Role exposure
Which employees or teams are most likely to receive voice-based requests with financial, access or reputational consequences.
Evaluate how exposed your people, channels and business controls are to AI voice impersonation across high-trust communications and approval workflows.
The main business question is not whether a synthetic voice is technically detectable in a lab. It is whether a believable voice can push someone to trust urgency, skip verification or misread authority inside a real workflow.
Deceptiment assesses the practical exposure around voice channels: who is targeted, which requests matter, what verification paths exist and whether security and operations teams can respond safely when a suspicious voice interaction occurs.
Which employees or teams are most likely to receive voice-based requests with financial, access or reputational consequences.
Where teams rely too heavily on caller familiarity, title or cadence instead of independent confirmation.
How WhatsApp, Teams, phone callbacks and mixed-channel follow-ups affect credibility and response behavior.
Whether suspected voice impersonation is routed quickly enough to the right control or incident owner.
Start with the functions most likely to receive urgent authority-based voice requests.
Improve call-back procedures, approval chains and out-of-band identity checks for sensitive requests.
Use the assessment to choose realistic AI vishing or executive impersonation scenarios for follow-up testing.
Repeat exercises after control changes so exposure reduction is demonstrated instead of assumed.
An assessment of how vulnerable roles, channels and workflows are to AI-enabled voice impersonation.
No. It focuses on organizational and workflow exposure rather than benchmarking media-forensics tools.
High-trust voice channels, verification habits, approval steps, escalation paths and response ownership.
Exposure observations, role priorities, control weaknesses, coaching needs and candidate simulation scenarios.
Use a risk-based assessment to identify where voice trust can become business risk before a live incident tests it first.
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