How Individuals & Businesses Can Spot When Bad Actors Are Using AI

Your finance team gets a call. It’s the CEO. She needs a wire transfer completed before the board meeting– it’s urgent. No need to loop anyone else in. By the time anyone questions it, the money is gone. 

As more people and businesses use artificial intelligence (AI), threat actors are using it too. For individuals and organizations, spotting the telltale signs of AI being weaponized is now a critical skill, but it’s getting harder by the day.    

AI gives attackers a direct line to the most vulnerable part of any organization: its people. With AI, attackers can convincingly mimic people with authority, create a sense of urgency, and strike a note of fear that drives people to act immediately, overriding their common sense before they even realize what happened.  

Mitigating these threats has to work at two levels simultaneously: the organizational and the human Without both you’re exposed, especially as employees often reuse credentials across home and work applications.  

The Four Big AI-Enabled Risks 

Increasingly, attackers streamline their operations by making social engineering attacks more believable. Here’s what I’m watching closely. 

DeepFake Audio and Video Attacks 

Deepfake audio and video attacks use AI-generated synthetic media to impersonate real people, like executives, public officials, or trusted partners with a level of realism that was impossible just a few years ago. These synthetic personas can trigger high-stakes actions like wire transfers, credential disclosure, or policy overrides, causing business impact like fraudulent financial transfers, reputational damage, or sensitive data exposure.  

For example, finance teams increasingly receive urgent “CEO requests” in voice calls that sound convincingly real, right down to the tone of authority and urgency. These attacks are even harder to detect now that AI reproduces tone, cadence, and facial movement with unsettling accuracy. 

When trying to identify these threats, look for subtle signs, like: 

• Slight lip-sync mismatches.
• Unnatural blinking or head movements.
• Overly polished or oddly flat vocal tone.
• Latency glitches during live calls.
• Slight facial warping during quick movements.
• Emotional deliverydoesn’tmatch the context. 

AI-Generated Phishing (Next-Generation Spear Phishing) 

AI-generated phishing campaigns leverage large language models (LLMs) to craft highly personalized, context-aware emails that mirror internal communications with alarming precision. Traditional grammar mistakes and spelling errors rarely appear in modern phishing emails. After harvesting credentials, attackers can pivot into lateral movement, data exfiltration, or broader business email compromise schemes. These emails reference real projects, mimic executive tone almost perfectly, and exploit scraped organizational and social media data to map reporting structures and responsibilities.  

Detection now depends on spotting subtler indicators: 

• Highly contextual emails referencing real projects.
• Perfect tone mimicry of executives.
• Subtle URL misspellings, like single character swaps.
• Requests that create urgency and secrecy.
• Slight deviations from usual writing style patterns.

AI-Driven Business Email Compromise (BEC) 

AI-driven BEC uses automation and style replication to uplevel traditional tactics. Modern AI systems can scrape prior email threads and mimic writing cadence, vendor invoice formats, and operational routing documentation. The financial damage is fast: fraudulent invoice payments, unauthorized bank account changes, supply chain disruption” flows better. Fraud looks like business as usual, rather than an intrusion.  

Some telltale indicators include: 

• Bank account changes with urgency.
• Slight formatting differences.
• New “reply-to” addresses hidden in headers.
• Domain spoofing with tiny character shifts.

AI-Enhanced Social Engineering 

AI-enhanced social engineering expands the attack surface beyond email into persistent, multi-channel psychological manipulation. Before introducing financial fraud, credential harvesting, or malware delivery, threat actors deploy fake recruiter bots, AI-generated personas, and automated chat agents that build real-seeming relationships over weeks or months. Malicious actors slowly build trust before exploiting their targets. 

AI accelerates this process by enabling them to create convincing persuasive interaction at scale, ultimately reducing the time spent on the attack which increases the overall return on investment (ROI). Since these attacks begin with a relationship rather than a malicious link, they are more difficult to detect.   

Warning indicators include: 

• Extremely fast, “bot-like” reply speed.
• Generic but persuasive emotional bonding.
• Refusal to get on live video.
• Image reverse search fails or shows stock origins. 

What Everyone Can Do to Protect Themselves 

AI-enabled threats exploit instinct and urgency. Protection starts by taking a moment to evaluate requests before acting. 

For individuals: 

• Adopt a “Verification Reflex”. Verify financial requests verbally via known number and using multi-channel verification, like calling and texting confirmation.  
• Go fully passwordless where you can. Traditional MFA is even easier to get past with AI-powered tools. Single-sign on using hardware-backed passkeys like Face ID, Touch ID, or YubiKey stops all but the most sophisticated attacks.   
• Enable SIM-swap protection. SIM swap attacks are especially dangerous for administrators. If someone hijacks your number, they can reset passwords, intercept MFA codes, take over admin accounts,and drain bank accounts. Ask your phone carrier to enable port-out protection, SIM-lock, and change requests need ID verification in-store only.   
• Freeze your credit. AI now enables attackers to scrape and reconstruct identities faster than ever.  
• Assume audio can be fake. Establish family and team code words. Never take urgency-based money or access requests at face value.  

For businesses, protecting against AI-enabled threat needs to work across multiple layers:

• Enforce financial controls.Require dual authorization for wire transfers, independent callback verification for bank-change requests, and written as well as verbal confirmation from known contacts. 
• Establishidentity validation protocols. Use code phrases for executive approvals, pre-approved authentication scripts, and video-authentication policies for sensitive calls. 
• Strengthen your technical stack.Enforce DMARC/DKIM/SPF, Advanced email detection with ML anomaly scoring, Cloud Access Security Broker (CASB) with Data Loss Prevention (DLP) monitoring, and user and entity behavior analytics (UEBA). 
• Build a governance layer.Create a formal deepfake escalation playbook. Run executive impersonation tabletop exercises. Include AI threat modeling in the risk register. Update SOC runbooks to include AI-driven threats.  

Shift From “Spot the Fake” to “Verify the Request” 

AI has erased the old security model that trained people to detect imperfections, like misspellings, awkward phrasing, strange formatting that subtly suggested something “felt off.” The new reality requires people to assume the message is polished, that the voice sounds right or the context is accurate. People and organizations must assume technical perfection and focus on scrutinizing intent.  

This shift requires taking a zero trust approach to communications, not just infrastructure. To identify modern attacks, organizations need insight into pattern-level indicators as attackers send hundreds of hyper-personalized emails simultaneously, containing the same emotional pressure language, and referencing internal code names with real stakeholders. When tone mirrors an executive too closely or LinkedIn details are copied, people must not assume authenticity. They must consider automation.  

AI dramatically improves adversary precision, allowing a fraud attempt to land during travel, an earnings call, a mergers announcement, or a public crisis. The timing is deliberate, and defenses have to be equally deliberate. 

About the Author: 

Satyam Patel is a results-driven Senior Security Advisor and CISO with over 25 years of experience protecting organizations from cyber threats. He excels at devising comprehensive security strategies, leading high-performing teams, and aligning security initiatives with business goals through effective collaboration with executive leadership and cross-functional stakeholders. 

A Certified Chief Information Security Officer (CCISO) through EC-Council, Satyam is a recognized thought leader who champions security awareness, compliance, and continuous improvement. His technical expertise spans application security, cloud security, identity access management, patch management, and more. 

Most recently at 247.AI, he spearheaded enterprise cybersecurity, implementing a strategic security program that significantly reduced breaches and introduced a dynamic Threat Vulnerability Management program. Previously as CISO and Director at CSA Group, he executed a 4-year cybersecurity strategy rooted in NIST and ISO standards for an international organization serving over 5,000 customers.