The cost of creation: AI is rewriting the economics of making games

From teams and timelines to testing and iteration, the shift could finally turn India's gaming scale into original intellectual property

Artificial intelligence (AI) is having the time of its life: Governments are unveiling AI missions, venture capital is pouring billions into startups, companies are racing to weave AI into products and services. As excitement around the technology gathers pace, so has the search for businesses likely to benefit from it.

 

Much of that conversation has centred on those building AI — model makers, chipmakers, infrastructure providers and startups. The bigger story, however, is in industries where technology quietly rewrites the economics of what was previously possible — an industry like gaming, for instance.

 

Long before ChatGPT entered the mainstream, AI was already embedded across the gaming ecosystem, powering non-playable characters, matchmaking, anti-cheat systems, recommendation engines and live-service operations.

 

Generative AI does not introduce AI to gaming — it changes where value is created. Instead of making games more intelligent, AI is becoming part of the production process itself by generating assets, accelerating prototyping, automating testing, improving localisation and compressing development cycles that once demanded far larger teams, longer timelines and significantly more capital.

 

India has built one of the world's largest gaming audiences but produced relatively few globally recognised gaming franchises. The industry’s biggest constraint was never a shortage of players — or even ideas. It was the cost of turning those ideas into intellectual property. Industry executives, investors and educators argue that generative AI is beginning to change that equation by making experimentation dramatically cheaper.

 

Building original gaming IP has traditionally demanded years of development, multidisciplinary teams and significant upfront capital long before a studio knew whether players would respond. AI does not remove that uncertainty. What it changes is the cost of navigating it, allowing more creators to build, test, discard, refine and try again before capital runs out.

 

By lowering the cost of creation, AI may also be changing who gets to build games. For an industry that has quietly lived with artificial intelligence for decades, that may prove to be the bigger opportunity. 

  Economics of experimentation

 

Gaming did not need generative AI to discover artificial intelligence. Games have relied on AI for decades to power everything from non-playable characters and matchmaking to anti-cheat systems and player recommendations. What generative AI changes is where AI now sits in the development process.

 

“Earlier, AI in gaming was largely back-end: NPC (non player characters) behaviour, matchmaking, anti-cheat or recommendation systems. Generative AI changes the front-end of creation itself,” says Rohit Agarwal, founder and director of AlphaZegus, a gaming-focused marketing firm.

 

AI is becoming part of the production pipeline itself, helping developers generate assets, accelerate coding, automate testing, improve localisation and shorten development cycles. At Krafton India, the Indian arm of Korean gaming giant Krafton, vice-president and head of publishing Minu Lee says AI is also helping studios iterate faster across development and live operations, allowing developers to spend less time on repetitive production work and more on gameplay, design and player experience.

 

“AI is reducing the cost of learning, not just the cost of production,” says Anurag Choudhary, founder of Felicity Games.

 

Every successful game is built on dozens of ideas that never make it to players. The expensive part is rarely creating an asset or writing code. It is spending months assembling teams, producing a game and only then discovering that players simply did not enjoy it. Generative AI is beginning to rewrite those economics by reducing both the time and cost of pre-production. Tasks such as concept art, asset creation, localisation and prototyping that once accounted for a large share of pre-production time and cost can increasingly be completed through AI-assisted workflows, allowing studios to test, discard and refine ideas before committing substantial capital.

 

That changes the economics of experimentation.

 

For Parth Chadha, co-founder and chief executive of STAN, a gaming community platform, that distinction is critical. “Building globally scalable IP takes 50 swings to land one hit, and the cost of each swing was historically too high,” he says. AI compresses the cost of every one of those swings, allowing developers to experiment more before capital runs out.

 

Lower experimentation costs also lower the barriers to participation.

 

“What smartphones did for creators was democratise distribution. AI is beginning to do something similar for game development,” says Sagar Nair, head of incubation at LVL Zero, a gaming incubator. Work that once required specialised artists, animators, localisation experts and quality-assurance teams can increasingly be supported through AI-assisted workflows, lowering the barriers to entry for smaller studios.

 

That change is already visible in India. “The gap between a small team and a credible product has shrunk significantly,” says Kashyap Reddy, founder of Metasports Interactive, a sports gaming startup. Rather than using AI to build larger productions, many Indian studios are deploying it to move faster across prototyping, personalisation, live operations and player acquisition—areas where speed often matters more than scale.

 

Taken together, those shifts point to something larger than faster production. AI may not improve the odds of building the next global hit. But by making experimentation dramatically cheaper, it allows far more creators to keep searching for one.

 

India’s IP moment

 

For India, this could be the moment when its scale finally begins to translate into globally recognized game franchises.

 

For years, the country’s gaming story has been defined by scale. According to Niko Partners, a video game market research and consulting firm, India became the fastest-growing gaming market it tracks in 2025, crossing the $1 billion revenue mark with 511 million players. That figure is expected to reach nearly 707 million by 2030. Yet, despite having one of the world's largest gaming audiences, India has produced relatively few globally recognised gaming franchises.

 

“The biggest gap has never really been audience scale. It has been the ability to consistently convert creative ambition into globally scalable products and IP,” Nair says.

 

Historically, that gap had less to do with imagination than the economics of building original games. Building original games demanded years of development, multidisciplinary teams and enough capital to survive repeated failures before finding a hit. AI is beginning to change that equation.

