India’s rapid digital expansion is exposing millions of first-time online shoppers to increasingly sophisticated artificial intelligence scams. Amazon warns that low consumer awareness now presents a major challenge as e-commerce reaches smaller cities.
The company views education as equally important as technical protection. Fraudsters can use generative AI to produce convincing identities, forged documents, synthetic reviews, and targeted phishing messages.
AI Fraud Threat Grows Beyond Major Cities
Rohan Oommen, Amazon’s vice president for customer and partner trust, says India differs sharply from mature e-commerce markets. The country still adds large numbers of first-time users from tier-2 and tier-3 cities.
“India has a large number of first-time users entering the digital economy. Awareness is much lower, which makes education a significant part of the solution,” Oommen said.
In established markets such as the United States, online shopping adoption has largely stabilised. India’s expanding user base creates commercial opportunities but also widens the pool of potential fraud targets.
New shoppers may have limited experience identifying suspicious links, fake customer service calls, impersonation attempts, or manipulated reviews. These risks increase as fraud tools become cheaper and easier to operate.
Behavioral Data Strengthens Detection
Meanwhile, Amazon is using artificial intelligence to identify abuse across its marketplace. The company deploys automated systems, including agentic AI, to conduct continuous audits and detect unusual activity.
Oommen said behavioural patterns provide stronger fraud signals than submitted documents or images. Bad actors can fabricate identification records, seller profiles, and product information using generative tools.
“Behaviour is much harder to fake than documents or images,” he said. Amazon’s systems analyse years of seller and customer activity to distinguish legitimate behaviour from coordinated abuse. The models can flag suspicious account changes, review manipulation, unusual transactions, and other high-risk patterns.
The same technology strengthening criminal tactics can also improve platform monitoring. However, automated detection still requires human oversight, enforcement processes, and cooperation with external authorities.
Phone Scams Remain Harder to Trace
Additionally, Amazon’s latest Trustworthy Shopping Experience Report highlights the scale of its fraud enforcement. The company removed nearly 300 million fake reviews globally during the reported period.
Amazon also removed about 70,000 phishing websites and acted against roughly 14,000 phone numbers linked to scams. Oommen said phone-based fraud presents a tougher enforcement challenge than fraudulent websites.
Investigators can often identify website infrastructure, hosting records, and digital links more easily. Phone scams create attribution problems, especially when criminals use spoofed numbers or rapidly changing communication channels.
Amazon says it does not wait for new regulations before acting against fraud. Its response includes automated detection, account enforcement, consumer education, and cooperation with law enforcement agencies.
