Indian telcos are experimenting with AI as a defense.
Every day, millions of Indians answer phone calls only to be welcomed by a stranger! A telemarketer pushing loans, an insurance agent trying to sell a policy, or worse, a scammer using a voice that sounds unnervingly real. Some of these calls are just frustrating. Others are sophisticated, AI-driven attempts to steal money or personal data.
The Hiya Global Call Threat Report 2025 identified approximately 137 million suspected spam calls daily worldwide, with India being a significant contributor to this number.
Surveys further indicate that many consumers in India receive at least three spam calls a day, often involving emotional manipulation or financial scams that aim to exploit their trust and confidence.
For a country with over 1.2 billion mobile subscribers, multiple languages, and varying digital literacy, curbing this menace is no small feat.
AI steps into the fray
While spam calls are a universal issue, Indian telcos are experimenting with AI as a defense. Bharti Airtel, for instance, recently reported that its network-level AI solutions resulted in a 68.7% decrease in financial losses and a 14.3% drop in overall cybercrime incidents, according to the Indian Cyber Crime Coordination Center (I4C).
As an Airtel subscriber, you may notice that suspicious calls are now flagged before your phone rings, eliminating the need for third-party apps that often compromise your privacy. “We see this as a small step in a much larger fight. We will continue to innovate until our networks are free of digital spam and scams,” says Gopal Vittal, Vice Chairman & MD, Bharti Airtel.
Unlike traditional spam-blocking apps that rely on user reporting, Airtel’s system operates deep within the network, analyzing billions of calls and links daily to detect suspicious patterns automatically.
Not all telcos are moving at the same pace.
- Vi (Vodafone Idea) has launched ‘Vi Protect’, an AI-driven safety suite that protects consumers and enterprises alike by filtering spam and phishing across voice and SMS.
- BSNL is using edge-level AI to block smishing (SMS phishing) before messages even reach the user.
- Jio, meanwhile, still relies heavily on user action, encouraging DND activation and reporting, though internal AI systems may soon automate detection.
The use of AI to deal with spam and cybercrime is not entirely new for telecom service providers. Between 2010 and 2012, operators such as Singtel began integrating AI and analytics for network-level spam detection.
Regulation: India vs. the World
In India, regulators have taken necessary steps to control spam and unsolicited communications. Two key measures are the Distributed Ledger Technology (DLT) system for A2P (application-to-person) messages and the Digital Consent Framework (DCF) for marketing communications.
The DLT system requires telemarketers to register their numbers and message templates, making it easier to trace and hold them accountable. The Digital Consent Framework ensures that users can actively choose what kinds of promotional messages they want to receive, giving them greater control over their inboxes and phones.
However, there are still gaps in enforcement. Scam calls can bypass these systems in several ways. For example, by using SIM farms (large volumes of prepaid SIM cards for automated calling), foreign VoIP numbers that appear local, or by telemarketers operating without registration. These loopholes mean that, despite the regulatory framework, many unwanted calls still reach users.
In August 2024, TRAI mandated telecom operators to disconnect and blacklist for two years any entity found misusing bulk connections for spam calls. The directive aims to curb the growing menace of robocalls and spam messages. It also instructed operators to disconnect all telecom resources of unregistered telemarketers found making spam calls. While this measure is expected to significantly reduce spam calls and provide relief to consumers, there is still a long way to go.
Other countries have combined regulation with technology in different ways. In Singapore, for instance, the Infocomm Media Development Authority (IMDA) utilizes AI-based traffic analysis to identify spam patterns, in conjunction with mandatory caller ID authentication, to ensure that the number displayed on the recipient’s phone is genuine. In the United States, the FCC enforces the STIR/SHAKEN protocol, which verifies the origin of voice calls and penalizes violators heavily, particularly for robocalls and spoofed numbers.
Meanwhile, Australia maintains a sender-ID registry for SMS, ensuring that promotional messages originate from verified sources and are backed by strict enforcement against those who violate the rules.
These global examples demonstrate that technology alone is insufficient to achieve this goal. AI can detect suspicious calls, but it works most effectively when combined with robust regulations, collaboration among telecom operators, and informed users. Only this combination can significantly reduce the flood of spam calls and protect consumers.
The human impact
Spam calls are not just statistics; they have a real impact on people’s lives. They can erode trust in phone communications, disrupt daily routines, and, in some cases, lead to financial loss. Certain groups, such as elderly users or those in rural areas, are particularly vulnerable to vishing, where scammers impersonate trusted entities over the phone to steal money or personal information.
While network-level AI systems can detect and block many of these fraudulent calls before they reach users, technology alone is not enough. User education is equally important, as it helps people recognize scams and respond safely.
The fight against spam is evolving, moving into a more sophisticated phase. Key strategies include:
- AI-enabled networks that analyze billions of calls and messages in real time to identify suspicious activity.
- Collaboration between telecom operators enables the sharing of threats and verification of caller identities, thereby preventing impersonation.
- Public awareness campaigns, especially in regional languages, should educate users about common scams and safe practices.
- Independent audits of AI systems to ensure they are accurate, reliable, and respectful of privacy.
- Partnerships between telecom companies and banks to detect and prevent fraud that involves impersonation of financial institutions.
If these measures are widely adopted, it may finally become possible for users to experience a phone that rings only when it should, free from the constant disruption and risk posed by spam.