 

According to Anuj Tandon, India partner at Bitkraft Ventures, a gaming-focused venture capital firm, AI is lowering production barriers across art, coding, localisation and design, allowing smaller teams to build games that previously required far larger studios. More importantly, it makes it economically viable to experiment with mythology-inspired worlds, regional-language experiences and culturally rooted stories that global publishers have little incentive to build.

 

India already has early examples of original IP. Nodding Heads Games’ Raji: An Ancient Epic showed that a game rooted in Indian mythology could find a global audience despite being developed by a small independent studio. More recently, SuperGaming’s Indus Battle Royale has sought to build an original Indian science-fiction universe. Generative AI could make it cheaper for many more studios to pursue similarly ambitious IP without requiring the budgets of global publishers.

 

The change extends beyond studios. At the Sonipat-based World University of Design, vice-chancellor Sanjay Gupta says AI is allowing students and independent creators to prototype and iterate ideas much earlier in the creative process. At Hyderabad-based Mahindra University's School of Design Innovation, dean B K Chakravarthy says as AI takes over more of the execution, the competitive advantage shifts towards original thinking, storytelling and design rather than technical scale.

 

Investors are beginning to see the opportunity differently.

 

The Supreme Court’s recent decision to uphold the 28 per cent GST on the full face value of online gaming bets has effectively closed one of the industry's biggest legal battles while reinforcing a broader reset in the sector. For investors, however, the bigger story lies beyond real-money gaming.

 

“What we are witnessing is not a capital flight, but a structural pivot,” says Rathnakar Samavedam, investment director and managing partner at Hyderabad Angels Fund. As businesses built around transaction-led gaming come under pressure, venture capital is increasingly flowing towards original IP, AI-native development infrastructure and technology-first interactive entertainment.

 

Just as regulation is redirecting capital, AI is making those businesses more viable by reducing the cost of building, testing and iterating games. Interactive media and gaming VC fund Lumikai's  latest State of Interactive Media report argues that the next generation of breakout companies will be built around AI-assisted game development, AI-native technology stacks and “systems of play” that power interactive consumer experiences.

 

For years, India had the players but struggled to produce globally relevant gaming IP. AI does not guarantee that breakthrough. But as technology lowers the barriers to creation and investors increasingly back businesses built on original IP rather than transaction velocity, India may finally have something it lacked for years: A realistic chance to build gaming franchises that travel far beyond its own borders.

 

The new bottleneck

 

Making games is becoming easier. Standing out is not.

 

As AI lowers the barriers to creation, it is also likely to increase the number of games competing for players’ attention. Developers may be able to build faster, iterate more often and launch with smaller teams. None of that guarantees players will stay.

 

“The concern is very real,” says Rohit Agarwal of Alpha Zegus. Lower barriers will inevitably increase the volume of games entering the market, but more content does not automatically create better games. “The winners won’t be the teams that generate the most assets. They’ll be the ones that build compelling experiences.”

 

Across conversations with founders and investors, one theme surfaced repeatedly: AI can generate artwork, write code, automate testing and accelerate production. “The bottleneck is moving from capital to taste,” says Parth Chadha of STAN.  

 

For Harjeet Chhabra, chief executive of Neela Mediatech, digital entertainment and gaming studio, famous for creating Taarak Mehta Ka Ooltah Chashmah, AI’s biggest contribution lies in eliminating repetitive work rather than replacing creators. Storytelling, memorable characters and meaningful player experiences remain fundamentally human challenges.

 

That is also why investors believe AI itself is unlikely to remain a lasting competitive advantage. As the technology becomes more widely accessible, differentiation will increasingly come from intellectual property, communities and distribution rather than the tools developers use.

 

“The scarcest resource in gaming is no longer content creation. It is sustained player attention,” says Salone Sehgal, founder and managing partner at VC firm Lumikai. As AI dramatically expands the supply of content, she argues, the companies that consistently earn attention—not merely produce more games—will emerge as the long-term winners.

 

The dark horse

 

Much of India's AI conversation today revolves around foundation models, semiconductor infrastructure and enterprise software. Those are undoubtedly important. But technology cycles rarely create value only for those building the technology. They also reshape industries that quietly discover new ways of using it.

 

For decades, gaming has used artificial intelligence to make games more intelligent. Generative AI is beginning to do something different. It is making games easier to build.

 

This addresses one of the industry's oldest constraints. Indian developers have never lacked talent, ambition or players. What they lacked was an economic model that made repeated experimentation possible. AI does not guarantee the country’s first globally successful gaming franchise, nor does it replace creativity, storytelling or taste. What it does is make failure cheaper—and in an industry built on iteration, that may be its biggest contribution.

 

The ripple effects are already visible. Investors are shifting their attention towards original IP and AI-native gaming infrastructure. Universities are rethinking how the next generation of creators is trained. Smaller studios are building products that would once have required much larger teams. Developers are spending less time on repetitive production work and more on design, gameplay and player experience.

 

Perhaps that is gaming's place in India’s AI story.

 

The industry's opportunity is not that it has suddenly discovered artificial intelligence. It is that artificial intelligence is beginning to remove one of the biggest barriers it has faced for decades.

 

The biggest winners of the AI era may well include those building the technology. They may also be the industries whose biggest constraint was never imagination, but the economics of bringing ideas to life. For gaming, those are finally beginning to change.