology, and the creative economy, shares why he believes the next generation of creative talent must learn to work with AI while still protecting the human authorship, cultural perspective, and judgment that make original IP valuable.

AI is now entering creative production workflows across game development, animation, and digital content. From your perspective, where is it already making the clearest impact, and where is the industry still overestimating what it can do?

The clearest wins are in production efficiency: texture generation, concept art iteration, voice localization, and QA automation. Tasks that used to take a junior artist a week now take an afternoon. Where the industry overestimates AI is in creative origination. A game lives or dies on its original story, its emotional hook, and its cultural specificity. AI cannot manufacture that.

What the industry is also underestimating is the market signal moving in the opposite direction. There is a growing worldwide consumer preference for human-authored creative work in music, film, and games. Studios that can credibly claim human authorship are already using it as a competitive differentiator. Expedition 33’s developer publicly stated that everything will be made by humans, and that became a marketing asset, not just an ethical position. That preference will only sharpen as AI-generated content floods the market and quality fatigue sets in.

At XCA, we’re responding to this directly. The efficiency gains AI delivers on the production side are being redirected into IP incubation. We’re investing in and developing original Southeast Asia-rooted IPs precisely because AI lowers the cost floor enough to make that bet viable for smaller studios. Southeast Asia is sitting on an enormous reserve of underexplored mythology, history, and regional identity. Black Myth: Wukong proved that culturally specific IP can win globally. That’s the opportunity we’re building toward.

The studios betting on AI to replace creative thinking will ship forgettable products. The smart ones are using it to free up capital and time for the work only humans can do.

In game development and adjacent creative industries, how are production roles changing as AI handles more routine or execution-heavy tasks?

The execution layer is compressing. Roles that were primarily about technical output, such as asset production, repetitive animation cycles, and boilerplate code, are being absorbed into AI-assisted pipelines. Malaysia proved this with God of War: world-class execution, but for someone else’s IP. The next generation needs to direct, not just deliver.

What’s expanding is the role of the creative orchestrator: someone who can brief AI tools effectively, evaluate quality, and direct output toward a coherent vision. Studios don’t need ten junior texture artists anymore. They need three who can prompt, iterate, and judge at speed. The ratio of directors to executors is shifting permanently.

For emerging talent, what skills are becoming more valuable as technical execution becomes easier to automate or accelerate?

Three things: creative judgment, systems thinking, and communication. All three must now be layered with AI literacy, but AI literacy means more than knowing the tools. At XCA, we’ve mandated a minimum 20 percent AI curriculum across all programs, structured in three layers. The first is execution: students use AI tools inside a real production pipeline from day one. The second is judgment: knowing when AI output is good enough and when it isn’t, and how to brief it effectively. The third is strategic: understanding what AI does to the economics of game development and IP ownership.

Most programs globally only teach the first layer. We think all three are non-negotiable. The talent who can operate across all three will outperform those who can only execute technically, regardless of how good the tools get.

What do employers now look for in entry-level creative or production talent that may not have been as important five years ago?

Cross-functional adaptability and pipeline awareness. Five years ago, a junior 3D artist needed to be good at 3D. Today, employers want someone who understands where their work sits in a broader production chain and can move across it.

At XCA, we’ve restructured our intake around this. We run short-term impact courses designed to assess exactly that adaptability: how quickly someone can acquire a skill, apply it in a real production context, and communicate across disciplines. The ones who demonstrate that get funneled into longer-term specialist tracks. That filter is increasingly what studios are asking us to run on their behalf.

We’ve also seen strong demand for people who understand the business of games: monetization logic, player psychology, and platform dynamics. Technical skill is table stakes. Commercial and creative judgment is the differentiator.

Many young creatives may worry that AI will reduce opportunities for junior roles. How should they think about building careers in an AI-assisted industry?

Stop treating AI as the threat and start treating it as the floor. Everyone will have access to the same tools. What differentiates you is what you build on top of them.

