The "perfect sandbox": Why India has become ground zero for AI-driven ad scams

Artificial intelligence has not just supercharged ad fraud. It has fundamentally rewritten it. In India’s massive mobile-first, performance-driven digital market, the fraud ecosystem is evolving faster than the systems built to contain it. What once required organised fraud rings can today be executed by a single operator with an open-source model.

Across founders, verification experts and ad-tech leaders, one theme is consistent: fraud is no longer a scale problem. It’s a sophistication problem.

Deepfake Influencers And Synthetic Founders: Scam Creators At Zero Cost

The first frontier of AI-fuelled fraud is the explosion of deepfake influencers and synthetic founder personas.

Rajiv Dingra, Founder and CEO of ReBid, calls this shift “disturbingly common”. “Fraudsters no longer need real creators — generative AI lets them fabricate hyper-realistic influencers or fake founders who look credible, speak fluently, and endorse products that don’t exist. These deepfake personas are now being deployed at scale… the cost has dropped to almost zero, but the impact on user trust is massive.”

Akshay Mathur, CEO and co-founder, Unpromptd expands the frame, noting that the incentive structure behind these personas is entirely different from real creators. “They do not need contracts, compliance guidelines, or talent rights. They also cannot be sued or held accountable.”

But the bigger concern, Mathur warns, is what synthetic creators are evolving into. “These personas are becoming tools to test cultural cues, accents, wardrobe, and narratives at low cost. Fraudsters now run market research using AI characters. They test what people react to and then scale those versions.”

This moves ad fraud from deception into behavioural engineering.

Clone Publishers, Composite Publishers And MFA 3.0

The cloning of legitimate publisher websites was once fringe. It is now a mainstream fraud vector.

Dingra says this is one of the fastest-rising threats. “AI tools can scrape and replicate an entire news or entertainment website — layout, fonts, tone, even bylines — in minutes. These cloned sites are plugged into programmatic exchanges and misrepresent themselves as premium publishers.”

Mathur adds that fraudsters have begun shifting from simple clones to composite publishers. “They blend layouts, typography, and content styles from multiple trusted sites to create something that feels familiar but is not an exact copy. These sites appear more legitimate during audits because they’re not direct replicas.”

Dhiraj Gupta, CTO and Co-founder of mFilterIt, says this sits within a broader surge of AI-generated MFA and “AI-slop” websites. “AI is accelerating fraud in ways we’ve never seen before. Fraudsters can spin up hundreds of low-quality sites with autogenerated content and synthetic traffic, making the supply chain look legitimate on the surface.”

Programmatic buying is especially exposed because verification layers have not fully modernised.

Mathur puts it bluntly: “Most verification layers still evaluate impressions at the surface level. As fraud becomes more generative, the supply chain audit needs to become more generative too.”

AI Botnets: From Dumb Clickers To Adaptive “Performance Marketers”

Old botnets were simple: click, bounce, repeat.

The new ones behave like carefully trained users.

Dingra says today’s botnets mimic complete digital journeys:

• scrolling at human-like speeds • pausing unpredictably • watching videos to completion • filling lead forms with synthetic details • idling like distracted humans

“Traditional fraud detection relies on pattern recognition. But AI botnets randomize behaviour so effectively that they blend into average user benchmarks.”

Mathur says the real challenge is diversity, not mimicry. “Bots today mimic diverse human behaviour. AI changes patterns faster than detection models can stabilise. They introduce imperfections to appear human.”

He adds that AI botnets now operate exactly like performance marketers.

“They optimise their behaviour in real time to get past detection. They switch IPs, rotate devices, alter scroll velocities. This is no longer brute force fraud. It is adaptive fraud.”

Gupta says these AI-driven journeys are now specifically targeting outcome-based campaigns.

“Performance campaigns are especially exposed because KPIs like installs, leads and sign-ups can be spoofed at scale. When your detection layer can’t tell a real user from an AI-trained bot, your ROAS collapses first.”

Generative AI As A Fraud Factory: 100 Landing Pages Before Lunch

Fraudsters no longer need design or development resources. Generative AI has industrialised scam production.

Dingra explains, “Fraudsters can spin up hundreds of templated landing pages in multiple languages… each with different headlines, product mockups, testimonials and CTAs. By the time one scam page is blocked, hundreds more are already live.”

Mathur argues the critical shift is the speed of optimisation. “Fraudsters can now run creative optimisation loops that rival legitimate advertisers. They generate a hundred pages, see which ones convert, refine the best performing versions. AI has simply given fraud the machinery to optimise the funnel at industrial speed.”

Why India Has Become The Global Testing Ground

Gupta says the reason India is ground zero for AI-driven fraud is structural.

“India combines scale, fragmentation, and performance-driven buying — it is the perfect sandbox. Millions of impressions and installs can be tested instantly. The affiliate and reseller-heavy ecosystem gives fraudsters a decentralised playground to experiment.”

Once tactics succeed in India, they spread globally.

“Fraud evolves in India faster than anywhere else — and once it works here, it quickly travels to global markets.”

SMBs Are Now The Preferred Victims — But Enterprises Aren’t Safe Either

Gupta confirms that AI-driven attacks disproportionately target small advertisers. “AI-generated schemes — synthetic installs, fake sign-ups, bot-driven cart events, deepfaked influencer traffic — are increasingly directed at SMBs because the ROI for fraudsters is higher.”

But the same patterns are now creeping into enterprise pipelines. “Brands with strong AI-led validation layers can contain it early. Those without end up funding these AI-driven fraud economies.”

Are Platforms Losing The Race? Not Completely.

Mathur offers a more balanced view—fraud is accelerating, but so is enforcement.

“Platforms shift their integrity stack every two to three years. AI is both the accelerant and the antidote.”

He says the future of fraud detection will look less like spam filters and more like antivirus evolution.

“Ad integrity will move from individual impression checks to ecosystem-level anomaly checks. Platforms will use their own large-scale AI to classify synthetic behaviour patterns that humans cannot see.”

Mathur captures the final, structural truth. “Fraud is not just a technical challenge. It is a market design challenge. The more automated the ad ecosystem becomes, the more automated the fraud ecosystem becomes. The platforms that win will be the ones that design their systems so that fraud becomes economically unviable and operationally exhausting.”