How AI Voice Scams Turn Personal Phones Into a Business Risk

Can you still trust an incoming phone call when AI can imitate a familiar voice, personalize the conversation and target information specifically to you? In this episode, I speak with Alex Quilici, CEO of YouMail, about how artificial intelligence is changing phone fraud and why the personal devices carried by employees are becoming part of the corporate attack surface. Alex explains how YouMail uses data from its consumer call-protection service to identify scam behavior, understand the type of fraud taking place and connect those patterns with the phone numbers involved. Advances in large language models have improved this analysis, but the same technology is also helping criminals build far more convincing campaigns. Generic robocalls are being replaced by personalized conversations designed to extract information, impersonate trusted people and manipulate victims. Fraudsters can use AI throughout the attack chain, from identifying targets and analyzing stolen data to generating dialogue and adapting an approach during the call. Alex argues that attackers have adopted these capabilities faster than many defenders expected because successful fraud produces an immediate financial return. The conversation also examines why voice biometrics can no longer be treated as sufficient proof of identity. As voice-cloning tools improve, companies may need to combine multiple forms of authentication and move sensitive communications into trusted applications. A call received through a banking app, for example, could give the customer greater confidence that the caller really represents their bank. For businesses, the risk extends beyond company-managed technology. Attackers can identify where someone works, learn about their role and contact them through a personal phone that may sit outside corporate monitoring. An employee's private number can therefore provide another route into the business through impersonation and social engineering. Alex also makes a persuasive case for collecting less personal data. Personalization can improve a service, but every additional piece of information becomes something an attacker might obtain during a breach. His advice is to identify the minimum information needed to deliver the intended experience rather than gathering data simply because it may prove useful later. Despite the seriousness of the threat, Alex offers evidence that coordinated action can produce results. He has seen brand-impersonation campaigns reduced from tens of millions of calls each month to around 100,000 through monitoring, disruption and cooperation between businesses and telecommunications providers. If AI is making fraudulent calls harder to recognize, should businesses stop treating the telephone network as a trusted communication channel by default? Listen to the episode and share your thoughts with me.