Our goal at XCA has never been to produce a Nike manufacturing hub. We want to create our own Nike brand, our own Malaysian-centric Southeast Asian IP. The same logic applies to individual careers. Develop a distinct creative voice, a cultural perspective, and a narrative instinct that no tool can replicate.

The platform model we’ve built at XCA reflects this honestly. We’re not promising jobs at the end of a course. We’re building a structured pathway: short-term impact course, real production exposure, and assessed conversion into a longer-term specialist role. That’s more useful to a young creative than reassurance. It’s a defined route with real gates, and the ones who clear them are the ones studios want.

How should training programs and academies adapt so graduates are prepared not only to use AI tools, but also to understand quality, workflow, and creative judgment?

Frankly, a traditional game development degree may not be the right answer for most people entering this industry. A three-year program governed by MQA requirements simply cannot iterate fast enough to stay current. By the time a curriculum is approved, the tools, pipelines, and roles it was designed for have already shifted. What the industry actually hires on is portfolio and shipped work. That’s why we built XCA around short-term impact courses that put students into real production immediately, not three years of theory with a credential at the end.

Beyond structure, curriculum has to be rebuilt around judgment and conversion. At XCA, we’ve mandated a 20 percent AI curriculum across all programs, but the design is deliberate: execution, judgment, and strategic understanding. Not a tool-familiarity module that goes stale in 12 months. We deliver it through live projects tied to our IP incubation program. Students working on real Southeast Asian IP development are using current tools by necessity, not by syllabus.

The result is graduates with portfolio work that is commercially positioned, not just technically competent. An academy that only teaches software produces graduates who are obsolete by graduation. We’re trying to produce graduates who have already shipped something that matters.

In creative production, where should companies draw the line between efficiency and preserving originality, authorship, and human direction?

AI should own the execution pipeline. Humans must own the creative thesis. The moment a studio lets AI determine what a game is about, such as its themes, its cultural voice, and its emotional stakes, you’ve lost the thing that makes players care.

This isn’t just an ethical position. It’s increasingly a commercial one. There is a growing and documented consumer preference for human-authored creative work globally. Albums, movie posters, and game assets generated by AI have faced public criticism and boycotts. Players notice. Audiences vote with their wallets. Studios that can credibly claim human authorship at the IP level are turning that into a competitive advantage, and that gap will widen as AI-generated content becomes ubiquitous and indistinguishable at the surface level.

The mechanism we use at XCA to institutionalize this is IP incubation. We invest in and develop original Southeast Asia-rooted IPs with a named creative lead, a defined cultural brief, and a human authorship trail from concept to pitch. Efficiency gains are captured aggressively at the production layer. But the IP itself, including its identity, its narrative direction, and its commercial positioning, has a human being accountable for it. That accountability is also what protects it legally and makes it fundable.

Everyone is worried AI will replace us. But AI can’t replace original ideas. Creators who build unique games with unique stories will always be irreplaceable. That’s where the future belongs.

Looking ahead, what can creative industries teach other sectors about the future of work, especially when human creativity is increasingly paired with AI tools?

The lesson is the same one I’ve been making about semiconductors: capital without talent is just hardware. Malaysia is investing billions into the semiconductor industry, but the real question is: who’s going to run these assets? Creative industries learned this the hard way. You can build the pipeline, fund the studios, and launch the programs, but if the talent can’t think, judge, and redirect, you’re just executing someone else’s vision.

But there’s a second lesson that’s less discussed: AI doesn’t just change how you make things, it changes what you can afford to own. Lower production costs mean smaller teams can now build and hold original IP. At XCA, that’s exactly what we’re doing, using the efficiency AI delivers to reinvest into Southeast Asian IP incubation and backing original ideas that would have been too expensive to develop five years ago.

That’s the playbook for any sector navigating AI. Use the cost reduction to move up the value chain, not just to cut headcount. Build adaptive talent, invest in what only you can own, and make sure a human being is accountable for the creative thesis at the top of the stack.