But along with new opportunities, it has expanded the potential for security threats capable of undermining a company’s reputation, financial stability, and customer trust. Among the most concerning of these is the rise of synthetic voice technology, or “deepfakes”, which is rapidly reshaping the cyberthreat landscape.

“Social engineering has always been a concern, but AI is enabling criminals to operate on an entirely new level,” says Douglas Tait, director of product marketing at Oracle Communications.

“These attacks don’t just harm finances, they erode trust, overwhelm customer service teams, and damage brands irreversibly.”

Yet, despite the clear risks, many companies remain stuck in a reactive mindset. “Most organisations still take what I call a ‘postmortem’ approach,” Tait explains.

“They wait for the breach to happen, then forensics teams try to capture the perpetrators, but by then the damage is done. Financial loss has occurred, brand perception is tarnished, and customer trust is eroded. This approach simply isn’t sufficient anymore.”

As AI-generated voice attacks become more convincing, a reactive strategy is increasingly ineffective. Instead, Tait advocates a proactive approach to voice security, one that intercepts threats before they can inflict harm.

The urgency is underscored by the latest figures: Onfido’s Identity Fraud Report 2024 highlights a 3,000% increase in deepfakes in just one year. “The combination of accessible AI tools and the ingenuity of cybercriminals means businesses need to act now,” says Tait. “Proactive defence isn’t just about detecting fraud, it’s about anticipating it.”

Oracle Communications divides proactive voice security into two complementary strategies: digital analysis and analog analysis.

Digital analysis: Mining metadata for threats

In today’s VoIP-driven environment, every call carries a wealth of metadata—information that often goes unexamined. Caller numbers, time, date, location, call quality, voicemail details, conferencing info, all of these seemingly mundane data points can be cross-referenced with known threat databases.

“By orchestrating machine learning and AI on the s metadata allows us to identify behavioural patterns, such as repeated social engineering attempts, denial-of-service calls, or even repeated deepfake sources,” Tait explains.

“Thanks to cloud computing and AI advancements, this level of analysis can now be performed quickly and cost-effectively, even before the call connects.”

Analog analysis: Decoding the human element

Beyond metadata, voice itself can be a rich source of insight. Advanced real-time audio services can examine speech patterns, tone, language, and context to detect anomalies or malicious intent. These intelligent systems act as gatekeepers, alerting security teams before harm occurs.

“By orchestrating speech-to-text algorithms, sentiment analysis, large language models, and conversational AI, we can monitor conversations in real time,” says Tait. “These subtle cues often escape the human ear but can indicate an attempt at fraud or social engineering, allowing immediate intervention.”

A multi-layered strategy

Together, digital and analog analyses form a multi-layered proactive defence. They monitor deviations from normal behaviour, unexpected conversation content, or anomalous calling patterns. When warning signs are detected, immediate action can prevent an attack from succeeding.

“This approach minimises financial and reputational harm, protects customers, and even deters attackers by making successful attacks harder to execute,” Tait emphasises. “Ensuring the authenticity of voice interactions strengthens trust in digital communication and helps create a safer online environment.”

The future of voice security

For Tait, the message is clear: proactive voice security is no longer optional. “Companies that embrace AI-driven, proactive defence will safeguard customer relationships, protect their brand, and maintain a competitive edge. Those that fail to adapt face escalating risks, financial loss, reputational damage, and erosion of trust, which can jeopardise their long-term success.”

The future of voice security, he concludes, lies in anticipation, not reaction. Investing in a secure, AI-driven infrastructure isn’t just smart, it’s essential.

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