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Businesses are responding to AI-enabled impersonation by making people part of a dependable verification process—not by asking employees to guess whether a voice, video, or message is fake. For consequential requests, the safer routine is to pause, confirm through a trusted route already on file, and report anything suspicious. That matters for finance teams in particular: an apparently familiar caller or executive message should not replace established payment and approval controls.
Why businesses are emphasizing human verification
Deepfake-enabled social engineering is being reported across both voice and video. In Gartner’s March–May 2026 survey of 297 senior cybersecurity leaders, 41% said their organization had experienced at least one social-engineering incident involving a deepfake during an employee audio call in the previous 12 months; 36% reported at least one involving a video call. These are survey responses from senior leaders, not a census or a universal rate for businesses. Gartner’s 2026 survey
The practical point is not that every call is suspect. It is that familiar voices, faces, and writing styles are no longer sufficient proof of identity when someone asks for a sensitive action. A caller may sound like a manager; a video may appear to show a colleague; a collaboration message may arrive in a familiar account. Verification should depend on a separate, trusted process rather than the realism of the request.
What to do when a request could move money or expose data
Gartner recommends training employees and approvers to “pause, verify, and report high-risk requests” regardless of whether they arrive through email, voice, video, collaboration tools, or an AI application. The recommendation, attributed to CISOs in Gartner’s release, is about consistent behavior across channels—not about identifying synthetic media by eye or ear. Gartner’s guidance
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- Pause before acting. Treat urgency, secrecy, a change to payment instructions, or a request to bypass normal approval as a reason to stop and check—not as a reason to hurry.
- Verify through an established route. Contact the requester using a known number or address already held in company records, or use the organization’s approved internal verification method. Do not rely on contact details supplied in the suspicious request or simply call back the number that called.
- Apply the normal approval controls. Follow required authorization and separation-of-duties procedures for transfers, vendor changes, account access, or sensitive disclosures. A familiar voice or video should not substitute for a required second approver.
- Report and escalate. Use the designated security or fraud-reporting channel, especially if the request pressures someone to avoid verification or a transfer or disclosure may already have occurred.
These steps work because they test the request through an independent channel and preserve routine controls. They do not depend on an employee making a reliable judgment about whether a clip or voice sounds artificial.
Why training needs to include practice
Knowing the rule is different from being able to follow it under pressure. ISACA’s 2026 State of Cybersecurity survey, which included more than 1,800 cybersecurity professionals globally, found that 8% of surveyed organizations regularly conducted AI-specific response exercises, while 64% had conducted none. Those figures describe the survey’s respondents, not every organization worldwide. ISACA’s survey findings
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An exercise can rehearse the handoffs that matter: who verifies an unusual request, who can stop a payment, how employees report a suspicious call, and who coordinates if information or funds may already be at risk. AI-specific practice can include a convincing impersonation in more than one channel, but the objective should be to test the organization’s verification and escalation process—not to grade staff on spotting a deepfake.
People are part of the threat as well as the defense
“Human-centered” security does not mean that a person is always the safeguard. Anthropic’s September 2026 report describes disrupted activity from December 2025 through August 2026 across seven harm areas. In its account of cyber operations, it says humans remained involved by setting attack targets and reviewing exfiltrated information. AI may scale parts of malicious work, while people still direct or validate elements of an operation. Anthropic’s September 2026 report
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That is another reason not to frame security as people versus technology. Organizations need controls that make unauthorized actions harder, people who know how to verify and report, and response plans that can be used when an incident is underway.
Why stronger technical controls do not eliminate social engineering
Visa’s Spring 2026 threat report says criminals are redirecting effort away from technical system compromise toward exploiting human trust. The report also says fraud involving device tokens on Visa’s network declined 9.6% from July–December 2025 compared with the same period in 2024. That is a finding about Visa’s network and a specific fraud category; it does not show that fraud overall declined. Visa’s Spring 2026 report
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The broader lesson for a business is that technical protections and verification routines address different risks. A control that reduces one form of technical fraud does not prove that a request from a supposed executive, supplier, or colleague is genuine. Payment changes and unusual requests still need the organization’s independent checks.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Businesses are also using AI defensively
AI can be used to support defense as well as deception. Experian’s August 19, 2026 release says 80% of businesses surveyed used AI to combat emerging threats. Among the AI-related fraud concerns it lists were AI-generated phishing (53%), AI-assisted first-party fraud (51%), document forgery (45%), automated bot attacks (40%), and deepfake voice scams (37%). The release’s figures are Experian survey results; its published summary does not establish a population or methodology detailed enough to treat them as universal business rates. Experian’s release
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AI-based tools may help organizations detect patterns or prioritize review, but these survey figures do not establish that a particular tool can reliably identify every deepfake. They are not a substitute for clear authorization rules, independent identity checks, and practiced incident response.
How to assess a business response plan
A useful plan can be evaluated by whether staff can apply it consistently, whatever channel an attacker uses. For finance leaders, security teams, and approvers, the core checks are:
- Channel coverage: Does the procedure apply to email, calls, video meetings, collaboration platforms, and AI applications?
- Trusted verification: Does it tell employees exactly how to reach the requester independently, using contact details or methods already established?
- Action controls: Are approval requirements clear for payments, bank-detail changes, access grants, and sensitive disclosures?
- Escalation: Can employees quickly report a suspicious request and reach someone empowered to pause a transaction or contain exposure?
- Rehearsal: Has the organization practiced an AI-related scenario so that people know their roles under time pressure?
These are process questions, not a ranking of products. The cited findings do not compare named vendors or establish that any detector works against all deepfakes.
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