artificial intelligence is changing the way cybercriminals manipulate human behavior.
Previously clear signs of phishing emails, such as boring wording, generic salutations and dull formatting, are being replaced by sophisticated pop-up messages built from broad language models.
Deepfake technology can now even clone a CEO’s voice to create a compelling video message in minutes. This technique has already been used to defraud organizations worth tens of millions of dollars.
In LevelBlue’s Social Engineering and Human Element report, 59% of companies say employees have a harder time distinguishing between real and fake interactions.
Meanwhile, attackers are increasingly combining AI-based social engineering with supply chain compromise, identity theft and automated reconnaissance.
Together, these vectors transform social engineering from a workforce problem to a systemic business risk.
A growing gap
The gap between awareness and action is widening. While technical controls continue to evolve, human behavior remains the most exploited vulnerability.
After all, computer systems are easier to repair than people. Attackers have learned that it’s often easier to fool someone than hack into a system, and AI gives them the speed and precision to do both.
The new tactical advantage of AI
Dynamic vector circuit: Bad actors can start by sending a benign email, measure engagement (opens, clicks) and then move within the same thread to deliver a voice or video payload. This mobility makes static awareness training less effective.
Large scale personality creation: Using aggregate data from social media and security vulnerabilities, attackers can create credible digital personas with names, roles, and tone of voice and use them to infiltrate organizations.
Deepfake Escalation: You can insert AI-generated audio or video during the call: “Sorry, I left my phone in another room, call me on this line” or “Here are the updated transfer instructions.” Familiarity with a familiar voice or face can cause employees to lose focus.
Conflicting messages and series of messages: Attackers repeatedly refine generative AI suggestions: “Make it more formal” or “Insert a line about quarterly performance.” Each iteration makes the message more credible and specific.
These technologies blur what is “normal” in digital communication. Even the most experienced security experts struggle to draw the line between authentic and artificial.
For man is always the cornerstone
Technical defenses such as email filtering, zero-trust architecture, and anomaly detection are still important, but AI-powered attacks rely on judgment, not code. Ultimately, every social engineering campaign is based on the human decision to click, share, approve or allow.
Resilient organizations understand that true security involves both locking down systems and integrating judgment into workflows. How to achieve this balance?
1. Management engagement and AI awareness
AI-based social engineering should be treated as a critical business threat. All managers, CTOs and DevOps teams need insight into how AI can manage APIs, customer journeys or internal processes.
When the board integrates AI risk into governance, along with scalability and compliance, investment in people increases alongside investment in technology.
2. Simulate the AI attack chain
Annual phishing tests no longer reflect the current threat landscape. Modern red team exercises are expected to replicate AI-powered attacks, bringing together emails, voice commands and deepfakes in the same simulation.
Monitor data such as when users notice anomalies and how they react to increasing fraud. This helps identify areas where training or process reinforcement is most needed.
3. AI detection with human filters
Companies must combine AI-based detection engines, such as deepfakes, voice anomalies and behavioral analysis, with structured human verification.
Suspicious content should trigger out-of-band query responses or confirmation checks. AI can detect anomalies, but humans provide context and intent. Together they form a closed defense circle.
4. External benchmarking and development training
Threat actors are constantly innovating and defenses must do the same. Working with cybersecurity experts to conduct regular Red Team-as-a-Service assessments can identify blind spots and update training based on new AI tactics.
Continuous modular learning, updated quarterly with real-time threat data, ensures teams stay up-to-date, unlike last year.
Building Human Resilience in the Age of Artificial Intelligence
Generative AI has blurred the line between authentic and artificial, but it has also reinforced the importance of human judgement. Technology can detect anomalies, but only humans can decide whether to trust, verify or act.
The companies that will be ahead are those that recognize this interaction: combining AI-powered defenses with a culture that encourages curiosity, critical inquiry and critical thinking.
Cybersecurity is more than a race against technology; It is a race that aims to strengthen the human element within us.
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